Bytebeam

bytebeam

IoT Background The phrase “Internet of Things” was formulated in 1999, prerequisite of it was radio-frequency identification(RFID) — to automatically identify and track tags attached to objects. electromagnetic fields Due to the widespread distribution of wireless networks, the emergence of cloud computing and the development of software-configurable networks in 2010 — conception of “Internet of Things” filled with a variety of technological content and implementation of practical solutions. In 2017 IoT become in more than only cyber-physical system for “home” using, it expanded on industrial objects (IIoT). Here is one of forecasts from NCTA about future of IoT market: NCTA Certainly, the market of “Internet of Things” will dynamically grow and develop. But all solutions must be stable, light and secured. BIoT solution The Byteball infrastructure is ideal for the Internet of Things (IoT) sphere: сore can be run on any platform that supports node.js, ready to work in 0.1 second, low technical requirements: 128MB of RAM and 8MB for the database.Therefore, we want to create a system for IoT and micropayments. We will build an architecture for fast and convenient work of developers with byteball and using javascript or any other programming language capable of working with JSON-RPC, WebSocket or other platform.Main advantages of payment channels are: reducing the cost of transactions(paying only for the channel openning and closing), acceleration of transactions, secured spending of funds. payment channels Our system will work on the punishment-based payment channels, where funds are blocked in multisig contract between the channel sides and to ensure the correctness of actions, the parties sign transactions that are carried out, but not published on the network.If a party publishes old data, it is punished and deprived of all means. Some of our cases: payments, management and communication. Charging your electric car, using a smart home appliance, watching a paid broadcast or using the Internet — this and more can be managed and paid by using BIoT. The capabilities of the Byteball platform allow communication between IoT devices. BIoT permit you to manage and monitor the process of payment and communication between devices by using our client on your smartphone or as in this case on the onboard computer of the electric car. Our solutions allow you to control different devices by using wireless connections (Bluetooth, Wi-Fi and etc.). And in combination with the Internet - you get full control over all kinds of devices in one application. This all gives more opportunities in the further development of the our product. Nearest plans Creating a testing DIY that demonstrates the real work of channels. Protocols support, documentation for protocols and CLI(Command Line Interface). Maximal optimization of channel creation and operation. A realtime HTML5-enabled client(pc/android/ios) to interact with the IoT device. DIY devices Contact us Follow our for last news, and join our community on .Our github profile — Send us your questions and suggestions on - Twitter Telegram BIoTws . team@biot.ws .

Welcome to BIoT — IoT solutions on Byteball platform!

Byteball is an innovative cryptocurrency, launched in 2016 25th December. Unlike many others, it has an interesting take on many concepts, including a solution to the governance problem, it is not only r_ule-enforcing_, but also has a very innovative governance process for rule- which includes the users. making Digital currencies such as Bitcoin is very good at rule-enforcing, without specifying mathematically who the rule makers are and their intent. As Bitcoin scaling problem shows where miners, full node operators, businesses and users are in conflict over which rule, how and when or if to activate it — a rule making process is needed. Cryptocurrencies must not only rule-enforce but also have a mechanism to resolve future issues and follow new rules. Ethereum showed with its forking and changing of existing rules, ie mutable immutability, that a rule- can be the initial developers and investors. To protect their investments, the immutable promise and rule was changed, breaking the cryptographic/mathematical promise. This solution, from the perspective of users, is similar to trusting a third-party. Most cryptocurrencies with a Foundation follow this path. maker We need a cryptocurrency where the of the system are also part of the governance model and can hold the rule-makers accountable and replaceable. Where the power of each rule-maker is limited. users Byteball is the solution. The unique composition of decentralized, distributed system, not fully trust-less, with a DAG instead of block-chain, and without trading Proof-of-Work/energy-waste for security — also hands power to the users. The rule- is done by a majority of 12 witnesses, each of which can be replaced, and each of which does not have to be trusted individually, or continuously online. Only a majority of witnesses has to be trusted to not conspire. The users are allowed to change 1 witness in their witness-list relative to the the rest of the network — this allows gradual replacement of all witnesses, and more witnesses to be active at same time on the network. enforcement The user has the power to select and replace the rule-enforcer in Byteball, with a simple click in a change of settings, becomes the rule-maker. The witnessing in Byteball gives users of the system a powerful voice over rule-enforcers, while avoiding wasting energy for security as in traditional systems. A potential weakness could be dis-interest of users to select their witnesses, or merely selecting a group who would conspire for total control, the given choice is as much a potential weakness as it is powerful. This article was inspired by from if you like it, see and help us build the best currency in our Slack. Vili Lehdonvirta http://blogs.oii.ox.ac.uk/policy/the-blockchain-paradox-why-distributed-ledger-technologies-may-do-little-to-transform-the-economy/ https://byteball.org is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising & sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

Byteball as solution to blockchain governance

The Greedy Miner’s Dilemma: Flaws in DAG-Based Consensus Protocols

Table of Links Abstract and I. Introduction II. Background III. Problem Definition IV. DAG-Oriented Solutions V. Game Theoretical Analysis VI. Simulation Model VII. Evaluation VIII. Countermeasures IX. Discussion and Future Work X. Related Work XI. Conclusion and References X. RELATED WORK DAG-Based Consensus Protocols The benefits of blockchain protocols come with certain trade-offs when balancing decentralization, scalability, and security. We have already mentioned the bottleneck in Nakamoto’s consensus protocol, and therefore, alternative approaches are emerging, such as DAG-based protocols. Beside DAG-based protocols, also 2nd layer [38], [37], [21] and sharding designs [29], [51], [23], addressing the same problems, had emerged. However, in the current work context, we solely focus on DAG-based designs. Wang et al. [48] performed a detailed systematic overview of DAG-designs. They described six categories containing more than thirty DAG-based blockchain systems classified based on their characteristics and principles. They extend the commonly used classification based on the type of ledgers [47]. GHOST [45], Inclusive Blockchain [26], Conflux [27], Haootia [47], and Byteball [3] represent DAG with the main chain. Hashgraph [24] and Nano [25] represent ledgers with parallel chains. Nevertheless, out of these categories, DAGs with the main chain are related to our research, such as Inclusive [26], SPECTRE [43], PHANTOM and GHOSTDAG [44]. We refer the reader to Sec. IV for details about these protocols. Performance Analysis of DAGs While many papers deal with the security and performance analysis of mentioned protocols, they consider neither mining strategy nor features of various incentive schemes. Park et al. [35] address the performance of DAG-based blockchains and relate it to the optimization of profit. They show that the average number of parents n can influence the transaction processing time. As a result, they propose a competitive-based transaction process system using a dynamic fee policy. Birmpas et al. [8] propose a new general framework that captures ledger growth for a large class of DAG-based implementations to demonstrate the structural limits of DAGbased protocols. Even with honest miner behavior, fairness, and efficiency of the ledger can be affected by different connectivity levels. One of the key technical problems of DAG-based protocols is identifying honest blocks. Wang proposes a MaxCord [50], a framework using a different approach for honest block identification problems using graph theory. Based on the definition of the disparity measurement between blocks, they convert the problem into a maximum k-independent set problem. Cao et al. [10] compared the performance of three consensus mechanisms: Bitcoin (PoW), Nxt (PoS), and Tangle (DAGPoW) in terms of parameters such as average time to generate a new block or confirmation delay and failure probability, showing how these mechanisms can affect the state of network resources or network load condition. Sycomore [2] and its extension Sycomore++ [12] is another DAG-oriented consensus protocol that utilizes DAGs to increase Nakamoto consensus throughput. The protocol proposes that the chain responds to the dynamically increased number of transactions and splits them into multiple chains, thus creating DAG structure. When the number of transactions decreases (utilization of blocks is reduced), the branches can be rejoined back into a single chain. Transactions are evenly partitioned based on the prefix of their hash, and they are randomly inserted into their corresponding chain (branch). The protocol does not directly suffer from our proposed attacks, although it might suffer from different problems related to double spending of transactions mined in parallel, which is however common for all DAG-oriented protocols. Authors:
(1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz);
(2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut);
(3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr);
(4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz);
(5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). This paper is available on arxiv under CC BY 4.0 DEED license. Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Background II. Background III. Problem Definition III. Problem Definition IV. DAG-Oriented Solutions IV. DAG-Oriented Solutions V. Game Theoretical Analysis V. Game Theoretical Analysis VI. Simulation Model VI. Simulation Model VII. Evaluation VII. Evaluation VIII. Countermeasures VIII. Countermeasures IX. Discussion and Future Work IX. Discussion and Future Work X. Related Work X. Related Work XI. Conclusion and References XI. Conclusion and References X. RELATED WORK DAG-Based Consensus Protocols The benefits of blockchain protocols come with certain trade-offs when balancing decentralization, scalability, and security. We have already mentioned the bottleneck in Nakamoto’s consensus protocol, and therefore, alternative approaches are emerging, such as DAG-based protocols. Beside DAG-based protocols, also 2nd layer [38], [37], [21] and sharding designs [29], [51], [23], addressing the same problems, had emerged. However, in the current work context, we solely focus on DAG-based designs. Wang et al. [48] performed a detailed systematic overview of DAG-designs. They described six categories containing more than thirty DAG-based blockchain systems classified based on their characteristics and principles. They extend the commonly used classification based on the type of ledgers [47]. GHOST [45], Inclusive Blockchain [26], Conflux [27], Haootia [47], and Byteball [3] represent DAG with the main chain. Hashgraph [24] and Nano [25] represent ledgers with parallel chains. DAG-Based Consensus Protocols DAG-Based Consensus Protocols Nevertheless, out of these categories, DAGs with the main chain are related to our research, such as Inclusive [26], SPECTRE [43], PHANTOM and GHOSTDAG [44]. We refer the reader to Sec. IV for details about these protocols. Performance Analysis of DAGs While many papers deal with the security and performance analysis of mentioned protocols, they consider neither mining strategy nor features of various incentive schemes. Park et al. [35] address the performance of DAG-based blockchains and relate it to the optimization of profit. They show that the average number of parents n can influence the transaction processing time. As a result, they propose a competitive-based transaction process system using a dynamic fee policy. Performance Analysis of DAGs Performance Analysis of DAGs n Birmpas et al. [8] propose a new general framework that captures ledger growth for a large class of DAG-based implementations to demonstrate the structural limits of DAGbased protocols. Even with honest miner behavior, fairness, and efficiency of the ledger can be affected by different connectivity levels. One of the key technical problems of DAG-based protocols is identifying honest blocks. Wang proposes a MaxCord [50], a framework using a different approach for honest block identification problems using graph theory. Based on the definition of the disparity measurement between blocks, they convert the problem into a maximum k-independent set problem. Cao et al. [10] compared the performance of three consensus mechanisms: Bitcoin (PoW), Nxt (PoS), and Tangle (DAGPoW) in terms of parameters such as average time to generate a new block or confirmation delay and failure probability, showing how these mechanisms can affect the state of network resources or network load condition. Sycomore [2] and its extension Sycomore++ [12] is another DAG-oriented consensus protocol that utilizes DAGs to increase Nakamoto consensus throughput. The protocol proposes that the chain responds to the dynamically increased number of transactions and splits them into multiple chains, thus creating DAG structure. When the number of transactions decreases (utilization of blocks is reduced), the branches can be rejoined back into a single chain. Transactions are evenly partitioned based on the prefix of their hash, and they are randomly inserted into their corresponding chain (branch). The protocol does not directly suffer from our proposed attacks, although it might suffer from different problems related to double spending of transactions mined in parallel, which is however common for all DAG-oriented protocols. Authors: (1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz); (2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut); (3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr); (4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz); (5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). Authors: Authors: (1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz); (2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut); (3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr); (4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz); (5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

Comparative Study of DAG Protocols and Their Impact on Blockchain Performance

Table of Links Abstract and I. Introduction II. Background III. Problem Definition IV. DAG-Oriented Solutions V. Game Theoretical Analysis VI. Simulation Model VII. Evaluation VIII. Countermeasures IX. Discussion and Future Work X. Related Work XI. Conclusion and References III. PROBLEM DEFINITION Let there be a PoW blockchain network that uses the Nakamoto consensus and consists of honest and greedy miners, with the greedy miners holding a fraction κ of the total mining power (i.e., adversarial mining power). Then, we denote the network propagation delay in seconds as τ and the block creation time in seconds as λ. We assume that the minimum value of λ is constrained by τ of the blockchain network. It is well-known that Nakamoto-style blockchains generate stale blocks (a.k.a., orphan blocks). As a result, a fraction of the mining power is wasted. The rate at which stale blocks are generated increases when λ is decreased, which is one of the reasons why Bitcoin maintains a high λ of 600s. DAG-Oriented Designs. Many DAG-oriented designs were proposed to allow a decrease of λ while utilizing stale blocks in parallel chains, which should increase the transaction throughput. Although there are some DAG-oriented designs that do not address the problem of increasing transaction throughput (e.g., IoTA [39], Nano [25], Byteball [3]), we focus on the specific group of solutions addressing this problem, such as Inclusive [26], GHOSTDAG, PHANTOM [44], SPECTRE [43], and Prism [6]. We are targeting the RTS strategy, which is a common property of this group of protocols. In the RTS, the miners do not take into account transaction fees of all included transactions; instead, they select transactions of blocks randomly – although not necessarily uniformly at random (e.g., [42]). In this way, these designs aim to eliminate transaction collision within parallel blocks of the DAG structure. Nevertheless, the interpretation of randomness in RTS is not enforced/verified by these designs, and miners are trusted to ignore fees of all (or the majority of [42]) transactions for the common “well-being” of the protocol. Contrary, miners of blockchains such as Bitcoin use a wellknown transaction selection mechanism that maximizes profit by selecting all transactions of the block based on the highest fees – we refer to this strategy as the greedy strategy in the context of considered DAG-based protocols. A. Assumptions We assume a generic DAG-oriented consensus protocol using the RTS strategy (denoted as DAG-PROTOCOL). Then, we assume that the incentive scheme of DAG-PROTOCOL relies on transaction fees (but additionally might also rely on block rewards),[4] and transactions are of the same size.[5] Let us assume that the greedy miners may only choose a different transaction selection strategy to make more profit than honest miners. Then, we assume that DAG-PROTOCOL uses rewarding where the miner of the block A gets rewarded for all unique not-yet-mined transactions in A (while she is not rewarded for transaction duplicates mined before). B. Identified Problems – Incentive Attacks Although the assumptions stated above might seem intuitive, there is no related work studying the impact of greedy miners deviating from the RTS strategy on any of the considered DAG-PROTOCOLs (GHOSTDAG, PHANTOM [44], SPECTRE [43], Inclusive [26], and Prism [6]) and the effect it might have on the throughput of these protocols as well as a fair distribution of earned rewards. Note that we assume GHOSTDAG, PHANTOM, and SPECTRE are utilizing the RTS strategy that was proposed in the Inclusive protocol [43], as recommended by the (partially overlapping) authors of these works – this is further substantiated by the practical implementation of GHOSTDAG/PHANTOM called Kaspa [42], which utilizes a variant of RTS strategy (see Sec. IV) that selects a majority portion of transactions in a block uniformly at random, while a small portion of the block capacity is seized by the transaction selected based on the highest fees. Nevertheless, besides potentially increased transaction collision rate, even such an approach enables more greedy behavior. We make a hypothesis for our incentive attacks: Hypothesis 1. A greedy transaction selection strategy will decrease the relative profit of honest miners as well as transaction throughput in the DAG-PROTOCOL. Note that the greedy transaction selection strategy deviates from the DAG-PROTOCOL and thus is considered adversarial. Authors:
(1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz);
(2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut);
(3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr);
(4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz);
(5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). This paper is available on arxiv under CC BY 4.0 DEED license. Note that block rewards would not change the applicability of our incentive attacks, and the constraints defined in the game theoretic model (see Sec. V-B) would remain met even with them.


Note that this assumption serves only for simplification of the follow-up sections. Transactions of different sizes would require normalizing fees by the sizes of transactions to obtain an equivalent setup (i.e., a fee per Byte). Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Background II. Background III. Problem Definition III. Problem Definition IV. DAG-Oriented Solutions IV. DAG-Oriented Solutions V. Game Theoretical Analysis V. Game Theoretical Analysis VI. Simulation Model VI. Simulation Model VII. Evaluation VII. Evaluation VIII. Countermeasures VIII. Countermeasures IX. Discussion and Future Work IX. Discussion and Future Work X. Related Work X. Related Work XI. Conclusion and References XI. Conclusion and References III. PROBLEM DEFINITION Let there be a PoW blockchain network that uses the Nakamoto consensus and consists of honest and greedy miners, with the greedy miners holding a fraction κ of the total mining power (i.e., adversarial mining power). Then, we denote the network propagation delay in seconds as τ and the block creation time in seconds as λ. We assume that the minimum value of λ is constrained by τ of the blockchain network. It is well-known that Nakamoto-style blockchains generate stale blocks (a.k.a., orphan blocks). As a result, a fraction of the mining power is wasted. The rate at which stale blocks are generated increases when λ is decreased, which is one of the reasons why Bitcoin maintains a high λ of 600s. DAG-Oriented Designs . Many DAG-oriented designs were proposed to allow a decrease of λ while utilizing stale blocks in parallel chains, which should increase the transaction throughput. Although there are some DAG-oriented designs that do not address the problem of increasing transaction throughput (e.g., IoTA [39], Nano [25], Byteball [3]), we focus on the specific group of solutions addressing this problem, such as Inclusive [26], GHOSTDAG, PHANTOM [44], SPECTRE [43], and Prism [6]. We are targeting the RTS strategy, which is a common property of this group of protocols. In the RTS, the miners do not take into account transaction fees of all included transactions; instead, they select transactions of blocks randomly – although not necessarily uniformly at random (e.g., [42]). In this way, these designs aim to eliminate transaction collision within parallel blocks of the DAG structure. Nevertheless, the interpretation of randomness in RTS is not enforced/verified by these designs, and miners are trusted to ignore fees of all (or the majority of [42]) transactions for the common “well-being” of the protocol. Contrary, miners of blockchains such as Bitcoin use a wellknown transaction selection mechanism that maximizes profit by selecting all transactions of the block based on the highest fees – we refer to this strategy as the greedy strategy in the context of considered DAG-based protocols. DAG-Oriented Designs greedy strategy A. Assumptions A. Assumptions A. Assumptions We assume a generic DAG-oriented consensus protocol using the RTS strategy (denoted as DAG-PROTOCOL). Then, we assume that the incentive scheme of DAG-PROTOCOL relies on transaction fees (but additionally might also rely on block rewards),[4] and transactions are of the same size.[5] Let us assume that the greedy miners may only choose a different transaction selection strategy to make more profit than honest miners. Then, we assume that DAG-PROTOCOL uses rewarding where the miner of the block A gets rewarded for all unique not-yet-mined transactions in A (while she is not rewarded for transaction duplicates mined before). A A B. Identified Problems – Incentive Attacks B. Identified Problems – Incentive Attacks B. Identified Problems – Incentive Attacks Although the assumptions stated above might seem intuitive, there is no related work studying the impact of greedy miners deviating from the RTS strategy on any of the considered DAG-PROTOCOLs (GHOSTDAG, PHANTOM [44], SPECTRE [43], Inclusive [26], and Prism [6]) and the effect it might have on the throughput of these protocols as well as a fair distribution of earned rewards. Note that we assume GHOSTDAG, PHANTOM, and SPECTRE are utilizing the RTS strategy that was proposed in the Inclusive protocol [43], as recommended by the (partially overlapping) authors of these works – this is further substantiated by the practical implementation of GHOSTDAG/PHANTOM called Kaspa [42], which utilizes a variant of RTS strategy (see Sec. IV) that selects a majority portion of transactions in a block uniformly at random, while a small portion of the block capacity is seized by the transaction selected based on the highest fees. Nevertheless, besides potentially increased transaction collision rate, even such an approach enables more greedy behavior. We make a hypothesis for our incentive attacks: Hypothesis 1. A greedy transaction selection strategy will decrease the relative profit of honest miners as well as transaction throughput in the DAG-PROTOCOL. Hypothesis 1. A greedy transaction selection strategy will decrease the relative profit of honest miners as well as transaction throughput in the Note that the greedy transaction selection strategy deviates from the DAG-PROTOCOL and thus is considered adversarial. Authors: (1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz); (2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut); (3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr); (4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz); (5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). Authors: Authors: (1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz); (2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut); (3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr); (4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz); (5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv Note that block rewards would not change the applicability of our incentive attacks, and the constraints defined in the game theoretic model (see Sec. V-B) would remain met even with them. Note that this assumption serves only for simplification of the follow-up sections. Transactions of different sizes would require normalizing fees by the sizes of transactions to obtain an equivalent setup (i.e., a fee per Byte). Note that block rewards would not change the applicability of our incentive attacks, and the constraints defined in the game theoretic model (see Sec. V-B) would remain met even with them. Note that block rewards would not change the applicability of our incentive attacks, and the constraints defined in the game theoretic model (see Sec. V-B) would remain met even with them. Note that this assumption serves only for simplification of the follow-up sections. Transactions of different sizes would require normalizing fees by the sizes of transactions to obtain an equivalent setup (i.e., a fee per Byte). Note that this assumption serves only for simplification of the follow-up sections. Transactions of different sizes would require normalizing fees by the sizes of transactions to obtain an equivalent setup (i.e., a fee per Byte).

Identifying Incentive Attacks in DAG-Oriented Blockchain Protocols

“If I have seen further, it is by standing on the shoulders of giants." This old metaphor, attributed to Bernard of Chartres, can describe the current situation of all inventions. We’re in this technology stage thanks to the advances made by our predecessors, and Obyte (all cryptocurrencies, indeed) is no different. Without computers, the Internet, specialized software, and cryptography, the whole crypto world wouldn’t be here. If we look more closely into the software and cryptography realms, numerous milestones had to be achieved before the appearance of decentralized money. Then, afterward, some others would come to make the Obyte ecosystem possible. The gives them credit at the end, but do you know who they are and what they really did? Let’s check a bit of history and interesting inventions. We’re in debt to experts from all parts of the world and their previous creations. Obyte whitepaper Satoshi Nakamoto Of course, this is the more obvious one. Bitcoin was the first cryptocurrency ever, and someone named Satoshi Nakamoto created it. We know little about him, though. He reportedly was born on April 5, 1975, he’s known as a brilliant programmer and a recognized —online activists behind decentralized tools. Beyond this, there are more questions than answers about his persona. Or their personas. We don’t even know if that’s his real name because he (or they?) chose the path of complete privacy. cypherpunk , on the other hand, is the first and most adopted cryptocurrency so far. This piece of software operates on a peer-to-peer (P2P) network, enabling direct transfers without intermediaries —besides the miners. Transactions are verified by network nodes through cryptography, and recorded in a public ledger called the blockchain. It’s not fully decentralized and has , but it’s the start of the cryptocurrency world. Bitcoin its own set of issues However, we don’t have miners or “validators”, as we don’t have a “blockchain” but a Directed Acyclic Graph (DAG) structure. This way, all transactions sent to the DAG are truly censorship-resistant and not dependable on third parties. We took a lot of the Bitcoin original system in Obyte, including the P2P transparent crypto-network and the goal to eliminate middlemen. Sergio Demian Lerner He describes himself this way: “In short, my name is Sergio Demian Lerner. I’m a Cryptofan, Independent Security Researcher, and Bitcoin specialist since 2011.” It could be an understatement, though. Lerner is an Argentinian programmer who has created and participated in a lot of cryptocurrency projects, and more importantly for us, he’s the original designer of DAG-like coins. He even mentions Byteball (now Obyte) in his . personal story He’s helped to fix over 8 vulnerabilities in Bitcoin and has been involved in projects like Copay (now BitPay), Bitshares, Counterparty, Ethereum, and Monero. Interestingly enough, the Obyte wallet UI is based on Copay. Lerner has collaborated in open-source crypto projects for years (and for free), but he’s not exactly a cypherpunk. Among others, he co-founded the blockchain auditing company CoinFabrik in 2014, and the Bitcoin-based sidechain ecosystem Rootstock (now RSK / IOV Labs) in 2015. Additionally, he’s a pioneer of atomic swaps, also mentioned in the Obyte whitepaper. considered As for the DAG, but create the chain themselves**,** with every transaction. We took this idea to create Obyte, and added Order Providers (OPs) as mere waypoints to order transactions, without them being powerful middlemen as miners or centralized companies. Lerner as “a cryptocurrency without blocks,” where every user would be a “miner” —in the sense that they wouldn’t need miners, described it Serguei Popov While Lerner first described DAGs to create cryptocurrencies, he never coded the project himself. However, other developers were interested in the idea and started to propose (and create) new ecosystems around it. Serguei Popov and the IOTA team were likely the first ones back in October 2015. Popov is a Russian-Brazilian mathematician in charge of the conceptual side of the IOTA crypto project. After receiving his Diploma and Ph.D. from the Department of Mathematics and Mechanics of Moscow State University in 1997, he left for Brazil to start an academic career as a professor. interested in cryptocurrencies by 2013, first in Bitcoin and later in the altcoin Nxt. By sharing his own calculations about that network on Bitcointalk, he got to meet the Nxt founder, Sergey Ivancheglo. He became Then, in , Sergey and David Sonstebo invited him to contribute to the theoretical side of IOTA —and that's how the was born, inspired by the previous work by Lerner. Users validate transactions by confirming two previous ones, promoting scalability and feeless microtransactions. However, unlike Obyte, their network is still controlled , and not by the users. late 2015 Tangle whitepaper IOTA is a cryptocurrency designed for the Internet of Things (IoT). It utilizes the Tangle, a DAG network, just like Obyte. by their foundation Tom Holden Some months before the release of Obyte (Byteball, back then), a Bitcointalk member known as Tom Holden proposed another DAG-like system to create an improved cryptocurrency. He named it Transaction Directed Acyclic Graph (TDAG). It utilizes a structured DAG that must form a bounded lattice, ensuring a unique root node and childless node. Each transaction references previous ones, like in every DAG. Besides, it offers incentives such as transaction fees and fee burning. We don’t know who Tom Holden really is, or what he does. However, is connected to the DAG-like ecosystems and probably his early proposal urged us to think about and fix some potential vulnerabilities that this type of system may bring. Tony Chryumov (Tonych), the Obyte founder, participated in that thread and pointed out a potential attack vector where an adversary could construct a shadow DAG, including double-spends, and spend more on fees in the shadow DAG than in the legitimate DAG. The attacker could then publish the shadow DAG, leading users to switch to it as it appears more profitable due to higher fees spent. Obyte solved this issue with the creation of witnesses (Order Providers). Stuart Haber and W. Scott Stornetta They also appear in the Bitcoin whitepaper as the proponents of Linked Timestamping, a cryptographic method that involves associating a timestamp with a piece of data or information, establishing a chronological order of events (or transactions). This process creates a chain or link of timestamps, where each timestamp is linked to the previous one, forming a secure and tamper-evident sequence registered in a difficult-to-alter and widely observed platform, such as a printed newspaper or a public ledger. Both Americans, Haber is a cryptographer and computer scientist, while Stornetta is a physicist —like was. They met while working for the communication company Bellcore (now Iconectiv), and co-authored the paper " ” in 1991. Currently, is an advisor member of the cryptocurrency Kadena and Yugen Partners, a private equity firm for crypto projects. Meanwhile, is a partner and Chief Scientist at the latter one. In other words, they are the creators of the first “blockchain,” so to speak. Tim May How to Time-Stamp a Digital Document Haber Stornetta https://www.youtube.com/watch?v=WWVoPBkPd6g&embedable=true The order in a DAG is different than in a blockchain, . They serve the same function as the newspaper in our first example: they’re well-known and trusted to post serially, which is equivalent to not publishing two versions of the same issue of the newspaper. Light clients in Obyte rely on witnesses to prove that a transaction exists. By default, light clients select Order Providers as their light client witnesses. but Obyte took the idea of publishing transactions in a widely observed system, such as a newspaper, and created the witnesses Bonus: 1984 Also mentioned in our whitepaper, " " by George Orwell, published in 1949, is a dystopian novel that explores a totalitarian society ruled by an oppressive government led by the Party and its enigmatic leader, Big Brother. Set in an alternative year, 1984, the story follows Winston Smith, a low-ranking member of the Party who becomes disillusioned with the oppressive regime. 1984 The novel delves into themes of censorship, surveillance, and the manipulation of truth, portraying a bleak future where individualism is suppressed, history is rewritten, and the concept of reality is distorted. This is a world where nobody would like to live, and sadly, it’s also not that far from what some modern countries have become, to varying degrees. , , , and of everyone’s money are now realities everywhere. That’s why activists are dedicated to creating freedom tools, and that is (or that should be) the raison d'être of cryptocurrencies. Obyte was created as a freedom tool as well, even more decentralized than its predecessors. We’re working hard to create a free world for everyone, everywhere. Ready to join us? Mass surveillance totalitarian regimes democratic censorship unjustified control like cypherpunks Featured Vector Image by storyset / Freepik

Obyte Precursors: Who Helped to Create Our Decentralized Ecosystem?

Obyte Precursors: কে আমাদের বিকেন্দ্রীভূত ইকোসিস্টেম তৈরি করতে সাহায্য করেছে?

Obyte-Vorläufer: Wer hat zur Schaffung unseres dezentralen Ökosystems beigetragen?

Precursores de Obyte: ¿Quién ayudó a crear nuestro ecosistema descentralizado?

Précurseurs d'Obyte : qui a aidé à créer notre écosystème décentralisé ?

ओबाइट प्रीकर्सर्स: हमारे विकेंद्रीकृत पारिस्थितिकी तंत्र को बनाने में किसने मदद की?

オバイトの先駆者: 私たちの分散型エコシステムの構築に貢献したのは誰ですか?

Obyte Precursors: 누가 우리의 분산형 생태계를 만드는 데 도움을 주었나요?

Precursores Obyte: Quem ajudou a criar nosso ecossistema descentralizado?

Предшественники Obyte: кто помог создать нашу децентрализованную экосистему?

Obyte Öncüleri: Merkezi Olmayan Ekosistemimizin Oluşturulmasına Kim Yardımcı Oldu?

Tiền thân của Obyte: Ai đã giúp tạo ra hệ sinh thái phi tập trung của chúng tôi?

Obyte 前身：谁帮助创建了我们的去中心化生态系统？

Both of them are computer protocols designed to carry on decentralized functions, mostly with the help of smart contracts and . Those functions may include financial transactions, supply chain management, identity verification, customized token creation, and more, all without the need for a central authority —that’s why they’re “decentralized.” But Ethereum and Obyte also have important differences. cryptocurrencies Depending on what you’re looking for or even your programming level (that could be zero), one or the other platform would be the most convenient for your needs. So, you can check ahead what are their main similarities and differences and how to take advantage of them. Let’s go! Open Crypto Projects This one is a similarity. Ethereum and Obyte are open-source and free projects available for everyone (with programming knowledge) to check and edit. If you don’t have programming abilities, you still can freely use their wallets and apps to the extent of the knowledge of any average Internet user. , gathered via GitHub. However, both Ethereum and Obyte have their own non-profit foundations in charge of fostering the development and adoption of these platforms. use the native assets of these platforms (GBYTE and ETH) to fund themselves and pay for some expenses —main developers, marketing efforts, bug bounty programs, grants, etc. In the background, both protocols are mostly developed and maintained by a lot of unpaid volunteers from all parts of the world These entities Their teams aren’t anonymous either, and none of the platforms are very new. Both protocols have well-known founders and developers. Ethereum was released in 2015 by a group of developers led by Vitalik Buterin, while Obyte was released in 2016 (as Byteball) by Anton Churyumov and his team. Dapps and Common Features Regarding what they can do, one of the key similarities is their ability to facilitate decentralized applications (DApps) and smart contracts. Both Ethereum and Obyte offer environments for developers to create and deploy these self-executing contracts, enabling a wide range of use cases. . and marketplaces are also possible on these platforms. On the other hand, organizations and companies can use the ledgers for supply chain management, identity verification, donations, and more. They include decentralized finance (DeFi), which is a whole industry made of payments, loans, savings, rewards, and more Non-fungible token (NFT) creation Another common feature is their support for tokenization. Ethereum, mainly through its ERC-20 and ERC-721 standards, and Obyte, with its built-in tokenization capabilities, enable the creation of customized digital assets and tokens. These tokens can represent anything from digital money to real-world assets like real estate and securities, providing a versatile framework for digitizing properties and conducting token-based transactions. Smart Contracts and Tokens Now, let’s look into the differences. While both platforms offer smart contracts and tokens, they do it very differently from each other. For starters, they operate with different programming languages: Ethereum with Solidity, and Obyte with . The first case (Solidity) has been known for its complexity and a steep learning curve for developers —since it’s a completely new programming language specifically designed for Ethereum. a wide array of undiscovered bugs and attacks in contracts written by not-so-skilled developers. Oscript This may bring –in the form of (AAs). This language is more transparent, making it easy to understand what is going on in the code and making it hard to make difficult-to-track errors. This way, numerous types of AAs providing various services (e.g., exchanges, stablecoins, prediction markets, etc.) can be created easily and safely. Oscript is also new, but it was designed for the opposite: to make it easier to create Dapps and contracts Autonomous Agents On the other hand, beyond AAs, smart contracts in Obyte are written in JSON data that can be shown in a human-readable way, which the Obyte wallet does. So, the user can quickly inspect the contract’s rules before interacting with it. The composition of a few common types of smart contracts is also available directly to users, just by filling out forms, with no coding required. That's not the case on Ethereum, where you would need coding knowledge to read and write them. Custom tokens Token creation is also different. In Obyte, all assets have the same status and obey the same rules as the native token GBYTE (beyond customized features like amount, decimals, privacy, fungibility, or name). This means that developers don’t have to reimplement basic transfer functions over and over again for every token, and there’s no way these functions can go wrong. On the other hand, on Ethereum, internal tokens (ERC-20 standard, mainly) don’t work as the native asset ETH. Besides, these tokens are  smart contracts themselves, and could be vulnerable to bugs and attacks. To send these tokens to other smart contracts, users need to give access to the smart contract to pull tokens from their wallets, where they’d be partially out of control. They need to be configured in detail, and users could if they send tokens to a contract that’s not equipped to receive them. lose money As for the interfaces, in order to send tokens to a smart contract users have to approve that smart contract to spend their tokens. This extra step is not intuitive at all. Meanwhile, in Obyte, users just send the tokens without extra steps. The creation of smart contracts and custom tokens on Ethereum often requires programming knowledge or expensive external middlemen (like or ). with the help of a chatbot in the wallet or the user-friendly , whose only fees are 0.005 GBYTEs (less than $1). Smart contracts are readable, and anyone can offer them through the wallet as well. Bitbond Token Generator In Obyte, anyone could create their own tokens without complex steps or high additional fees Asset Registry Fees and Decentralization Obyte tends to be cheaper, faster, and more decentralized than Ethereum. This blockchain uses Proof-of-Stake (PoS) to validate transactions and issue new coins. , so-called validators are chosen to create new blocks based on the number of native coins they "stake" or hold as collateral. This eliminates the need for the high amount of energy that previous Proof-of-Work (PoW) coins like Bitcoin require, but it could sacrifice decentralization –even if that concept isn’t in PoW networks either. In PoS networks fully achieved Validators with larger stakes wield more power in the network, potentially leading to centralization as those with substantial resources can dominate decision-making. Just like Ethereum, Obyte doesn’t need a lot of energy. Indeed, Obyte isn’t a “blockchain” but a distributed network built with the structure of a Directed Acyclic Graph (DAG). The graph is constructed only by users with each transaction they add. The new transactions link to the previous ones, and they’re registered forever this way. No one can censor transactions. But it doesn’t have PoS-like validators either, allowing a higher level of decentralization. To prevent double-spending, the Obyte DAG has who help establish a full order. They’re well-respected individuals or companies that create transactions like everyone else, but these transactions serve as waypoints for ordering all other transactions. They don’t have a lot of power, though, unlike miners or validators. Users remain in full control of their assets throughout the transaction process without having to rely on a select group. Decentralization is much stronger in this system. "Order Providers” Currently (September 2023), Ethereum has an average transaction fee of around $3 —it’s reached even $196 in the past, though. Meanwhile, transaction fees in Obyte are now around $0.0000083. The difference in transaction fees is also remarkable. Obyte Exclusive Features Obyte stands out in the crypto space by offering a range of exclusive features that contribute to its unique value proposition. Besides traditional Dapps, DeFi platforms, liquidity mining opportunities, and other common features with Ethereum, we can also count some interesting functions only available in this ecosystem as user-friendly apps. They’re human-readable smart contracts that allow users to send funds with . This means that transactions can be contingent on specific events or triggers, unlocking a wide array of use cases. For instance, you could send a payment that is only released to the recipient once they send another payment to you or an event is posted on the DAG, creating a trustless and automated system for contractual agreements. Conditional Payments: predefined conditions Obyte enables the creation of tokens with bonding curves, a mathematical system that allows token prices to be dynamically determined based on supply and demand. These curves facilitate automated price adjustments as more tokens are bought or sold, which can be useful for projects conducting token sales or managing liquidity. The , , and use this system. Tokens with Bonding Curves: OSWAP Token Bonded Stablecoins Prophet prediction markets This unique feature allows for dispute resolution in cases where one of the parties must release the funds to the other from a smart contract —for example, after the completion of a task or a purchase. Arbiters from the can step in to mediate and make decisions, adding a layer of security and trust to complex transactions and agreements on the platform. Contracts with Arbitration: ArbStore This function enables users to send cryptocurrency via simple text messages, mail, chats, . It’s a very user-friendly approach that lowers barriers to entry and makes cryptocurrency transactions more accessible to a broader audience, potentially driving adoption and mainstream use. Textcoins: or paper platform facilitates cascading donations for open-source projects, where recipients on GitHub can set up automated donations to multiple recipients in different proportions. This way, all interconnected projects can help each other while receiving donations from others. Cascading Donations: Obyte's Kivach These automated conversational agents are integrated into the Obyte wallet, enabling users to interact with numerous services and perform various actions through simple instructions and steps. Chatbots enhance the user experience by simplifying complex tasks and providing real-time assistance to users. Chatbots: These exclusive features collectively make Obyte a compelling platform for developers and users alike, offering a wide range of capabilities beyond simple transactions. Ethereum also has numerous use cases, depending on developers and users worldwide. Despite this, we can say that Obyte offers a more decentralized, open, and inexpensive ecosystem with unique features available for everyone.

Ethereum vs. Obyte: A Comparison — Or How to Choose the Best One for You

ইথেরিয়াম বনাম ওবাইট: একটি তুলনা —অথবা আপনার জন্য সেরাটি কীভাবে চয়ন করবেন

Ethereum vs. Obyte: Ein Vergleich – oder wie Sie das beste für Sie auswählen

Ethereum vs. Obyte: una comparación o cómo elegir el mejor para usted

Ethereum vs Obyte : une comparaison – ou comment choisir celui qui vous convient le mieux

एथेरियम बनाम ओबाइट: एक तुलना-या अपने लिए सर्वश्रेष्ठ कैसे चुनें

イーサリアムとオバイト: 比較 — または自分にとって最適なものを選択する方法

Ethereum 대 Obyte: 비교 – 또는 귀하에게 가장 적합한 것을 선택하는 방법

Ethereum vs. Obyte: uma comparação - ou como escolher o melhor para você

Ethereum против Obyte: сравнение — или как выбрать лучший для себя

Ethereum ve Obyte: Bir Karşılaştırma — Veya Sizin İçin En İyisini Nasıl Seçebilirsiniz?

Ethereum và Obyte: So sánh —Hoặc Cách chọn cái tốt nhất cho bạn

以太坊与 Obyte：比较——或者如何选择最适合您的一个

The crypto world is still very new, compared to more traditional assets. “ ” and “Cryptocurrencies” are now viral terms, but that’s not enough. Real adoption is still a challenge, especially for specific brands inside this wide industry. That’s exactly why numerous developers and projects often give away some share of their tokens. Bitcoin Mostly, these gifts help to promote the project and increase real-world adoption and use cases. It’s a win-win for brands and users: . The main ways to distribute free crypto tokens to anyone willing to claim them are airdrops or giveaways and faucets. they earn some money they didn’t have before, and the platform gains in awareness There’s not a lot to do by the user in either case. The team behind the platform decides the airdrop rules, so, maybe you should share a post about them, click a button on their webpage, or have owned another coin before a certain date (like Ether or Bitcoin). As for the faucets, they’re websites or apps in which you can answer surveys or solve captchas in exchange for a few coins. Free Bitcoins website, first faucet in existence. Retrieved from the Internet Archive. We do have some free cryptocurrency in as well. And we have additional methods. Let’s find out how to earn some free tokens! Obyte How to get some free GBYTEs Obyte (previously Byteball) never had an Initial Coin Offering (ICO), crypto mining, staking, or similar method. Instead, most GBYTEs have been distributed via airdrops and rewards. Our first BTC airdrops until 2017 gave away over 645,341 GBYTEs to numerous early adopters. If someone owned a certain amount of Bitcoin (BTC) at that moment, they were able to receive some share of GBYTEs. This distribution method is now discontinued, but we still offer several ways to earn free coins. ID Attestations Anyone can create their own /verified data on Obyte. We call this function “attestation”, and it could also work to access several applications in the Obyte ecosystem. You can verify your real name, your email, your GitHub account, your status as an accredited investor, and more. This is done through chatbots in the Obyte wallet (Chat tab -Bot Store). , depending on the attestation type. self-sovereign identity For attesting your personal data, you can also earn between $8 and $79 in GBYTEs Telegram Quiz A is available for everyone to use and earn some rewards —and gain some knowledge about Obyte. (e.g., How large is the transaction fee in Obyte?) to the bot. Once you answer correctly enough of them, you’ll earn at least $0.02 in GBYTEs. The reward is paid . Telegram bot You only need to answer multiple choice questions about our platform as a textcoin Trading rewards We have a for GBYTEs traders on the crypto exchange Bittrex —outside the United States. Up to 100 GBYTEs is distributed weekly to those who made profits by taking long positions in the GBYTE/BTC pair. The reward is equal to the profit, i.e. it doubles the profit. rewards program If your position is still open at the end of the week, and it is profitable, we double your unrealized profit too. (if you bought more than you sold or withdrew). Your share in the total 100 GBYTE reward pool is equal to your share in the total net buys during the week. Additionally, other 100 GBYTEs are also given away weekly for GBYTE net buys Investment of time: grants and tasks Offer your own time in exchange for GBYTEs is an option too. It’s not completely free this way, since your own time and efforts are valuable, but it’s free from monetary investment (unlike , for example). , that help to improve the Obyte ecosystem. You can check and send your proposal to our team. Liquidity Mining We have a Grants Program for projects, especially non-profit/open-source the requirements Likewise, we have a share of GBYTEs for developers and other professionals that are helping to improve and promote the Obyte ecosystem. For example, before the release of Autonomous Agents (AA), developers participated to build use cases for it. The total prize pool was $38,000 in GBYTEs. So, you can always share your best ideas with us! in a contest End of the byte!

Educational Byte: How to Earn Some Free Cryptocurrency on Obyte

Byte educativo: cómo ganar criptomonedas gratis en Obyte

Octet éducatif : comment gagner de la crypto-monnaie gratuite sur Obyte

शैक्षिक बाइट: ओबाइट पर कुछ मुफ्त क्रिप्टोक्यूरेंसी कैसे अर्जित करें

Educational Byte: Obyte で無料の暗号通貨を獲得する方法

Byte educacional: como ganhar algumas criptomoedas grátis no Obyte

Byte giáo dục: Cách kiếm tiền điện tử miễn phí trên Obyte

教育字节：如何在 Obyte 上赚取一些免费的加密货币

While it is easy to visualize a smartphone, a smart TV, or even a smart car — the quintessential 23rd Century smart city might largely elicit confusion from the public. In theory, the word “smart” - with regards to electronic devices or data- means the appliance is programmed to be capable of some independent action. The rise of smart cities will be propelled by emerging trends such as machine learning, blockchain, and IoT. This in mind, a smart city would imply a particular jurisdiction or area to process, address, utilize, and make decisions on the millions of data inputs the thousands of smart sensors in that area take in. For example — a smart state-issued parking app that helps drivers find available parking spaces without scavenging street after street for those few meters of space. Potentially, the car may itself be equipped to handle digital payments, which prevents the need to carry change for filling up that parking meter. For other uses involving traffic, perhaps the government utilize a sensor-dependent traffic system which analyses the flow of on-road vehicles and accurately determines which blocks require more green lights and which don’t. While these examples are more of a smart transit system than a smart city, it is important to note that a city is a set of various process running in unison. Simply put, a city is made by several governances, administrative, educatory, social, and technical processes. Putting the “smart” in a city, in reality, implies smart transit systems, smart governance systems, smart research systems, and so forth, to run with their immutable databases that connect to each other for sharing information to make decisions. In short, each facet of a smart city will have an underlying unique, immutable database. Efficiency and energy conservation will form another factor for the city of the future. Minor things, such as improving observations or planning or electricity grids based on usage, or dimming street lights when the sensors do not sense any cars (while keeping the footpaths well-lit), all add up to the smart city ethos. Hence, we may divide a 23rd Century city into three distinct categories: One that can accurately connect the local legislation with citizens to ensure e-participation and collective intelligence while making decisions. One that efficiently makes use of existing physical infrastructure via emerging technologies and data analytics and cultivates a robust economic, cultural, and social environment. One that readily learns, adapts, and innovates to changing circumstances by improving the intelligence of the city. Several other features can be pointed out in this regard. Smart tech can evaluate and monitor environmental changes. Smart tech can improve sanitary functions by Internet-connected garbage trucks and IoT-enabled waste management systems. Smart sensors can be critical components of an early warning system before droughts, floods, landslides or hurricanes. The list goes on and on. If it weren’t immediately apparent to you yet, such a futuristic system requires a tremendous data processing capability on the back-end. Apart from that, an immutable database needs to store all this information to make it readily available when needed. SO — is using a blockchain the solution here? Just like any other problem which attaches this buzzword to itself? The answer is an unenquivocal no. Just like any technology, Blockchain has some uses and some non-uses. For example, you could in theory make Rick’s Butter Robot that senses you on the table and fetches a knife, a stick of butter, a slice of bread, and puts it on for you. Or you could just do it yourself. Similarly, a blockchain of this size, processing such a significant amount of data could require a complex set of crypto-economic laws governing it, and an even broader set of participants maintaining it. Or, we could just use a DAG. A DAG? While I explained in simple terms what the smart-city would do, i.e. create a city-wide database running thousands of other customized databases (side-chains), a may be used for where the blockchain’s capability is limited. DAG architecture So WTF is DAG? In crypto-terms, Bitcoin is considered the . blockchain 1.0 It did the most basic stuff that a blockchain can do, i.e. validate and confirm transactions while noting it all down on a huge public ledger available for viewing by the world. Then came Vitalik Buterin’s brainchild ( along with 19 other developers ), the open-source, decentralized ledger platform Ethereum. Ethereum was built as a platform that allows applications to run precisely as programmed, with Buterin himself comparing the platform to an Android/iOS operating system that can run thousands of unrelated applications on it. This was regarded as . blockchain 2.0 And now, in the year 2018, the rise of Iota led people to consider a Directed Cyclic Graph ( ) system as DAG blockchain 3.0. But what makes this particularly impressive is the DAG is not a blockchain at all — in a sense — there are no blocks in this system. To Expand - irected = the connections between the nodes (edges) have a direction. D cyclic = “non-circular” = moving from node to node by following the edges, A you will never encounter the same node for the second time. raph = structure consisting of nodes, that are connected to each other with edges. G The figure below shows a basic DAG structure : DAG is best applied to problems related to data processing, scheduling, finding the best route in navigation, and data compression. i.e DAG is for building a smart city. BEST suited For whatever reason, the term and technology remains , but from the various forums and sub-reddits I explore, I see rising interest from tech circles. relatively unknown Companies like NANO, IOTA, Byteball and Cybervein operate on this type of an architecture. Cyber-what? While searching for tokens on OKEx — I came across the Cybervein project, which on closer inspection seemed quite like the DAG powerhouse. While NANO impresses Reddit with instantaneous, zero-fee payments and IOTA continues to seduce tech circles with getting IoT-based devices on the blockchain, Cybervein comes closest to building a smart city if my earlier mentioned points are considered. The project aims to “ ” by creating a public network of immutable databases that trades, stores, and monetizes the exchange of information. interconnect the data that runs the world From their white paper— The Cybervein ledger is fractally built as a network of independent, yet interconnected Smart Contracts. Contracts are designed as private ledgers, immune to irrelevant network congestion, yet able to easily communicate and exchange value and information. Much like the internet. The smart city of the future requires this kind of a setup/platform to adequately function in its purest sense. The underlying architecture has to remain block-less in nature, and the transactions need to run directly into the DAG networks. Cities can’t wait for network participants to confirm transactions or validate blocks. While I can’t fathom how the future would look. I believe DAG projects like NANO and Cybervein are closely working towards that regard. Zero blocks at a time.

The 23rd Century: Enter the Smart City

Disclosure: This article is sponsored by Syscoin to sustain my blockchain innovation series. I'm not part of Syscoin or hold/receive any Syscoin tokens. This article is part of my blockchain innovation series where I try to spot interesting technology that might impact the further development of blockchain. Today’s innovation talks about a directed acyclic graph (DAG) technology and how gave a twist to this concept with their Z-DAG implementation. Syscoin What is DAG technology? What is Z-DAG? How is Z-DAG different from a regular DAG? What is zero-confirmation in relation to DAG Technology? Techniques Syscoin Uses for Optimizing Transaction Throughput DAG: A Buzz or Breakthrough? If we simplify how blockchain works, we can compare it with a staircase. Each block you add is a new level on top of your staircase. So, your staircase grows vertically in a single direction. Staircase levels are stacked one at the time. This guarantees that the same transactions are recorded across all nodes in the network. In case a node decides to propose a malicious block or malicious transactions, your staircase would violate the “protocol” rules defined for building staircases. On the other side, a DAG can be compared with a tree which grows in several separate branches. Transactions are processed in a network of interlocking branches that grow outwards in multiple directions. The validation in a DAG is also quite different from a standard blockchain. Each newly added transaction to a branch is responsible for validating two previous transactions (depends on the protocol definition). If the transaction does not follow this guideline, it is impossible to be valid itself. It might sound like a weak requirement to only validate the two previous transactions. However, by validating the two previous transactions you are actually validating a whole branch of transactions connected to this last transaction. Source image: A simple DAG by Vasa Due to this division in branches, a DAG is able to confirm transactions much faster reaching very high speeds. I’m not gonna mention exact numbers as a lot of projects claim to have reached very high transaction throughput (TPS). But one thing is for sure, a DAG allows mostly for a higher TPS than regular blockchain technology. In short, a DAG is a very promising technology that allows for a higher TPS to be reached. It has an interesting structure similar to a tree where every transaction has to verify two prior transactions. In case you want to learn more about DAG technology, fellow writer Vasa wrote an amazing post going deeper into the DAG variations and its properties . What is Z-DAG Technology? Now we know what a DAG is, let’s explore what kind of beast Syscoin has built, naming it Z-DAG. According to Whiteblock CEO Zak Cole, “The Z-DAG protocol is extremely innovative and presents a practical solution for many of the performance issues that are currently bottlenecking the continued scalability of blockchain systems.” Let’s find out what is true about this statement! Diving into Z-DAG Technicals Zero-Confirmation Directed Acyclic Graph (Z-DAG) is a probabilistic transaction scheme that allows for one to separate micro/macro transactions with different security domain tradeoffs in exchange for convenience. Whereas Bitcoin applies PoW scheme on top of every micro or macro transaction, Z-DAG allows an interactive protocol for merchants to decide. Every merchant can accept or decline a Z-DAG transaction based on their preference. Every Z-DAG transaction that has entered the mempool and has some type of probabilities that it will get mined in the future since balances are tracked in real-time and not upon PoW. Upon PoW, however, the state is removed and reproduced based on the block. Because balances are updated in real-time based on transactions in mempool, it is a probabilistic model so the ultimate truth will be what the miners put into the block and what the block of transactions that has Proof of Work on it has in terms of which transactions get mined. Once miners mine a block, the state is replayed based on the state of the previous block. Thus, the probability model around Z-DAG settlement is the likelihood that transactions in the mempool and their balances accurately reflect the truth once miners create and forward blocks to the network. The balances have a high probability of being the same as when they first entered the mempool and settled via ZDAG. This means PoW is ultimately the partition tolerance in the system and the idea is that the view of the network and view of the miner is essentially the same after X seconds where X can be a reasonable amount of time before a transaction is propagated across the network. For now, they have chosen for 10 seconds for the reference client but it can come down as networks are exponentially increasing in efficiency and this can organically be tending towards 0. Source: Syscoin website — report Whiteblock How is Z-DAG different from a regular DAG? Regular DAG protocols do not rely on Proof-of-Work. These protocols include uncles or historical information to keep the graph from dissolving. There is typically no longest-chain-rule with DAGs as it is based on the probability that transactions are ordered based on the historical information provided. However, that comes with some problems. There is little to no partition tolerance which is why there is sometimes central or authoritative models to ensure the DAG doesn’t steer off course (referring to IOTA). With Z-DAG, the partition tolerance is around every block. For every block, the balances are set based on validating each transaction in a block. Therefore, the DAG cannot dissolve as it is only based on what happens within a block. This serves the purpose for a micro-transaction layer 0 solution on top of Proof-of-Work, ultimately settling transactions just like Bitcoin. What is zero-confirmation in relation to DAG Technology? “Z-DAG (Zero-Confirmation Directed Acyclic Graph) is an instant settlement protocol that is used as a complementary system to proof-of-work (PoW) in the confirmation of Syscoin service transactions. In essence, a Z-DAG is simply a directed acyclic graph (DAG) where validating nodes verify the sequential ordering of transactions that are received in their memory pools.” — Syscoin Whitepaper p.1 So, how does this tie back to a DAG? A DAG is a natural construction of transactions with dependencies on balances for dependability. In Bitcoin this dependence is affected after a block, in Syscoin it is affected upon mempool inclusion on every node. It is important to note that Satoshi wrote about a snack machine example where about 3 seconds is needed to detect a double spend. In the Syscoin implementation, they increased this time slot to 10 seconds but the real-time balances are adjusted and one can spend in a chain of transactions based on their balances, creating a natural DAG that is resolved every block. In Syscoin v3, they enforced the order of the DAG by doing topology sort and circuit detections. However, in Syscoin v3, this is not really needed because balances are strictly enforced and clients will not allow invalid transactions to be created in a block that would overflow a balance. Techniques Syscoin Uses for Optimizing Transaction Throughput Let’s take a look at some technical implementations Syscoin has implemented to improve the transaction speed of the overall network. 1. Parallel Signature Verification First of all, whenever a node receives a newly broadcasted transaction, it will relay the transaction to other nodes before validating it. This means that also potentially invalid transactions are broadcasted to the rest of the network. However, this approach allows for more transactions to be validated quicker. A couple of invalid transactions have minimal impact on the overall throughput of the network. This multithreaded approach greatly reduces the time it takes for signatures to be verified. Users choose the time they want to wait and as they wait longer and check the status of their transactions, it is more likely they will detect and not complete the transaction with the buyer in a point of sale application. How to Prevent for Double Spends? Syscoin recommends that 10 seconds is a good amount of time to wait for a transaction to arrive at your node before checking if it's valid. Of course, it's up to the merchant as it’s an interactive protocol. Also, balances are tracked throughout the system to detect two spends that overflow the balance. If this occurs, the sender will be flagged and the receiver will be able to see something went wrong. 2. Flagging Invalid Signatures Syscoin has a protocol in place that will flag a signature as invalid whenever the signature validation check fails in the multithreaded verification process. This flag causes the network to switch back to a single threaded mode in order for other nodes to not waste valuable time and resources on validating an invalid transaction. 3. Sub-linearly Scaling Transaction Throughput Syscoin’s whitepaper explains that a master node can scale to 700–1000 transactions per second (TPS) on average. This number is calculated with latency effects taken into account. However, when 100 of these master nodes are active, the whitepaper talks about a possible TPS of 70k. I questioned them about this statement to find out how this works. Jag Sidhu, the Lead Core Developer and co-founder, explained to me how this scaling works. “It would be a sub-linear increase in efficiency as more nodes enter and an exponential decrease in the effect of latent nodes on the overall functioning of ZDAG on the network. As more paths open up, latent nodes will trail messages where with fewer nodes, higher risk of depending on a latent node for information. Competitors of Syscoin Any DAG project is considered to be a competitor for Syscoin. Let's take a look at the competition. Nano Nano is also able to reach very high transaction speed as they leverage DAG technology. Nano has developed a new piece of technology called block-lattice that allows them to leverage DAG technology but still work like a traditional blockchain. Nano works with nodes that all act as an individual wallet or chain. Only the node owner can make changes to these individual chains which means they can be updated asynchronously. Fast transaction speed by block-lattice Zero transaction fees Byteball Byteball is one of the older projects in the blockchain space. Unlike Nano, transactions are not free on the Byteball chain. However, Byteball offers the feature of having fully private and untraceable transactions. Transaction verification in 30 seconds 51% attack impossible due to validator system to avoid double spends Private transactions IOTA IOTA is also one of the first DAG projects, or more know as Tangle. A new transaction can be added to the network if you first verify the two previous transactions (actually building the tangle). This means that they offer instant transactions which are zero fee. The main idea for IOTA is to build a DLT infrastructure for machine to machine payments, enabling economy 4.0 where smart machines communicate with each other and create a whole economy by itself. IOTA allows for micro transactions and can handle a high throughput. Zero fee transactions Developed for IOT (machine to machine) Enables micro transactions Hedera Hashgraph Hedera Hashgraph might be an odd one in the list as it is a patented technology. You can buy licenses to use the software. Hedera also uses DAG technology and gained attention with their gossip about gossip protocol. As this is too complex to explain for this article, you can find a . podcast here Drawbacks of Syscoin In general, many DAG projects have proven that they can handle very high transaction amounts. Often, much higher than a traditional blockchain. However, DAG technology is still in its infancy and there are still many questions about its performance and how decentralised they actually are. Specifically to Syscoin, whenever a node receives a newly broadcasted transaction, it will relay the transaction to other nodes before validating it. This means that also potentially invalid transactions are broadcasted to the rest of the network. It is not sure how this can impact the network if high volumes of invalid transactions are broadcasted to the network. Also, Syscoin waits 10 seconds for a transaction to arrive before checking its validity. It would be nice if they could provide some more quantitive arguments to back up this "10 seconds rule". In short, I feel that the Syscoin network should be stress-tested a bit more to really figure out how well their protocol works. Let's hope for the best! Conclusion DAG technology has shown some great potential in many projects like Nano, Byteball, and now Syscoin. It mostly allows for a higher transaction throughput than a regular blockchain project. In short about Syscoin, it holds some innovative technical approaches to increase their transaction throughput. The most interesting one is the parallel signature validation. Let’s see how this innovative approach entangles itself in the future.

Entangling Z-DAG Technology with SysCoin

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