Performance of cooperation-based networks, like delay tolerant networks (DTNs), are severely affected by selfish nodes that are not willing to participate in message forwarding due to resource constraints. Thus, nodes must receive satisfactory incentives to compensate their resource depletion for cooperation. The available incentive schemes for DTNs either rely on hypothetical central trusted authorities or do not use explicit digital currency that is provably secure. Blockchain, a decentralized and secure digital ledger of immutable transactions, is an attractive approach for addressing the incentive challenges in DTNs that lack central trusted authorities. Ethereum, the blockchain-based cryptocurrency, makes it possible to devise practical credit-based incentive schemes for such networks. However, the usage of blockchain is restricted by the availability of end-to-end Internet connectivity, which restricts the use of blockchain in intermittently connected networks like DTNs and has prompted exploration of new mechanisms for using blockchain in such networks. This chapter first proposes a mechanism, based on the Ethereum platform using smart contracts in Solidity, for integrating blockchain technology with DTNs, towards exploiting the immutability and availability of blockchains in DTNs. It then develops BlockCent, a blockchain-based node incentivizing scheme for DTNs that runs on the blockchain-DTN integrated environment. The scheme uses a novel reward strategy to bring rationality to the incentivizing process. To add logic to the incentivizing method, the scheme uses a novel incentive strategy. The proposed incentivizing scheme is applied to the disaster management use case for fast transmission of relief shelter needs to the emergency operation center, thus leading to efficient disaster relief. Extensive security analysis justifies security of the proposed scheme. Exhaustive experiments conducted on the ONE simulator and the Ethereum platform substantiate the efficiency of the scheme in terms of design parameters like selfishness reduction and reward fairness, and network parameters like delivery ratio, average delay, and overhead ratio, while not compromising blockchain performance parameters like processing time and gas consumption.
Jun 18, 2021·2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)
Ethereum is a permissionless blockchain with a Turing complete machine for smart contracts. Ethereum's Gas mechanism, which charges the execution of each operation code, is proposed to ensure the termination of smart contracts that run in the EVM (Ethereum Virtual Machine) and to compensate the computational usage. Thus, the Gas awarded should be rational to the required computational, to ensure the alignment and to avoid the denial of services attack. Currently, in Ethereum, Gas awarded is set statically for each operational code in the smart contract, but it is unknown if whether these values are correct or not for various computer architectures. Therefore, in this paper, we show the most common used operational codes and the rationality of the Gas to the CPU usage for a selected set of the EVM's operational codes.
Sharding is a popular way to achieve scalability in blockchain protocols, increasing their throughput by partitioning the set of transaction validators into a number of smaller committees, splitting the workload. Existing approaches for blockchain sharding, however, do not scale well when concurrent transactions alter the same replicated state component—a common scenario in Ethereum-style smart contracts.
Amirmohammad Pasdar, Zhongli Dong, Young Choon Lee
Blockchain is a form of distributed ledger technology (DLT) where data is shared among users connected over the internet. Transactions are data state changes on the blockchain that are permanently recorded in a secure and transparent way without the need of a third party. Besides, the introduction of smart contracts to the blockchain has added programmability to the blockchain and revolutionized the software ecosystem leading toward decentralized applications (DApps) attracting businesses and organizations to employ this technology. Although promising, blockchains and smart contracts have no access to the external systems (i.e., off-chain) where real-world data and events resides; consequently, the usability of smart contracts in terms of performance and programmability would be limited to the on-chain data. Hence, \emph{blockchain oracles} are introduced to mitigate the issue and are defined as trusted third-party services that send and verify the external information (i.e., feedback) and submit it to smart contracts for triggering state changes in the blockchain. In this paper, we will study and analyze blockchain oracles with regard to how they provide feedback to the blockchain and smart contracts. We classify the blockchain oracle techniques into two major groups such as voting-based strategies and reputation-based ones. The former mainly relies on participants' stakes for outcome finalization while the latter considers reputation in conjunction with authenticity proof mechanisms for data correctness and integrity. We then provide a structured description of patterns in detail for each classification and discuss research directions in the end.
Permissioned Blockchains are increasingly considered in enterprise use-cases, many of which do not require geo-distribution, or even disallow it due to legislation. Examples include countrywide networks, such as Alastria, or those deployed using cloud-based platforms such as IBM Blockchain Platform. We expect these blockchains to eventually run in environments with high bandwidth and low latency modern networks, as well as with advanced programmable hardware accelerators.
Zachary Painter, Victor Cook, Christina Peterson, Damian Dechev
Blockchain networks use consensus mechanisms so participants can exchange transactions without the need to rely on a trusted third party. Consensus mechanisms using Proof of Work burn significant energy to select a block miner and the delay limits performance. Other consensus mechanisms such as Proof of Stake or Practical Byzantine Fault Tolerance still designate a single validator to append a block to the chain, preventing blocks from being built and published in parallel. In this paper we introduce a new consensus mechanism, Proof of Descriptor, enabling clients to work together to publish blockchain transactions using a descriptor object which stores information on the cooperative parallel execution of transactions. Proof of Descriptor consensus allows commutative transactions to be mined individually. It does not require a leader to propose the next block, enabling clients to cooperate on completing transactions, assembling blocks and publishing them. We demonstrate that our approach is less prone to attack since it is not vulnerable to a malicious leader, while simulations show a potential 20x improvement over the fastest sequential blockchain, Solana.
Blockchain-based smart contract platforms have traditionally employed the transaction-driven execution model. This paper presents an alternate framework for blockchain-based smart contract execution called EDSC. Our platform design presents a novel approach to tackle the scalability and performance challenges facing the smart contract ecosystem. We base EDSC's design on the Ethereum template, and it can be readily implemented for other existing smart contract platforms. To evaluate our design, we perform an experimental implementation using the Ethereum client. Our experiments with performance modeling show, on average, a 2.2 to 4.6 times reduced total latency of event-triggered smart contracts, demonstrating the effectiveness of the design in supporting time-sensitive applications. Additionally, we comment on the design's potential security aspects and demonstrate its utility by discussing potential use cases.
The full-replication data storage mechanism, as commonly utilized in existing blockchains, suffers from poor scalability, since it requires every node to preserve a complete copy of the whole block data locally to tolerant potential Byzantine failures. In a hostile environment, the malicious node may discard or tamper data deliberately. Thus, existing distributed storage method, which partitions data into multiple parts and distributes them over all nodes, cannot suit for blockchains. This demonstration showcases BFT-Store, a novel distributed storage engine for blockchains to break full-replication by integrating erasure coding with Byzantine Fault Tolerance (BFT) consensus protocol. This demonstration will (\romannumeral1) allow audience members to see how BFT-Store partitions block data over all nodes to reduce the storage occupation of system, and (\romannumeral2) allow audience members to see how BFT-Store recovers blocks under distributed scenario even with Byzantine failure.
Mohammad Javad Amiri, Divyakant Agrawal, Amr El Abbadi
The unique features of blockchains such as immutability, transparency, provenance, and authenticity have been used by many large-scale data management systems to deploy a wide range of distributed applications including supply chain management, healthcare, and crowdworking in permissioned settings. Unlike permissionless settings, e.g., Bitcoin, where the network is public, and anyone can participate without a specific identity, a permissioned blockchain system consists of a set of known, identified nodes that might not fully trust each other. While the characteristics of permissioned blockchains are appealing to a wide range of largescale data management systems, these systems, have to satisfy four main requirements: confidentiality, verifiability, performance, and scalability. Various approaches have been developed in industry and academia to satisfy these requirements with varying assumptions and costs. The focus of this tutorial is on presenting many of these techniques while highlighting the trade-offs among them. We demonstrate the practicality of such techniques in real-life by presenting three different applications, i.e., supply chain management, large-scale databases, and multi-platform crowdworking environments, and show how those techniques can be utilized to meet the requirements of such applications.
Pingcheng Ruan, Tien Tuan Anh Dinh, Dumitrel Loghin, Meihui Zhang · 7 authors
Blockchain has come a long way - a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain evolves into another data management system, the natural question is how it compares against distributed database systems. Existing works on this comparison focus on high-level properties, such as security and throughput. They stop short of showing how the underlying design choices contribute to the overall differences. Our work fills this important gap.
The blockchain has been considered as a new decentralized computing paradigm that has great potential to meet various computing needs. Considering a private network (such as data center) where incentive mechanisms are not required, this paper innovatively remolds the transaction-recording blockchain for decentralized data processing. In our design, workers have different processing capacity and tasks have different resource requirements. Workers first get task information from the blockchain and then process tasks locally, and next perform the proof of useful work (PoUW) consensus to compete for a scheduler, according to the number of the consumed CPU instructions in data processing. The scheduler is responsible for dispatching task information to the blockchain. A salient feature of our decentralized data processing is that workers actively select tasks, instead of passively receiving tasks as in a centralized framework. This will lead to collisions (i.e., multiple workers select the same task). To alleviate the collisions and provide the max-min fairness of data-processing, we propose a modified fair queue (called M-FQ) algorithm for the scheduler, as well as a fair task selection with collision avoidance (called Fair-CA) scheme for workers. Extensive simulations verify that our framework can well balance the fairness and the collision, while achieving as high throughput and good fairness as centralized frameworks. This study is the first attempt toward designing a general decentralized computing framework.
Haytham Qushtom, Jelena Mišić, Xiaolin Chang, Vojislav B. Mišić
The use of blockchain for Internet-of-Things (IoT) data recording necessitates an efficient and scalable consensus mechanism. In this paper, we describe a two-tier architecture in which IoT data is packaged in batches or blocks, approved by a low-tier cluster first and a top-tier cluster second, before being added to the replicated blockchain ledger. Both tiers use PBFT-like consensus enhanced with multiple-entry point operation using bandwidth reservation. This approach eliminates the dependence on a single primary leader that is characteristic for PBFT-like protocols, and allows the system to be deployed in geographically wide area. We provide a detailed probabilistic analysis of the proposed architecture using a discrete time Markov chain, and show that system performance depends on the number of ordering nodes in each cluster and the number of low-tier clusters.
Decentralized systems and protocols are becoming more popular every year. The main limitations of public permissionless blockchains are low bandwidth and high fees. There are various ways to reduce the load on the network to address these drawbacks, the majority of them were developed for Ethereum but stay valid for many other chains. The paper considers the following options for scaling decentralized systems: consensus modification and sharding that are embedded in the core of a blockchain, second layer solutions and sidechains that can be built on top of a network.
Alex Shamis, Peter Pietzuch, Miguel Castro, Edward Ashton · 12 authors
Permissioned ledger systems execute transactions on a set of replicas governed by members of a consortium. They use Byzantine fault tolerance protocols to distribute trust among the replicas, and thus can ensure linearizability if fewer than 1/3 of the replicas misbehave. With more misbehaving replicas, current systems provide no guarantees, and all replicas and members share the blame.
We describe PAC, a permissioned ledger system that \emph{assigns blame to misbehaving replicas} while supporting \emph{governance transactions} to change the consortium membership and the set of replicas. PAC signs and stores protocol messages in the ledger and provides clients with signed, universally-verifiable \emph{receipts} as evidence that a transaction executed at a certain ledger position. If clients obtain a sequence of receipts that violate linearizability, anyone can \emph{audit} the ledger and the sequence of receipts to assign blame to at least 1/3 of the replicas, even if all replicas and members misbehave. Auditing assigns blame by finding contradictory statements signed by the same replica. Since the set of replicas changes, PAC determines the valid signing keys at any point in the ledger using a shorter sub-ledger of governance transactions. PAC provides a strong disincentive to misbehavior at low cost: it can execute more than 48,000~transactions per second, and clients receive receipts in two network round trips.
Alex Shamis, Peter Pietzuch, Miguel Castro, Cédric Fournet · 12 authors
Permissioned ledger systems allow a consortium of members that do not trust one another to execute transactions safely on a set of replicas. Such systems typically use Byzantine fault tolerance (BFT) protocols to distribute trust, which only ensures safety when fewer than 1/3 of the replicas misbehave. Providing guarantees beyond this threshold is a challenge: current systems assume that the ledger is corrupt and fail to identify misbehaving replicas or hold the members that operate them accountable -- instead all members share the blame. We describe IA-CCF, a new permissioned ledger system that provides individual accountability. It can assign blame to the individual members that operate misbehaving replicas regardless of the number of misbehaving replicas or members. IA-CCF achieves this by signing and logging BFT protocol messages in the ledger, and by using Merkle trees to provide clients with succinct, universally-verifiable receipts as evidence of successful transaction execution. Anyone can audit the ledger against a set of receipts to discover inconsistencies and identify replicas that signed contradictory statements. IA-CCF also supports changes to consortium membership and replicas by tracking signing keys using a sub-ledger of governance transactions. IA-CCF provides strong disincentives to misbehavior with low overhead: it executes 47,000 tx/s while providing clients with receipts in two network round trips.
Amazon Elastic Kubernetes Service (EKS) high availability demands architectural, operational, and security considerations. Results show that Kubernetes cluster durability and performance under different workloads need multi-region failover, intelligent auto-scaling, and adequate networking. Cluster auto-scaler updates and vertical and horizontal autoscaling rules improve resource efficiency and computational overhead. High Kubernetes availability requires security. Least privilege enforcement, automatic certificate rotation, RBAC, and encryption reduce data breaches, compliance violations, and illegal access. AWS KMS, Secrets Manager, and service mesh-based mutual TLS authentication safeguarded cluster communication. Observability and performance benchmarking are critical for proactive system monitoring and resilience engineering. Companies use Prometheus and Grafana for metric collecting, Fluentd and OpenTelemetry for distributed tracing, and chaos engineering frameworks for fault injection to foresee and correct issues. These methods improve enterprise MTTR, downtime, and predictability. Industry case studies prove EKS installation works. Kubemetes' scalability, dependability, and affordability aid financial institutions, healthcare, e-commerce, and telecoms. Plenty of choice Best Kubernetes practices decrease latency, infrastructure costs, and downtime. Many themes are developing for Kubemetes' high availability. Rethinking workload orchestration with serverless Kubernetes solutions like AWS Fargate for EKS simplifies infrastructure administration and resource utilization. Without node provisioning, organizations can develop quickly and inexpensively. Kubernetes-based edge computing for latency-sensitive applications including real-time analytics, 10T device orchestration, and 5G network optimization is another trend. K3s and MicroK8s at the network edge and centralized multi-cluster control planes enable regionally distributed high availability with minimal latency. Istio, Linkerd, and Consul enhance interservice communication, traffic routing, and security. Massive Kubernetes systems benefit from progressive traffic shifting, zero-downtime rolling deployments, and autonomous circuit breaking. Another achievement is Kubernetes monitoring system machine learning-driven anomaly detection and predictive maintenance. Al-powered observability frameworks can identify infrastructure deterioration, forecast resource congestion, and automate preemptive scaling to avert failures and enhance workload allocation. Kubernetes high availability optimization has improved, however Al-driven auto-scaling and self-healing clusters need research. Traditional auto-scaling ümresholds disregard non-linear workloads, traffic surges, and unexpected failures. Analysis of reinforcement learning-based scaling algorithms that dynamically adjust cluster capacity in real time utilizing historical data, prediction analytics, and workload demand predictions. Kubernetes clusters that self-heal are another autonomous infrastructure management frontier. Complexities may prevent human intervention or failover. Al-driven failure detection, automatic node repair, and intelligent fault recovery can identify abnormalities, problematic nodes, shift workloads, and take real-time remedial action in Kubernetes clusters. Studying genetic algorithms and evolutionary computing for Kubemetes scheduler development is intriguing. Least-loaded node selection schedulers and computationally efficient bin packing are not adaptive. Al-driven evolutionary scheduling models may improve Kubernetes pod placement, inter-node communication cost, and workload allocation. Cross-cluster federation and Al-augmented multi-cluster load balancing are promising research areas. Dynamic workloads need real-time adaptive load balancing in Kubernetes Federation v2. Future Al-powered predictive load distribution models may improve federated cluster job allocation by factoring network latency, computational cost, and failure likelihood. Finally, blockchain-based decentralized cloud orchestration and Kubernetes high availability intrigue. Distributed ledger technology for secure state synchronization, federated identity management, and decentralized resource scheduling may make Kubernetes more resilient to cloud provider outages, security breaches, and infrastructure failures. Blockchain-based Kubernetes topologies may increase fault tolerance, frustless multi-cloud deployments, and data integrity across geographically distant clusters. High availability computing will be defined by Al-driven automation, self-healing infrastructure, and decentralized cloud-native designs as Kubernetes use grows. These improvements may improve Kubernetes workload orchestration, system resilience, and cloud-native application scalability.
Feilong Wang, Yipeng Ji, Mingsheng Liu, Yangyang Li · 7 authors
At present, the transaction delay of the consortium block chain applying the Practical Byzantine Fault Tolerance (PBFT) consensus protocol can only reach 2 to 5 seconds, and the throughput cannot reach tens of thousands. In addition as the number of nodes increases, the performance of the consortium block chain declines very quickly. The main challenge of previous research are to realize communication network topology of PBFT algorithm and high information exchange in the case of Byzantine failure, thus, this paper proposes an optimized Byzantine fault-tolerant algorithm to solve the performance bottleneck of the consortium chain. First of all, for the communication network structure of the whole network broadcast, we have reached an agreement on the transaction according to the pre-prepare and prepare phases of PBFT, and generally enter the commit phase, there is a high probability that the leader is honest, so we will communicate with the commit phase The network is optimized as a star communication structure. Second, combined with Tendermint, merge the view-change process of Byzantine failures of the normal consensus process, and switch the leader according to the longest chain principle. The algorithm is based on a partially synchronized network model to ensure the security and liveness of the protocol, and improve the performance and effective robustness.
This work proposes Practical Byzantine Fault Tolerance (PBFT) ordering service needed for block formation in permissioned blockchain environments. Contrary to current PBFT implementations that only provide a single point of entry to the ordering service, we allow each ordering node to act as an entry point that proposes and conducts the consensus process of including new record in the distributed ledger. To ensure atomicity of record insertion in distributed ledger, we have developed a bandwidth reservation protocol that uses a modification of CSMA/CA protocol to regulate access to the broadcast medium formed by the P2P network of TCP connections between orderers. We have modeled record insertion service time in a cluster where ordering nodes have random position within Cartesian coordinate system. We have also modeled total request access time to the ledger which includes waiting time in the ordered's queue and record insertion time. These models are used to evaluate system performance under variable request rate ordering service, variable number of nodes and variable physical cluster dimensions. We also address cluster interconnections which can increase coverage and capacity of PBFT system.
The revolution with technologies happens very often, here is one such technology called “Blockchain” which will be a game-changer in many functional sectors of the society. Initially, this technology was developed to support cryptocurrencies (such as Bitcoin, Ethereum, and Litecoin etc).Now a days it is gaining the attention of the researchers in almost the entire field. The consensus protocol in the cryptography and peer to peer architecture is one of the essential parts of the blockchain technology. The best consensus protocol in a blockchain system provides the fault tolerance. These censuses in blockchain are broadly classified in to two types. The absolute-finality consensus protocol and probabilistic-finality consensus protocols. In this paper, the different types of censuses protocols are discussed along with their working, strength and weakness. It also gives the overview on the different types of blockchain technology with their advantages and disadvantages. At the last we also presented a comparison of these consensus protocols by considering different qualitative parameters.
Andrew Cullen, Pietro Ferraro, Robert Shorten, William H. Sanders · 5 authors
The surge of Internet of Things (IoT) applications requires distributed systems capable of securely exchanging messages and immutably recording data. While traditional blockchain architectures were not designed with IoT in mind, more recent Distributed Ledger Technologies (DLTs), which are not based on proof of work, can be considered as a solution to deal with the above requirements. However, without proof of work, these ledgers require an explicit way to manage the rate at which messages are issued and disseminated. In this work, we present an access control scheme for IoT-oriented DLTs, that is the mechanism used to choose which messages can be written to the ledger. Our approach aims to efficiently exploit the available network resources (bandwidth, processing power) and to guarantee fair access depending on node reputation. While these concepts have already been touched by well-known areas of networking research, such as TCP and quality of service, in DLT networks this problem is harder since nodes cannot trust familiar feedback measurements, such as packet acknowledgements or congestion notifications. In this paper, we design a completely decentralised mechanism which involves a round robin-based scheduler and a TCP-inspired rate setter. Extensive simulations show that our approach provides fair access, guarantees that all honest nodes eventually receive the same messages, and makes sure that malicious nodes cannot degrade performance or affect security.
Recently, with the vigorous development of Decentralized Finance (DeFi) on Ethereum blockchain, the economic value and user scale of Ethereum keep growing. However, the low transaction processing capability of Ethereum prevents its further development. One factor that limits the transaction processing capability is the bandwidth required to synchronize the blocks over the nodes in the Ethereum network. This work proposes a new block synchronization protocol, referred to as LightBlock, which is dedicated to reducing the bandwidth used by the Ethereum network to disseminate messages. The LightBlock protocol is of great significance to the improvement of TPS. Since Ethereum's block synchronization protocol is a kind of gossip protocol, the redundant message propagation is its inherent shortcoming. In the LightBlock protocol, we use transaction Hash to replace the transaction of the original block to form a LightBlock structure. The propagation of LightBlock structure requires a much smaller bandwidth resource than the propagation of the original block has. Moreover, in order to reduce the communication overhead of the new protocol, each node needs to predict the missing transactions of its neighbor nodes before propagating the LightBlock strcuture. Therefore, we set up three models to measure the similarity of the current Ethereum node transaction pool and other parameters. Through analysis, the size of LightBlock is reduced by an average of 83.55% compared to the size of the current block; after adding the function of predicting missing transactions, the probability of not increasing the number of additional communications increases from 0.2 to 0.398.
For applications of Byzantine fault tolerant (BFT) consensus protocols where the participants are economic agents, recent works highlighted the importance of accountability: the ability to identify participants who provably violate the protocol. At the same time, being able to reach consensus under dynamic levels of participation is desirable for censorship resistance. We identify an availability-accountability dilemma: in an environment with dynamic participation, no protocol can simultaneously be accountably-safe and live. We provide a resolution to this dilemma by constructing a provably secure optimally-resilient accountability gadget to checkpoint a longest chain protocol, such that the full ledger is live under dynamic participation and the checkpointed prefix ledger is accountable. Our accountability gadget construction is black-box and can use any BFT protocol which is accountable under static participation. Using HotStuff as the black box, we implemented our construction as a protocol for the Ethereum 2.0 beacon chain, and our Internet-scale experiments with more than 4000 nodes show that the protocol achieves the required scalability and has better latency than the current solution Gasper, which was shown insecure by recent attacks.