Abstract The number of users approaching the world of cryptocurrencies exploded in the last years, and consequently the daily interactions on their underlying distributed ledgers have intensified. In this paper, we analyze the flow of these digital transactions in a certain period of time, trying to discover important insights on the typical use of these technologies by studying, through complex network theory, the patterns of interactions in four prominent and different Distributed Ledger Technologies (DLTs), namely Bitcoin, DogeCoin, Ethereum, Ripple. In particular, we describe the Distributed Ledger Network Analyzer (DiLeNA), a software tool for the investigation of the transactions network recorded in DLTs. We show that studying the network characteristics and peculiarities is of paramount importance, in order to understand how users interact in the DLT. For instance, our analyses reveal that all transaction graphs exhibit small world properties.
Quan Nguyen, André Cronje, Michael Kong, Egor Lysenko · 5 authors
This paper consolidates the core technologies and key concepts of our novel Lachesis consensus protocol and Fantom Opera platform, which is permissionless, leaderless and EVM compatible. We introduce our new protocol, so-called Lachesis, for distributed networks achieving Byzantine fault tolerance (BFT)~\cite{lachesis01}. Each node in Lachesis protocol operates on a local block DAG, namely \emph{OPERA DAG}. Aiming for a low time to finality (TTF) for transactions, our general model considers DAG streams of high speed but asynchronous events. We integrate Proof-of-Stake (PoS) into a DAG model in Lachesis protocol to improve performance and security. Our general model of trustless system leverages participants' stake as their validating power~\cite{stakedag}. Lachesis's consensus algorithm uses Lamport timestamps, graph layering and concurrent common knowledge to guarantee a consistent total ordering of event blocks and transactions. In addition, Lachesis protocol allows dynamic participation of new nodes into Opera network. Lachesis optimizes DAG storage and processing time by splitting local history into checkpoints (so-called epochs). We also propose a model to improve stake decentralization, and network safety and liveness ~\cite{stairdag}. Built on our novel Lachesis protocol, Fantom's Opera platform is a public, leaderless, asynchronous BFT, layer-1 blockchain, with guaranteed deterministic finality. Hence, Lachesis protocol is suitable for distributed ledgers by leveraging asynchronous partially ordered sets with logical time ordering instead of blockchains. We also present our proofs into a model that can be applied to abstract asynchronous distributed system.
Fault tolerance of a blockchain is often characterized by the fraction $f$ of "adversarial power" that it can tolerate in the system. Despite the fast progress in blockchain designs in recent years, existing blockchain systems can still only tolerate $f$ below $0.5$. Can practically usable blockchains tolerate a malicious majority, i.e., $f$ above $0.5$? This work presents a positive answer to this question. We first note that the well-known impossibility of {\em byzantine consensus} for $f$ above $0.5$ does not carry over to blockchains. To tolerate $f$ above $0.5$, we use {\em byzantine broadcast}, instead of byzantine consensus, as the core of the blockchain. A major obstacle in doing so, however, is that the resulting blockchain may have extremely low throughput. To overcome this central technical challenge, we propose a novel byzantine broadcast protocol OverlayBB, that can tolerate $f$ above $0.5$ while achieving good throughput. Using OverlayBB as the core, we present the design, implementation, and evaluation of a novel Proof-of-Stake blockchain called BCube. BCube can tolerate a malicious majority, while achieving practically usable transaction throughput and confirmation latency in our experiments with $10000$ nodes and under $f = 0.7$. To our knowledge, BCube is the first blockchain that can achieve such properties.
Proof-of-Stake (PoS) blockchain systems, especially those that allow stakeholders to organize themselves in “stake-pools”, have emerged as a compelling paradigm for the deployment of large scale distributed ledgers. A stake-pool operates a node that engages in the PoS protocol and potentially represents a large number of smaller stakeholders. While such pooled PoS operation is attractive from various angles, it also exhibits a significant shortcoming that, so far and to the best of our knowledge, has not been sufficiently understood or investigated. Pooled PoS operation, to be effective and not lead to sub-optimal dictatorial or cartel-like configurations, should enable the stakeholders to revoke and re-delegate their stake in a way that is aligned with their incentives. However, given that stake-pool operators are exactly those entities who determine what transactions are to be recorded in the ledger, they are quite likely to form a cartel and censor any transaction they want, such as those that attempt to adjust the current stake-pool lineup. In this way, a power grab takes place, where the stake-pool cartel perpetuates its control over the PoS system. We first model and observe formally the emergence of the above problem in pooled PoS systems. Then, we describe an anti-censorship mechanism that takes advantage of the underlying cryptographic functions of the ledger and the nature of peer-to-peer networks to diffuse information without suppression. Specifically, the mechanism exploits digital signatures which can endorse messages that are censored and bind them to delegation transactions, as well as the ability of the underlying ledger to produce unpredictable randomness which can be used to randomly “audit” the suitability of a stake-pool by forcibly expiring it. Upon such expiration, members can evaluate their membership taking into account what information is available, including information potentially not recorded in the ledger but diffused in the peer-to-peer network. We provide a thorough game-theoretic analysis of this mechanism discovering various types of Nash equilibria which demonstrate that the “revolution”, i.e., the strategic decision of pool members to withdraw support from a censoring cartel as well as the pool operators to step down, can be incentivized, under suitable and plausible conditions in the utility functions of the involved participants.
Damilare Peter Oyinloye, Je Sen Teh, Norziana Jamil, Moatsum Alawida
Blockchain networks are based on cryptographic notions that include asymmetric-key encryption, hash functions and consensus protocols. Despite their popularity, mainstream protocols, such as Proof of Work or Proof of Stake still have drawbacks. Efforts to enhance these protocols led to the birth of alternative consensus protocols, catering to specific areas, such as medicine or transportation. These protocols remain relatively unknown despite having unique merits worth investigating. Although past reviews have been published on popular blockchain consensus protocols, they do not include most of these lesser-known protocols. Highlighting these alternative consensus protocols contributes toward the advancement of the state of the art, as they have design features that may be useful to academics, blockchain practitioners and researchers. In this paper, we bridge this gap by providing an overview of alternative consensus protocols proposed within the past 3 years. We evaluate their overall performance based on metrics such as throughput, scalability, security, energy consumption, and finality. In our review, we examine the trade-offs that these consensus protocols have made in their attempts to optimize scalability and performance. To the best of our knowledge, this is the first paper that focuses on these alternative protocols, highlighting their unique features that can be used to develop future consensus protocols.
Juan Boubeta-Puig, Jesús Rosa-Bilbao, Jan Mendling
Blockchain provides an immutable distributed ledger for storing transactions. One of the challenges of blockchain is the particular processing of dynamic queries due to accumulating costs. Complex Event Processing (CEP) provides efficient and effective support for this in a way, however, that is difficult to integrate with blockchain. This paper addresses the research challenges of integrating blockchain with CEP. More specifically, we envision an effective development environment in which (i) event-driven smart contracts are modeled in a graphical way, which are, in turn, (ii) automatically transformed into complementary code that is deployed in both a CEP engine and a blockchain network, and then (iii) executed on off-chain CEP applications which, connected to different data sources and sinks, automatically invoke smart contracts when event pattern conditions are met. We follow a classic systems engineering approach for defining the concepts of our system, called CEPchain, which addresses the described requirements. CEPchain was evaluated using a real-world case study for vaccine delivery, which requires an unbroken cold chain. The results demonstrate that our approach can be applied without requiring experts on event processing and smart contract languages. Our contribution simplifies the design of integrated CEP and blockchain functionality by hiding implementation details and supporting efficient deployment.
Runtime monitoring comes at a runtime cost. Overheads induced by monitoring and verification code may be necessary, and yet prohibitive in certain circumstances. When verification is local to a single unit of execution in a system, one can choose whether or not to monitor based on the risk of that individual unit. In this paper, we propose a monitoring and verification approach for a class of long-lived transaction-based systems whose execution can be partitioned into separate subtraces, one for each such transaction, and which are independent of each other from a correctness perspective. We focus on the use of this approach for the monitoring of smart contracts on distributed ledger technologies to show how we can reduce overheads in this manner.
The use of blockchain technology is becoming more widespread. Governments have expanded their use of the technology from online polls to business management of smaller local governments while private institutions have increased their services from financial to medical services management. This paper presents the modified pBFT blockchain consensus algorithm for a more efficient data management method in cases of applying blockchains in authorized nodes such as governmental agencies. The network communication cost was minimized while the consensus accuracy was maximized by applying a method of simplifying the request management process and electing the reliability-based consensus node during the pBFT consensus algorithm process. By applying the modified pBFT consensus algorithm, stability and speed of the consensus and verification process among various organizations can be guaranteed as well as application in efficient management and value creation of data.
Jian Liu, Peilun Li, Raymond Cheng, N. Asokan · 5 authors
Today's blockchains suffer from low throughput and high latency, which impedes their widespread adoption of more complex applications like smart contracts. In this paper, we propose a novel paradigm for smart contract execution. It distinguishes between consensus nodes and execution nodes: different groups of execution nodes can execute transactions in parallel; meanwhile, consensus nodes can asynchronously order transactions and process execution results. Moreover, it requires no coordination among execution nodes and can effectively prevent livelocks. We show two ways of applying this paradigm to blockchains. First, we show how we can make Ethereum support parallel and asynchronous contract execution \emph{without hard-forks}. Then, we propose a new public, permissionless blockchain. Our benchmark shows that, with a fast consensus layer, it can provide a high throughput even for complex transactions like Cryptokitties gene mixing. It can also protect simple transactions from being starved by complex transactions.
Blockchain creates a secure environment on top of strict cryptographic assumptions and rigorous security proofs. It permits on-chain interactions to achieve trustworthy properties such as traceability, transparency, and accountability. However, current blockchain trustworthiness is only confined to on-chain, creating a “trust gap” to the physical, off-chain environment. This is due to the lack of a scheme that can truthfully reflect the physical world in a real-time and consistent manner. Such an absence hinders further blockchain applications in the physical world, especially for the security-sensitive ones. In this paper, we propose a framework to extend blockchain trust from on-chain to off-chain, and take trustworthy vaccine tracing as an example scheme. Our scheme consists of 1) a Trusted Execution Environment (TEE)-enabled trusted environment monitoring system built with the Arm Cortex-M33 microcontroller that continuously senses the inside of a vaccine box through trusted sensors and generates anti-forgery data; and 2) a consistency protocol to upload the environment status data from the TEE system to blockchain in a truthful, real-time consistent, continuous and fault-tolerant fashion. Our security analysis indicates that no adversary can tamper with the vaccine in any way without being captured. We carry out an experiment to record the internal status of a vaccine shipping box during transportation, and the results indicate that the proposed system incurs an average latency of 84 ms in local sensing and processing followed by an average latency of 130 ms to have the sensed data transmitted to and been available in the blockchain.
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.
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.
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.
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.
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.
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.
In this paper, a novel Byzantine consensus protocol among $n$ players is proposed for the partially synchronous model. In particular, by assuming that standard cryptography is unbreakable, and that $n>\max\bigl(\frac{3}{2}k+3t,2(k+t)\bigr)$, this protocol is an equilibrium where no coalition of $k$ rational players can coordinate to increase their expected utility regardless of the arbitrary behavior of up to $t$ Byzantine players. We show that a baiting strategy is necessary and sufficient to solve this, so-called rational agreement problem. First, we show that it is impossible to solve this rational agreement problem without implementing a baiting strategy, a strategy that rewards rational players for betraying its coalition, by exposing undeniable proofs of fraud. Second, we propose the Huntsman protocol that solves the rational agreement problem by building recent advances in the context of accountable Byzantine agreement in partial synchrony. This protocol finds applications in distributed ledgers where players are incentivized to steal assets by leading other players to a disagreement on two distinct decisions where they ``double spend''.
Hyperledger Fabric is an enterprise grade permissioned distributed ledger platform that offers modularity for a broad set of industry use cases. One modular component is a pluggable ordering service that establishes consensus on the order of transactions and batches them into blocks. However, as of the time of this writing, there is no production grade Byzantine Fault-Tolerant (BFT) ordering service for Fabric, with the latest version (v2.3) supporting only Crash Fault-Tolerance (CFT).In this work we describe the design and implementation of a BFT ordering service for Fabric, employing a new BFT consensus library. The new library, based on the BFT-SMART protocol and written in Go, is tailored to the blockchain use-case, yet is general enough to cater to a wide variety of other uses. The BFT library's design and integration into Fabric address crucial aspects that were left unsolved in all prior work, making them unfit for production use. We evaluate the new BFT ordering service by comparing it with the currently supported Raft-based CFT ordering service in Hyperledger Fabric.
Distributed ledgers based on Proof-of-Work (PoW) are typically vulnerable when mining participation is low. During these periods, an attacker with a mining majority can mount serious attacks, like double spending or transaction censorship. Our work explores mechanisms to secure a ledger against such adversaries and puts forth the first rigorous study of checkpointing as a protection from 51% attacks. The core idea is to employ an external set of parties to finalize blocks after their creation. This idea takes the form of checkpointing and timestamping, the former ensuring low latency in a federated setting and the latter being fully decentralized. Crucially, we identify and protect against a (previously undocumented) attack, "block lead", thus our scheme is the first to guarantee liveness.