PoWerStore

The overhead of Byzantine fault tolerant (BFT) storage is a primary concern that prevents its adoption in practice. The cost stems from the need to maintain at least 3t + 1 copies of the data at different storage replicas in the asynchronous model, so that t Byzantine replica faults can be tolerated. This paper presents MDStore, the first fully asynchronous BFT storage protocol that reduces the number of replicas that store the payload data to as few as 2t + 1 and maintains metadata at 3t + 1 replicas on (possibly) different servers. At the heart of MDStore lies a metadata service built upon a new abstraction called “timestamped storage.” Timestamped storage allows for conditional writes (facilitating the implementation of the metadata service) and has consensus number one (making it implementable with wait-free semantics in an asynchronous system despite faults). In addition to its low replication overhead, MDStore offers strong guarantees by emulating a multi-writer multi-reader atomic register, providing wait-free termination, and tolerating any number of Byzantine readers and crash-faulty writers.

Byzantine fault-tolerant storage systems can provide high availability in hazardous environments, but the redundant servers they require increase software development and hardware costs. In order to minimize the number of servers required to implement fault-tolerant storage services, we develop a new algorithm that uses a “Listeners” pattern of network communication to detect and resolve ordering ambiguities created by concurrent accesses to the system. Our protocol requires 3f + 1 servers to tolerate up to f Byzantine faults—f fewer than the 4f + 1 required by existing protocols for non-self-verifying data. In addition, SBQ-L provides atomic consistency semantics, which is stronger than the regular or pseudo-atomic semantics provided by these existing protocols. We show that this protocol is optimal in the number of servers— any protocol that provides safe semantics or stronger requires at least 3f + 1 servers to tolerate f Byzantine faults in an asynchronous system. Finally, we examine a non-confirmable writes variation of the SBQ-L protocol where a client cannot determine when its writes complete. We show that SBQ-L with non-confirmable writes provides regular semantics with 2f + 1 servers and that this number of servers is minimal.

Geographically distributed storage is an important method of ensuring high data availability in cloud computing and storage systems. With the increasing demand for moving file systems to the cloud, current methods of providing such enterprise-grade resiliency are very inefficient. For example, replication based methods incur large storage cost though they provide low access latencies. While erasure coded schemes reduce storage cost, they are associated with large access latencies and high bandwidth cost. In this paper, we propose a novel scheme named CAROM, an ensemble of replication and erasure codes, to provide resiliency in cloud file systems with high efficiency. While maintaining the same consistency semantics seen in today's cloud file systems, CAROM provides the benefit of low bandwidth cost, low storage cost, and low access latencies. We perform a large-scale evaluation using real-world file system traces and demonstrate that CAROM outperforms replication based schemes in storage cost by up to 60% and erasure coded schemes in bandwidth cost by up to 43%, while maintaining low access latencies close to those in replication based schemes.

Cloud computing is the next stage in evolution of the internet, which provides large amount of computing and storage to customers provisioned as a service over the internet. However, cloud computing facing so many security challenges due to the possible compromise or byzantine failures. In this paper, we focus on Ensuring data storage security in cloud computing, which is an important aspect of Quality of Service (QoS). We propose an effective and flexible distribution verification protocol to address data storage security in cloud computing. In this protocol, we rely on erasure code for the availability, reliability of data and utilize token pre-computation using Sobol Sequence to verify the integrity of erasure coded data rather than Pseudorandom Data in existing system. Unlike prior works, our scheme provides more security to user data stored in cloud computing. The performance analysis shows that our scheme is more secure than existing system against Byzantine failure, unauthorized data modification attacks, and even cloud server colluding attacks.

The growing number of Internet of Things (IoT) objects and the operational and security challenges in IoT systems are encouraging researchers to design suitable IoT architecture. Enormous data generated in the IoT environment face several kinds of security and privacy challenges. IoT system generally suffers from several issues like data storage, safety, privacy, integrity, transparency, trust, and single point of failure. IoT environment is emerging with several solutions to resolve these problems. The main objective of this paper is to design a cloud-blockchain-based secure IoT architecture that provides advanced and efficient storage and security solutions to IoT ecosystem. Blockchain technology appears to be a decent choice to resolve such kinds of problems. Blockchain technology uses a hash-based cryptographic technique for information security and integrity. Cloud computing provides advanced storage solutions with several remote services to store, compute and analyze the data. The proposed IoT architecture is based on the integration of cloud and blockchain services, which aim to provide transparent, decentralized, and trustworthy and secure storage solutions. In addition to the standard layers (perception layer, network layer, processing layer, and application layer) the proposed IoT architecture in the present paper includes a service layer, a security layer, and a parallel management and control layer, which focus on the security and management of the entire IoT infrastructure.

To balance performance and storage efficiency, modern clustered file systems often first store data with replication, followed by encoding the replicated data with erasure coding. We argue that the commonly used random replication does not take into account erasure coding in its design, thereby raising both performance and availability issues in the subsequent encoding operation. We propose encoding-aware replication, which carefully places the replicas so as to (i) eliminate cross-rack downloads of data blocks during the encoding operation, (ii) preserve availability without data relocation after the encoding operation, and (iii) maintain load balancing across replicas as in random replication before the encoding operation. We conduct extensive HDFS-based testbed experiments and discrete-event simulations, and demonstrate the performance gains of encoding-aware replication over random replication.

he HotStuff protocol is a recent breakthrough in Byzantine Fault Tolerant (BFT) consensus that enjoys both responsiveness and linear view change by creatively adding a round to classic two-round BFT protocols like PBFT. Despite its great advantages, HotStuff has a few limitations. First, the additional round of communication during normal cases results in higher latency. Second, HotStuff is vulnerable to certain performance attacks, which can significantly deteriorate its throughput and latency. To address these limitations, we propose a new two-round BFT protocol called Fast-HotStuff, which enjoys responsiveness and efficient view change that is comparable to the linear view-change in terms of performance. Our Fast-HotStuff has lower latency and is more robust against the performance attacks that HotStuff is susceptible to.

The primary concern of traditional Byzantine fault tolerance is to ensure strong replica consistency by executing incoming requests sequentially according to a total order. Speculative execution at both clients and server replicas has been proposed as a way of reducing the end-to-end latency. In this article, we introduce optimistic Byzantine fault tolerance. Optimistic Byzantine fault tolerance aims to achieve higher throughput and lower end-to-end latency by using a weaker replica consistency model. Instead of ensuring strong safety as in traditional Byzantine fault tolerance, nonfaulty replicas are brought to a consistent state periodically and on-demand in optimistic Byzantine fault tolerance. Not all applications are suitable for optimistic Byzantine fault tolerance. We identify three types of applications, namely, realtime collaborative editing, event stream processing, and services constructed with conflict-free replicated data types, as good candidates for applying optimistic Byzantine fault tolerance. Furthermore, we provide a design guideline on how to achieve eventual consistency and how to recover from conflicts at different replicas. In optimistic Byzantine fault tolerance, a replica executes a request immediately without first establishing a total order of the message, and Byzantine agreement is used only to establish a common state synchronization point and the set of individual states needed to resolve conflicts. The recovery mechanism ensures both replica consistency and the validity of the system by identifying and removing the operations introduced by faulty clients and server replicas.

The use of good random numbers is crucial to the security of many mission-critical systems. However, when such systems are replicated for Byzantine fault tolerance, a serious issue arises (i.e., how do we preserve the integrity of the systems while ensuring strong replica consistency?). Despite the fact that there exists a large body of work on how to render replicas deterministic under the benign fault model, the solutions regarding the random number control are often overly simplistic without regard to the security requirement, and hence, they are not suitable for practical Byzantine fault tolerance. In this chapter, the authors present a novel integrity-preserving replica coordination algorithm for Byzantine fault tolerant systems. The central idea behind our CD-BFT algorithm is that all random numbers to be used by the replicas are collectively determined, based on the contributions made by a quorum of replicas, at least f+1 of which are not faulty.

Lifetime and availability of data stored on a P2P system: Evaluation of redundancy and recovery schemes

International audience

Work to date on algorithms for message-passing systems has explored a wide variety of types of faults, but corresponding work on shared memory systems has usually assumed that only crash faults are possible. In this work, we explore situations in which processes accessing shared objects can fail arbitrarily (Byzantine faults).KeywordsShared MemoryCorrect ProcessShared ObjectShared Memory SystemFaulty ProcessThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This paper addresses the problem of solving stabilizing uniform consensus in mobile networks. In this problem, the input of nodes may change multiple times before they eventually stabilize. However, when the system stabilizes all correct nodes output a value and there are no two non-crashed nodes (whether faulty or not) that output different values. In contrast to stabilizing consensus, stabilizing uniform consensus is not solvable with Byzantine faults. So we consider here weaker kinds of faults, namely crash faults and omission faults. We show that for crash and send-omission faults, n > 2t is a necessary and sufficient condition for solving stabilizing uniform consensus, where n is the total number of mobile nodes, out of which t may be faulty. Interestingly, when the input of nodes are fixed, stabilizing uniform consensus is solvable with crash faults for n > t and with send-omission faults for n > 2t (for t > 1). When considering general omission faults, we show that stabilizing uniform consensus is not solvable, even for fixed inputs and t = 1.

Design and implementation of a Byzantine fault tolerance framework for Web services

Cluster-based databases have been traditionally used for providing fault tolerant storage solutions. However, the limited scalability of this kind of systems has motivated the creation of a variety of storage systems based on the cloud paradigm, which achieve high scalability and availability by giving up some functionalities such as strong consistency. While this is fairly acceptable for a wide range of applications, there are still many use cases which cannot take advantage of the cloud paradigm because they are unable to resign their transactional nature. The purpose of this paper is to review how these novel systems overcome typical scalability and availability issues and present a new architecture able to offer transactional support on the cloud. This hybrid architecture is based on well-known replication protocols used in classic transactional systems which are combined according to the application workload, thus providing different consistency levels depending on the needs of each application. Moreover, the system inherits the elasticity and dynamism properties of the cloud paradigm, which makes it able to offer high scalability and availability levels without sacrificing transactional support.