Byzantine quorum systems

Summary. Quorum systems are well-known tools for ensuring the consistency and availability of replicated data despite the benign failure of data repositories. In this paper we consider the arbitrary (Byzantine) failure of data repositories and present the first study of quorum system requirements and constructions that ensure data availability and consistency despite these failures. We also consider the load associated with our quorum systems, i.e., the minimal access probability of the busiest server. For services subject to arbitrary failures, we demonstrate quorum systems over servers with a load of , thus meeting the lower bound on load for benignly fault-tolerant quorum systems. We explore several variations of our quorum systems and extend our constructions to cope with arbitrary client failures. Received: October 1996 / Accepted June 1998     

Fault detection for Byzantine quorum systems

In this paper, we explore techniques to detect Byzantine server failures in asynchronous replicated data services. Our goal is to detect arbitrary failures of data servers in a system where each client accesses the replicated data at only a subset (quorum) of servers in each operation. In such a system, some correct servers can be out-of-date after a write and can therefore, return values other than the most up-to-date value in response to a client's read request, thus complicating the task of determining the number of faulty servers in the system at any point in time. We initiate the study of detecting server failures in this context, and propose two statistical approaches for estimating the risk posed by faulty servers based on responses to read requests     

An SSL Back-End Forwarding Scheme in Cluster-Based Web Servers

State-of-the-art cluster-based data centers consisting of three tiers (Web server, application server, and database server) are being used to host complex Web services such as e-commerce applications. The application server handles dynamic and sensitive Web contents that need protection from eavesdropping, tampering, and forgery. Although the secure sockets layer (SSL) is the most popular protocol to provide a secure channel between a client and a cluster-based network server, its high overhead degrades the server performance considerably and, thus, affects the server scalability. Therefore, improving the performance of SSL-enabled network servers is critical for designing scalable and high-performance data centers. In this paper, we examine the impact of SSL offering and SSL-session-aware distribution in cluster-based network servers. We propose a back-end forwarding scheme, called ssl_with_bf, that employs a low-overhead user-level communication mechanism like virtual interface architecture (VIA) to achieve a good load balance among server nodes. We compare three distribution models for network servers, round robin (RR), ssl_with_session, and ssl_with_bf, through simulation. The experimental results with 16-node and 32-node cluster configurations show that, although the session reuse of ssl_with_session is critical to improve the performance of application servers, the proposed back-end forwarding scheme can further enhance the performance due to better load balancing. The ssl_with_bf scheme can minimize the average latency by about 40 percent and improve throughput across a variety of workloads.     

提高冗余服务性能的动态容错算法

针对分布式应用的性能要求,引入了负载平衡机制,以便对activere plication和primary backup容错算法进行权衡.提出一种基于冗余服务的动态容错算法RAWA(read-any-write-any),能根据系统负载状况动态改变请求的quorum,不但提高了请求的处理速度,而且以一种简单、有效的方式实现了负载平衡.结合所提出的一致性维护和互斥访问机制,该算法可以适用于嵌套访问和状态服务.另外,还分析了RAWA算法的性能,并通过在CORBA平台上与其他容错算法的对比测试,证明RAWA算法在     

Load balancing to adjust for proximity in some network topologies

Each job scheduler in large decentralized load balancing systems generally must consider whether it is advantageous to offload jobs to remote computation servers when the local load is too high. Although processing power may appear to be available at a very distant server, two problems arise due to the transmission delay between the scheduler and server. Predictably, the response time of the job is adversely affected as the job spends valuable time in transit, but a more subtle problem involves the value, or reliability, of the state information regarding job queues. The longer the delay between scheduler and server, the less a scheduler should value the state information of the server (given that the state changes over time). We examine the performance of schedulers in topologies with different average proximity and show a probabilistic algorithm that allows schedulers to dynamically form efficient clusters in the network.     

基于服务类型的负载平衡中间件模型

数字图书馆会出现用户请求响应时间较长、服务器资源消耗较大以及集群环境中各服务器性能不同导致的网络负载不平衡问题。为解决上述问题,提出基于服务类型的负载平衡中间件模型。该模型考虑不同的服务请求对服务器负载状况的影响,结合各服务器的性能进行动态负载调度。性能测试结果表明,该中间件负载平衡效果良好,可用性与可靠性较高。     

Signed quorum systems

With n servers that independently fail with probability of p < 0.5, it is well known that the majority quorum system achieves the best availability among all quorum systems. However, even this optimal construction requires (n+1)/2 functioning servers out of n. Furthermore, the number of probes needed to acquire a quorum is also lower bounded by (n+1)/2. Motivated by the need for a highly available and low probe complexity quorum system in the Internet, this paper proposes signed quorum systems (SQS) that can be available as long as any O(1) servers are available, and simultaneously have O(1) probe complexity. SQS provides probabilistic intersection guarantees and exploits the property of independent mismatches in today’s Internet. Such key property has been validated previously under multiple Internet measurement traces. This paper then extensively studies the availability, probe complexity, and load of SQS, derives lower bounds for all three metrics, and constructs matching upper bounds. We show that in addition to the qualitatively superior availability and probe complexity, SQS also decouples availability from load and probe complexity, so that optimal availability can be achieved under most probe complexity and load values. Haifeng Yu is currently a Researcher at Intel Research Pittsburgh. He is also an Adjunct Assistant Professor at the Department of Computer Science, Carnegie Mellon University. His research interests cover the general area of distributed systems, as well as related fields such as operating systems, database systems, fault-tolerance and large-scale peer-to-peer systems. Haifeng receives his Ph.D. and M.S. from Duke University, and his B.E. from Shanghai Jiaotong University, China. More information about his research is available at http://www.cs.cmu.edu/yhf.     

Load sharing in distributed multimedia-on-demand systems

Service providers have begun to offer multimedia-on-demand services to residential estates by installing isolated, small-scale multimedia servers at individual estates. Such an arrangement allows the service providers to operate without relying on a highspeed, large-capacity metropolitan area network, which is still not available in many countries. Unfortunately, installing isolated servers can incur very high server costs, as each server requires spare bandwidth to cope with fluctuations in user demand. The authors explore the feasibility of linking up several small multimedia servers to a (limited-capacity) network, and allowing servers with idle retrieval bandwidth to help out servers that are temporarily overloaded; the goal is to minimize the waiting time for service to begin. We identify four characteristics of load sharing in a distributed multimedia system that differentiate it from load balancing in a conventional distributed system. We then introduce a GWQ load sharing algorithm that fits and exploits these characteristics; it puts all servers' pending requests in a global queue, from which a server with idle capacity obtains additional jobs. The performance of the algorithm is captured by an analytical model, which we validate through simulations. Both the analytical and simulation models show that the algorithm vastly reduces wait times at the servers. The analytical model also provides guidelines for capacity planning. Finally, we propose an enhanced GWQ+L algorithm that allows a server to reclaim active local requests that are being serviced remotely. Simulation experiments indicate that the scheduling decisions of GWQ+L are optimal, i.e., it enables the distributed servers to approximate the performance of a large centralized server     

基于自主容器云平台的大数据日志采集系统

随着云计算、虚拟化、容器云等技术的应用以及国产自主可控的要求，越来越多的服务会部署在国产的服务器以及自主可控的容器云平台上。自主可控云平台上的服务在运行的过程中，需要获取日志数据，来进行一系列的监控、统计、分析以及预测工作。然而由于国产服务器的特殊性以及容器云平台的特殊性，传统的日志采集方式（包含实时采集和集中式采集）并不能够很好地适用于自主可控的容器云平台，为了提高服务的质量和性能并且保证日志数据的一定全面性，本文提出一种自适应的数据采集算法，能够根据服务器的负载自我调整日志数据采集发送量。当服务器负载较低的时候，提高数据采集和发送的数量，甚至是做到实时采集；当服务器负载较高时，降低对日志数据的采集和发送量，从而降低对服务器负载的压力，提高服务自身的质量和性能。最后通过理论和实验分析验证该数据采集算法在保证数据一定的全面性的同时，能有效缓解国产服务器的压力。     

Access control and signatures via quorum secret sharing

We suggest a method of controlling the access to a secure database via quorum systems. A quorum system is a collection of sets (quorums) every two of which have a nonempty intersection. Quorum systems have been used for a number of applications in the area of distributed systems. We propose a separation between access servers, which are protected and trustworthy, but may be outdated, and the data servers, which may all be compromised. The main paradigm is that only the servers in a complete quorum can collectively grant (or revoke) access permission. The method we suggest ensures that, after authorization is revoked, a cheating user Alice will not be able to access the data even if many access servers still consider her authorized and even if the complete raw database is available to her. The method has a low overhead in terms of communication and computation. It can also be converted into a distributed system for issuing secure signatures. An important building block in our method is the use of secret sharing schemes that realize the access structures of quorum systems. We provide several efficient constructions of such schemes which may be of interest in their own right     

Distributed cooperative Web servers

Traditional techniques for a distributed web server design rely on manipulation of central resources, such as routers or DNS services, to distribute requests designated for a single IP address to multiple web servers. The goal of the distributed cooperative Web server (DCWS) system development is to explore application-level techniques for distributing web content. We achieve this by dynamically manipulating the hyperlinks stored within the web documents themselves. The DCWS system effectively eliminates the bottleneck of centralized resources, while balancing the load among distributed web servers. DCWS servers may be located in different networks, or even different continents and still balance load effectively. DCWS system design is fully compatible with existing HTTP protocol semantics and existing web client software products.     

Playback Dispatch and Fault Recovery for a Clustered Video System with Multiple Servers

Recent technology advances have made multimedia on-demand services feasible. One of the challenges is to provide fault-tolerant capability at system level for a practical video-on-demand system. The main concern on providing fault recovery is to minimize the consumption of system resources on the surviving servers in the event of server failure. In order to reduce the overhead on recovery, we present three schemes for recovering faulty playbacks through channel merging and sharing techniques on the surviving servers. Furthermore, to evenly distribute the recovery load among the surviving servers, we propose a balanced dispatch policy that ensures load balancing in both the normal server conditions and the presence of a server failure.     

实时通信集群负载均衡策略研究与应用

实时通信主要传输实时音视频,具有低延时和高带宽消耗的特点.在用户量较大的场景下,单服务器方案无法满足整体需求,此时需搭建分布式集群对外提供服务,而如何将这些访问合理的分配到不同服务器上,均衡集群内服务器的负载就显得尤为重要.本文首先分析单服务器场景下的实时通信流程,然后研究和分析常见的负载均衡算法,同时为满足同群组客户端需转发到相同服务器的一致性要求,提出一种基于一致性哈希算法和遗传算法的自适应负载均衡算法,并对该算法进行应用和实验验证.     

基于Nginx负载均衡的动态改进算法

随着过去几十年互联网服务的指数增长,各大网站的访问量急剧上升。海量的用户请求使得热门网站的网络请求率可能在几秒钟内大规模增加。一旦服务器承受不住这样的高并发请求,由此带来的网络拥塞和延迟会极大地影响用户体验。负载均衡是高可用网络基础架构的关键组件,通过在后端引入一个负载均衡器,将工作负载分布到多个服务器来缓解海量并发请求对服务器造成的巨大压力,提高后端服务器和数据库的性能以及可靠性。而Nginx作为一款高性能的HTTP和反向代理服务器,正越来越多地应用到实践中。文中将分析Nginx服务器负载均衡的体系架构,研究默认的加权轮询算法,并提出一种改进后的动态负载均衡算法,实时收集负载信息,重新计算并分配权值。通过实验测试,对比不同算法下的负载均衡性能,改进后的算法能有效提高服务器集群的性能。     

一种基于网络地址转换的负载均衡算法

本文探讨集群服务器使用的负载均衡技术及负载分配的策略,并将网络地址转换应用于VOD集群,将负载分给多个服务器分担,以解决VOD集群服务器面临的大量并发访问造成的CPU或I/O的高负载问题。为了达到最佳的负载均衡效果,负载均衡器需要根据各个服务器的当前CPU和I/O状态来分配负载,这就需要动态监视服务器的负载,并应用优化的负载分配策略,达到平均分配负载的目的。     

协同虚拟环境中的主动动态负载平衡算法

在基于多服务器体系结构的协同虚拟环境中,用户的随意运动引起某些服务器负载过大而导致系统性能的下降。主动动态负载平衡算法定义了3个主动触发条件,当服务器计算代价过大或任务划分不当引起服务器之间通信量过大或服务器负载接近饱和时,将兴趣隶属度大的用户转移给邻域服务器管理,保证了对虚拟环境中的用户代理进行合理划分。试验数据显示,该方法在均衡各个服务器负载的前提下,可以提高系统的实时性和服务质量。     

Tulip: A New Hash Based Cooperative Web Caching Architecture

With the exponential growth of WWW traffic, web proxy caching becomes a critical technique for Internet web services. Well-organized proxy caching systems with multiple servers can greatly reduce the user perceived latency and decrease the network bandwidth consumption. Thus, many research papers focused on improving web caching performance with the efficient coordination algorithms among multiple servers. Hash based algorithm is the most widely used server coordination mechanism, however, there's still a lot of technical issues need to be addressed. In this paper, we propose a new hash based web caching architecture, Tulip. Tulip aggregates web objects that are likely to be accessed together into object clusters and uses object clusters as the primary access units. Tulip extends the locality-based algorithm in UCFS to hash based web proxy systems and proposes a simple algorithm to reduce the data grouping overhead. It takes into consideration the access speed dispatch between memory and disk and replaces expensive small disk I/O with less large ones. In case a client request cannot be fulfilled by the server in the memory, the system fetches the whole cluster which contains the required object into memory, the future requests for other objects in the same cluster can be satisfied directly from memory and slow disk I/Os are avoided. It also introduces a simple and efficient data dupllication algorithm, few maintenance work need to be done in case of server join/leave or server failure. Along with the local caching strategy, Tulip achieves better fault tolerance and load balance capability with the minimal cost. Our simulation results show Tulip has better performance than previous approaches.     

Adaptive Server Load Balancing in SDN Using PID Neural Network Controller

Web service applications are increasing tremendously in support of high-level businesses. There must be a need of better server load balancing mechanism for improving the performance of web services in business. Though many load balancing methods exist, there is still a need for sophisticated load balancing mechanism for not letting the clients to get frustrated. In this work, the server with minimum response time and the server having less traffic volume were selected for the aimed server to process the forthcoming requests. The Servers are probed with adaptive control of time with two thresholds L and U to indicate the status of server load in terms of response time difference as low, medium and high load by the load balancing application. Fetching the real time responses of entire servers in the server farm is a key component of this intelligent Load balancing system. Many Load Balancing schemes are based on the graded thresholds, because the exact information about the network flux is difficult to obtain. Using two thresholds L and U, it is possible to indicate the load on particular server as low, medium or high depending on the Maximum response time difference of the servers present in the server farm which is below L, between L and U or above U respectively. However, the existing works of load balancing in the server farm incorporate fixed time to measure real time response time, which in general are not optimal for all traffic conditions. Therefore, an algorithm based on Proportional Integration and Derivative neural network controller was designed with two thresholds for tuning the timing to probe the server for near optimal performance. The emulation results has shown a significant gain in the performance by tuning the threshold time. In addition to that, tuning algorithm is implemented in conjunction with Load Balancing scheme which does not tune the fixed time slots.     

Quantitative survivability evaluation of three virtual machine-based server architectures

Virtual machine-based services have become very popular in data centers and cloud computing in recent years. Efficient redundancy technology of virtual machine provides good availability for services; thus, it has become possible to provide continuous services even if the system suffers intrusions. So far, many intrusion tolerant server architectures have been developed based on virtual machine technology in academia and industry. Unfortunately, to the best of our knowledge, there is very little work done on evaluating the survivability of virtual machine-based server architectures in the literature.In this paper, we focus on analyzing and evaluating the survivability of three virtual machine-based architectures, which are load balance server architecture (LBSA), isolated component server architecture (ICSA), and Byzantine fault tolerant server architecture (BFTSA). As a reference, a traditional server cluster without virtual machines is also analyzed and compared. We model different architectures with Continuous Time Markov Chain (CTMC). We analyze the transient behaviors and steady states of different virtual machine-based architectures. Furthermore, the costs of the traditional server cluster and the virtual machine-based architectures are compared in terms of processing costs, memory costs, communication costs, and fail-safe fault tolerance. The results show that BFTSA has better survivability than LBSA and ICSA, but with longer time to reach the steady states and higher communication costs.