Combining high performance and fault tolerance in a distributed file server

Among the most reliable and fault tolerant components in a distributed system are storage systems. Obviously, reliability of storage systems belongs to the most researched issues in distributed computing. Every distributed file system project is based on different assumptions about size, load, amount of sharing, and desirable semantics, making it hard to compare research results fairly. The current Amoeba file server is the Bullet File Server [van Renesse, Tanenbaum, and Wilschut, 1989] which provides immutable files, is optimized for whole-file transfer and does caching at the file server. It has excellent performance for reading cached files (1.5 + 1.5 n ms for n kilobytes) and for sustained file I/O (680 kilobytes per second, both on read and write). Although performance is excellent, there is room for improvement, especially in the area of fault tolerance, sharing semantics and caching. I am currently doing the back-of-the-envelope design for a new file server that will form the basis of both our normal file system and of a complex-object server which is being designed by the database group at CWI. In addition to those desirable properties of fault tolerance, persistency, consistency, and availability, I am anxious to achieve even better performance than the Bullet server by extensive use of client and server caching.This position paper presents some of our design ideas. Note that this is work in progress; that

A Highly Available Cluster of Web Servers with Increased Storage Capacity

Ponencias de las Decimoséptimas Jornadas de Paralelismo de la Universidad de Castilla-La Mancha celebradas el 18,19 y 20 de septiembre de 2006 en AlbaceteWeb servers scalability has been traditionally solved by improving software elements or increasing hardware resources of the server machine. Another approach has been the usage of distributed architectures. In such architectures, usually, file al- location strategy has been either full replication or full distribution. In previous works we have showed that partial replication offers a good balance between storage capacity and reliability. It offers much higher storage capacity while reliability may be kept at an equivalent level of that from fully replicated solutions. In this paper we present the architectural details of Web cluster solutions adapted to partial replication. We also show that partial replication does not imply a penalty in performance over classical fully replicated architectures. For evaluation purposes we have used a simulation model under the OMNeT++ framework and we use mean service time as a performance comparison metric.Publicad

Distributed multimedia systems

Multimedia systems will allow professionals worldwide to collaborate more effectively and to travel substantially less. But for multimedia systems to be effective, a good systems infrastructure is essential. In particular, support is needed for global and consistent sharing of information, for long-distance, high-bandwidth multimedia interpersonal communication, greatly enhanced reliability and availability, and security. These systems will also need to be easily usable by lay computer users. \ud In this paper we explore the operating system support that these multimedia systems must have in order to do the job properly

Parallel detrended fluctuation analysis for fast event detection on massive PMU data

("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment