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

A Survey of Fault-Tolerance and Fault-Recovery Techniques in Parallel Systems

Supercomputing systems today often come in the form of large numbers of commodity systems linked together into a computing cluster. These systems, like any distributed system, can have large numbers of independent hardware components cooperating or collaborating on a computation. Unfortunately, any of this vast number of components can fail at any time, resulting in potentially erroneous output. In order to improve the robustness of supercomputing applications in the presence of failures, many techniques have been developed to provide resilience to these kinds of system faults. This survey provides an overview of these various fault-tolerance techniques.Comment: 11 page

Scalable Persistent Storage for Erlang

The many core revolution makes scalability a key property. The RELEASE project aims to improve the scalability of Erlang on emergent commodity architectures with 100,000 cores. Such architectures require scalable and available persistent storage on up to 100 hosts. We enumerate the requirements for scalable and available persistent storage, and evaluate four popular Erlang DBMSs against these requirements. This analysis shows that Mnesia and CouchDB are not suitable persistent storage at our target scale, but Dynamo-like NoSQL DataBase Management Systems (DBMSs) such as Cassandra and Riak potentially are. We investigate the current scalability limits of the Riak 1.1.1 NoSQL DBMS in practice on a 100-node cluster. We establish for the first time scientifically the scalability limit of Riak as 60 nodes on the Kalkyl cluster, thereby confirming developer folklore. We show that resources like memory, disk, and network do not limit the scalability of Riak. By instrumenting Erlang/OTP and Riak libraries we identify a specific Riak functionality that limits scalability. We outline how later releases of Riak are refactored to eliminate the scalability bottlenecks. We conclude that Dynamo-style NoSQL DBMSs provide scalable and available persistent storage for Erlang in general, and for our RELEASE target architecture in particular