A Generic API for Load Balancing in Structured P2P Systems

International audienceReal world datasets are known to be highly skewed, often leading to an important load imbalance issue for distributed systems managing them. To address this issue, there exist almost as many load balancing strategies as there are different systems. When designing a scalable distributed system geared towards handling large amounts of information, it is often not so easy to anticipate which kind of strategy will be the most efficient to maintain adequate performance regarding response time, scalability and reliability at any time. Based on this observation, we describe the methodology behind the building of a generic API to implement and experiment any strategy independently from the rest of the code, prior to a definitive choice for instance. We then show how this API is compatible with famous existing systems and their load balancing scheme. We also present results from our own distributed system which targets the continuous storage of events structured according to the Semantic Web standards, further retrieved by interested parties. As such, our system constitutes a typical example of a Big Data environment

RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene