An experimental evaluation of a peer-model monitoring system for the support of a parallel processing environment

Abstract

The process of monitoring the machines or computing nodes in a network, and of monitoring the communication traffic between them, is very important to efficiently launch and execute parallel coarse-grained applications or even classical (serial-type) applications, taking advantage of machines in the network that are not heavily used. An experimental software system, named MONSYS, that is capable of monitoring the machines in a network, is presented. MONSYS can be used in the support of an Application Manager system capable of distributing parallel tasks (or classical programs) over the machines in a local area network with the objective of achieving load balancing. It can also be used as a tool in the administration of networks. MONSYS exhibits a highly decentralized and fault tolerant architecture based on the Peer-Model, which, together with its information diffusion algorithms, constitute its prime novelty. A set of experiments that investigate the performance and scalability of a prototype of MONSYS is presented and discussed. The experiments reported show that MONSYS offers a reasonably accurate picture of the internal state of the machines monitored, without being a burden to the network communication channels or to the machines themselves. In fact, the quantitative results obtained indicate that MONSYS can be several times more performant than an equivalent system using a multicast communication scheme for the exchange of machine state information.