Supercomputing out of recycled garbage: preliminary experience with Piranha
ICS '92 Proceedings of the 6th international conference on Supercomputing
Windows NT SNMP
ATLAS: an infrastructure for global computing
EW 7 Proceedings of the 7th workshop on ACM SIGOPS European workshop: Systems support for worldwide applications
ParaWeb: towards world-wide supercomputing
EW 7 Proceedings of the 7th workshop on ACM SIGOPS European workshop: Systems support for worldwide applications
JavaSpaces Principles, Patterns, and Practice
JavaSpaces Principles, Patterns, and Practice
Core JINI
Adaptive Parallelism and Piranha
Computer
On Properties of Game Theoretical Approaches to Balance Load Distribution in Mobile Grids
IWSOS '08 Proceedings of the 3rd International Workshop on Self-Organizing Systems
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Heterogeneous networked clusters are being increasingly used as platforms for resource-intensive parallel and distributed applications. The fundamental underlying idea is to provide large amounts of processing capacity over extended periods of time by harnessing the idle and available resources on the network in an opportunistic manner. In this paper we present the design, implementation and evaluation of a framework that uses JavaSpaces to support this type of opportunistic adaptive parallel/distributed computing over networked clusters in a non-intrusive manner. The framework targets applications exhibiting coarse-grained parallelism and has three key features: (1) portability across heterogeneous platforms, (2) minimal configuration overheads for participating nodes, and (3) automated system state monitoring (using SNMP) to ensure non-intrusive behavior. Experimental results presented in this paper demonstrate that for applications exhibiting coarse grained parallelism, the opportunistic parallel computing framework can provide performance gains. Furthermore, the results indicate that monitoring and reacting to current system state minimizes intrusiveness.