Linear programming and network flows (2nd ed.)
Linear programming and network flows (2nd ed.)
IBM Journal of Research and Development
A grid service broker for scheduling distributed data-oriented applications on global grids
MGC '04 Proceedings of the 2nd workshop on Middleware for grid computing
Balancing Risk and Reward in a Market-Based Task Service
HPDC '04 Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing
Profitable services in an uncertain world
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
A taxonomy of market-based resource management systems for utility-driven cluster computing
Software—Practice & Experience
Multiagent and Grid Systems - Smart Grid Technologies & Market Models
Tycoon: An implementation of a distributed, market-based resource allocation system
Multiagent and Grid Systems
Mirage: a microeconomic resource allocation system for sensornet testbeds
EmNets '05 Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors
A simple local-control approximation algorithm for multicommodity flow
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
Distributed resource allocation in stream processing systems
DISC'06 Proceedings of the 20th international conference on Distributed Computing
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In this paper we consider the problem of maximising utility in linked market-driven distributed and Grid systems. In such systems, users submit jobs through brokers who can virtualise and make available the resources of multiple service providers, achieving greater economies of scale, improving throughput and potentially reducing cost. Customers compete against each other by assigning a utility value or function to the successful processing of their jobs in an effort to have them prioritised in the face of contested and constrained resources. Brokers and service providers also attempt to maximise the utility they gain, choosing to process jobs that will earn them the highest profit with respect to the resources required. For this to be effective over many linked computing marketplaces highly distributed resource allocation is needed, where each participant can operate independently using only local information, and ideally reach a global state where all participants are satisfied. We model such a system by adapting the classical multi-commodity flow problem to the market-based, utility driven distributed systems, where all participants selfishly attempt to maximise their own gain. We then obtain a utility-aware distributed algorithm that generates increased utility for participants in such systems, especially under scenarios of high contention.