Abstract
Cloud services are often distributed across several data centers requiring new scalable approaches to efficiently perform searching to reduce the energy and price cost of fulfilling requests. Multiagent-based systems have arisen as a powerful technique for improving distributed processing on a wide scale, which can operate in environments where partial observability is the norm and the cost of prolonged search can be exponential. In this paper, we present a multiagent-based service composition approach, using agent-matchmakers and agent-representatives, for the efficient retrieval of distributed services and propagation of information within the agent network to reduce the amount of brute-force search. Our extensive simulation results indicate that by introducing localized agent-based memory searches, the amount of actions (with their associated energy costs) can be reduced by over 50 percent which results in a lower energy cost per composition request.
Original language | English |
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Pages (from-to) | 358 - 369 |
Number of pages | 11 |
Journal | IEEE Transactions on Sustainable Computing |
Volume | 6 |
Issue number | 3 |
DOIs | |
Publication status | Published - 18 Nov 2018 |