Affiliation:
1. Computing Laboratory, University of Oxford,
2. School of Industrial and Systems Engineering, Georgia Institute of Technology,
Abstract
Internet centers host services for e-banks, e-auctions and other clients. Hosting centers then must allocate servers among clients to maximize revenue. The limited number of servers, costs of reallocating servers, and unpredictability of requests make server allocation optimization difficult Based on the many similarities between server and honey bee colony forager allocation, we pro pose a new decentralized honey bee algorithm which dynamically allocates servers to satisfy request loads. We compare it against an omniscient optimality algorithm, a conventional greedy algorithm, and an algorithm that computes omnisciently the optimal static allocation. We evaluate performance on simulated request streams and commercial trace data Our algorithm performs better than static or greedy for highly variable request loads, but greedy can outperform it under low variability. Honey bee forager allocation, though suboptimal for static food sources, may possess a counterbalancing responsiveness to food source variability.
Subject
Behavioral Neuroscience,Experimental and Cognitive Psychology
Cited by
172 articles.
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