Abstract
This paper proposes to employ linear programming algorithms for global resource scheduling to reduce the extra cost for power consumption and operation expenditures, for remote resource access in a cloud-based resource pool with concrete restraints of the networking environment. The scheduler adapts the problem modeling granularity and solution which corresponds to the differential demands of the various stages of a continual process for the initial construction and subsequent operation of a cloud-based resource pool. In particular, the proposed algorithms takes into account resource configuration, service deployment and real-time load, among other factors, to strike a tradeoff among the scheduling performance, response time and computation cost. Different environment modeling methods are provided according to the specific location of networking resource bottleneck. A simple greedy algorithm is provided for a small-scale pool with abundant networking resources.
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Deng, L., Yu, Q., Peng, J. (2011). Adaptive Optimal Global Resource Scheduling for a Cloud-Based Virtualized Resource Pool. In: Park, J.J., Lopez, J., Yeo, SS., Shon, T., Taniar, D. (eds) Secure and Trust Computing, Data Management and Applications. STA 2011. Communications in Computer and Information Science, vol 186. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22339-6_28
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DOI: https://doi.org/10.1007/978-3-642-22339-6_28
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