Managing Distributed Memory to Meet Multiclass Workload Response Time Goals

In this paper we present an online method for managing a goal-oriented buffer partitioning in the distributed memory of a network of workstations. Our algorithm implements a feedback mechanism which dynamically changes the sizes of dedicated buffer areas and thereby the buffer hit rate for the different classes in such a way that user-specified response time goals are satisfied. The aggregated size of the buffer memory across all network nodes remains constant and only the partitioning is changed. The algorithm is based on efficiently approximating the trajectory of the per-class response time curves as a function of the available buffer. Changes in the workload that would lead to violation of response time goals are counteracted by accordingly adjusting the buffer allocation. For local replacement decisions, we integrate a cost-based buffer replacement algorithm to fit into our goal-oriented approach. We have implemented our algorithm in a detailed simulation prototype and we present first results obtained from this prototype.

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In  15th International Conference on Data Engineering

Publisher  IEEE Computer Society
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