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<p><b>Abstract</b>—Many distributed systems must be scalable, meaning that they must be economically deployable in a wide range of sizes and configurations. This paper presents a scalability metric based on cost-effectiveness, where the effectiveness is a function of the system's throughput and its quality of service. It is part of a framework which also includes a <it>scaling strategy</it> for introducing changes as a function of a <it>scale factor</it>, and an <it>automated virtual design optimization</it> at each scale factor. This is an adaptation of concepts for scalability measures in parallel computing. Scalability is measured by the range of scale factors that give a satisfactory value of the metric, and good scalability is a joint property of the initial design and the scaling strategy. The results give insight into the scaling capacity of the designs, and into how to improve the design. A rapid simple bound on the metric is also described.</p><p>The metric is demonstrated in this work by applying it to some well-known idealized systems, and to real prototypes of communications software.</p>
Scalability, distributed systems, scalability metric, software performance, performance model, layered queuing, performance optimization, replication.
Murray Woodside, Prasad Jogalekar, "Evaluating the Scalability of Distributed Systems", IEEE Transactions on Parallel & Distributed Systems, vol. 11, no. , pp. 589-603, June 2000, doi:10.1109/71.862209
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