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Fifth IEEE International Conference on Cluster Computing (CLUSTER'03)
Towards an Efficient Cluster-Based E-Commerce Server
Hong Kong
December 01-December 04
ISBN: 0-7695-2066-9
Victoria Ungureanu, Rutgers University
Benjamin Melamed, Rutgers University
Michael Katehakis, Rutgers University

Cluster-based server architectures combine good performance and low cost, and are commonly used for applications that generate heavy loads. Essentially, a cluster-based server consists of a front-end dispatcher and several back-end servers. The dispatcher receives incoming requests, and then assigns them to back-end servers, which are responsible for request processing. The many benefits of cluster-based servers make them a good choice for e-commerce applications as well. However, applying this type of architecture to e-commerce applications is hindered by the fact that e-commerce clusters have the additional task of verifying that requests comply with contract terms. The problem is further complicated by the fact that contract terms may be expressed as functions of dynamic, mutable states.

The problem addressed in this paper is the effective assignment of e-commerce requests, such that the load is balanced among back-end servers and request validation is efficient. To this end, we propose a policy called TDA (Type Dependent Assignment), which takes account of the type of contracts. Under TDA, stateless contracts are replicated on all back-end servers. In contrast, a stateful contract, C, is preassigned to a designated back-end server, called the base of C, which is responsible for maintaining the state of C. The operation of TDA may be broadly outlined as follows. A request governed by a stateless contract is assigned to the least loaded server. In contrast, a request governed by a stateful contract is assigned to its base, if the base is not overloaded, and to the least loaded server, otherwise.

Citation:
Victoria Ungureanu, Benjamin Melamed, Michael Katehakis, "Towards an Efficient Cluster-Based E-Commerce Server," cluster, pp.474, Fifth IEEE International Conference on Cluster Computing (CLUSTER'03), 2003
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