A composite service is usually specified by means of a process model that captures control-flow and data-flow relations between activities that are bound to underlying component services. In mainstream service orchestration platforms, this process model is executed by a centralized orchestrator through which all interactions are channeled. This architecture is not optimal in terms of communication overhead and has the usual problems of a single point of failure. In previous work, we proposed a method for executing composite services in a decentralized manner. However, this and similar methods for decentralized composite service execution do not optimize the communication overhead between the services participating in the composition. This paper studies the problem of optimizing the selection of services assigned to activities in a decentralized composite service, both in terms of communication overhead and overall quality of service, and taking into account collocation and separation constraints that may exist between activities in the composite service. This optimization problem is formulated as a quadratic assignment problem. The paper puts forward a greedy algorithm to compute an initial solution as well as a tabu search heuristic to identify improved solutions. An experimental evaluation shows that the tabu search heuristic achieves significant improvements over the initial greedy solution. It is also shown that the greedy algorithm combined with the tabu search heuristic scale up to models of realistic size.

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