Abstract

Automatic planning, with dynamic binding and adaptive composition recovery, has been used to tackle complex service provisioning in mobile environments, but given frequent network topology changes, and services with time-dependent QoS, finding composites that can functionally and non-functionally satisfy a user's request remains difficult. Many service composition mechanisms either require a centralised perspective of the environment, or use optimisation mechanisms that trade off computational efficiency for optimality. Stigmergy-based approaches have been used to model decentralised service interactions between service providers, using a community of mobile software agents that share the same goal to approximate the set of QoS-optimal service compositions. Inspired by this model, this article addresses computational efficiency concerns using a collaborative approach to engage multiple communities of agents for provisioning QoS-optimal service compositions in mobile environments. New compositions can emerge from local decisions and interactions with agents from diverse communities. We assess whether having multiple communities improves the diversity and optimality of solutions. We also measure the proposed approach’ efficiency in dealing with incomplete information. The results show that the proposed approach trades optimality for a more diverse set of solutions, at a cost of higher overhead.

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