Dynamic Service Composition Orchestrated by Cognitive Agents in Mobile & Pervasive Computing
This addresses service composition challenges for mobile and pervasive computing systems, though it appears incremental as it builds on existing agent-based approaches.
The paper tackled the problem of automatic service composition in mobile and pervasive computing by developing a cognitively-inspired agent-based model focused on bounded rationality, which showed promising results compared to state-of-the-art models.
Automatic service composition in mobile and pervasive computing faces many challenges due to the complex nature of the environment. Common approaches address service composition from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints. Our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.