QoS-aware Automatic Service Composition Based on Service Execution Timeline with Multi-objective Optimization

With the evolution of web technologies, various services become available in the pervasive network environment. Combining atomic services via the input and output dependency according to functional requirements with the multiple nonfunctional Quality-of-Service (QoS) guarantees has become a widely considered optimization problem. The conventional multi-objective service composition relying on manually predefined service chains fails to ensure global optimality. Although the automatic service composition successfully expands the search space, the searching graph which it relies on causes computationally expensive and fails to handle multiple objectives. Therefore, this paper proposes a novel efficient multi-objective automatic service composition approach. Particularly, it introduces a service execution timeline model to decompose the composition problem into several sub-problems to reduce computational complexity. Further, it employs an evolutionary process to explore the search space and determine the approximately Pareto front of the composition solutions. The experimental results on the benchmarks show that our approach could achieve a better trade-off between the computation cost and ensuring a better QoS compared with two recently proposed automatic composition approaches.