XLEngine: a cross-layer autonomic architecture with network wide knowledge for QoS support in wireless networks
Résumé
The provision of Quality of Service (QoS) over wireless networks has recently been the subject of intensive research. There is a growing consensus among the research community that combining cross-layering and autonomic paradigms is, until now, the best alternative for better QoS support in such networks. The cross-layer concept is recommended to over-come the performance problems of the wireless channel, and the autonomic concept is imposed as the size and complexity of networks grow. Most proposed cross-layer architectures lack of autonomicity. Moreover, the majority of them considers purely local information in their optimizations and do not care about the effects of such egoistic behavior on other wireless nodes. This non-collaborative behavior limits the overall system performance. We combine cross-layering and autonomic concepts in the design of a new architecture called XLEngine (Cross-Layer Engine) having the ability to make optimizations based on local and network wide knowledge. We implemented XLEngine under the simulator J-Sim. We show, through simulations, that our XLEngine architecture significantly outperforms the layered architecture.