Resource Management in QOS Based Survivable Wireless Networks

Download or read book Resource Management in QOS Based Survivable Wireless Networks written by Bing Cao and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wireless networks have become crucial to provide mobile users with untethered communication services. Future generation wireless network has naturally evolved as a heterogeneous one, in which different wireless technologies compliment others to provide diverse Quality of Service (QoS). On one side, societal dependence on wireless services demands the survivability as a built-in design initiative. On the other side, resource management strategies are vital to efficiently utilize limited radio resources. This dissertation contributes to research on the resource management for QoS based survivable wireless networks. The main objective is to design adaptive resource schemes that can improve wireless survivability while satisfying QoS requirements. First a multi-layer wireless survivability framework is developed to encompass new features of Third-Generation (3G) cellular systems. Within this framework, adaptive resource management algorithms are utilized as the primary strategy to achieve Radio Network Subsystem (RNS) survivability. New capacity models and capacity utilization models are designed to support the survivability analysis of algorithms for managing the heterogeneous wireless resources of 3G systems. The resource management algorithms developed include an adaptive admission control algorithm with channel switching, QoS and priority. The results show that these adaptive algorithms outperform prior schemes especially in overload situations. The RNS survivability design is further extended to the hybrid wireless context for which different design strategies are studied. A novel utility based adaptive resource management scheme is proposed for the hybrid wireless networks to meet both survivability and QoS expectations. This is shown to achieve effective load balancing and failure tolerance in high traffic overload.