00000ctm a22000004a 4500 UP-99796217610949819 Buklod 20230215105418.0 m |o d | ta 130920s xx d r |||| u| (iLib)UPD-00205806052 DENGII rda eng DMLUC LG 996 2013 E643 M33 Macabale, Nemesio Jr.,A. author. CLAW channel load aware routing metric for wireless mesh networks Nemesio A. Macabale Jr. Quezon City College of Engineering, University of the Philippines Diliman 2013. xviii, 127 leaves illustrations 28 cm text rdacontent unmediated rdamedia volume rdacarrier Thesis (Ph.D. Electrical Engineering)--University of the Philippines, Diliman. Despite advances in the field, many research challenges remain in optimally routing traffic within a wireless mesh network. Due to the shared nature of the wireless channel, routing based on metrics traditionally used in wired networks such as hop counts do not take into account load, interference and ocntention within the channel shared among neighboring mesh nodes. As a result, routing algorithms that use such "load-agnostic" metrics tend to direct multiple traffic flows naively along known best paths, eventually congesting wireless channels along path and causing significant drops in network throughput. To address this issue, we designed a new channel-load aware routing metric called CLAW that takes into consideration traffic load, contention and interference within the channel. In contrast with other load aware routing metrics that need to collect region-wide information to assess region-wide channel load, the CLAW routing metric is based on node-local information and simple computation. It uses available functions from a wireless node's MAC layer to monitor the state of the MAC and physical layers. Consequently, CLAW provides accurate estimates of channel busyness and contention as fractions of time, simplifying computations. Although CLAW is designed to replace hop count routing metrics, during the course of our investigation we found that directly replacing a hop count routing metric with a load-aware one would not immediately improve performance. This is due to the fact that the load estimates used to choose routes are themselves affected by the route choices with feedback effects that cause routing oscillation and instability. To handle these issues, CLAW treats the routing process in a manner analogous to a control system with a feedback control. By addressing these issues, CLAW significantly improves network performance in both throughput and delay against hop count and other competing load-aware routing metrics found in the literature. Wireless communication systems. Routing (Computer network management). Wireless mesh networks. Routing metric. Congestion awareness. Thesis FI UP UPD DARCHIVES LG 996 2013 E643 M33 UPD DENG-II LG 996 2013 E643 M33 Thesis