Predictive Mobility Management Using Optimized Delays And Security Enhancements In IEEE 802.11 Infrastructure Networks

• Main Author: Biju, Issac
• Format: Thesis
• Language: English
• Published: Universiti Malaysia Sarawak (UNIMAS) 2008
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://ir.unimas.my/id/eprint/26832/1/Biju%20Issac%20ft.pdf; http://ir.unimas.my/id/eprint/26832/

The IEEE 802.11 wireless local area networks (also called WLAN) is very popular nowadays, and many public places have WLAN installations, for example in airports, coffee houses, shopping malls and customer service centres. Though a good data rate of 54 Mbps is offered by 802.11 g standard, there are indeed issues to tackle in relation to mobility and security. Our research focus is to improve the mobility management and security aspect of IEEE 802.11 infrastructure networks. Dealing with the mobility management and dealing with the security enhancement form the first and second part of the thesis respectively. In the first part, performance analysis of the current IEEE 802.11 network standards was initially done. Under the current technology, when a mobile node moves from one access point to another, the handoff is not always smooth and connection may be dropped as a result. The reason for that is inherent in the mobility design problems of the existing implementations. For handoff to be smooth, the cumulative handoff delay should be around 50 msec or lesser for voice related applications. However, currently the handoff delay is of the order of several hundred milliseconds. This is contributed by delays such as - scan or probe delay, authentication delay and reassociation delay. Our contribution to mobility management is to propose a mobility prediction algorithm using location tracking and data mining, to propose a delay management approach that cuts down major delays, and to propose a two stage resource reservation scheme. Location tracking without the use of GPS (Global Positioning System) works by using a centralized server that helps to locate the current location of the mobile node within a restricted area, based on the Received Signal Strength Indicator (RSSI) value that the mobile node receives from the neighbouring access points. The circular region around an access point is divided into four regions, which is a key concept and the central server knows the region and association of the mobile node.