Wireless broadband has become an essential technique in our current daily life. By connecting to a wireless access point or base station, people are able to access the Internet anytime, anywhere. The Internet today is a medium imbued with various online applications, such as business transactions, public services, entertainments, remote educations, etc., each possessing different quality of service (QoS) requirements. Consequently, resource management will become an increasingly important component of the service-oriented next generation Internet architecture in which the QoS-oriented MAC layer protocol design, the admission control, the load balancing and the package scheduling will be more targeted. How to provide better solutions for resource management emerges as a major issue.
In this dissertation, we take on two important issues in resource management of wireless networks. In the first part, we address queue management and packet scheduling in multi-radio multi-channel mesh networks and present a utility-based algorithm that assigns and schedules each incoming packet based on the utility value estimated by considering the corresponding flows QoS requirements and status. The utility value of each packet is dynamically adjusted using Reinforcement Learning. We analyze the performance of our algorithm using a discrete-event simulator. Simulation results show that our algorithm outperforms prior known algorithms. We then show that the problem of finding a schedule that maximizes the system throughout is NP-Complete for tree networks when channel switching overhead is considered even though the equivalent problem can be solved in a polynomial time when switching overhead is ignored.
In the second part, we address access control in internetworking systems. Two internetworking models are considered. Firstly, we provide a utility-based access control framework for an integrated UMTS/WLAN dual system in which mobile stations make their own handover decisions. The performance of our technique is analyzed using OPNET simulator. Simulation results show that stable load balancing is achieved by a well-defined utility function. Secondly, we consider infra-structured Wi-Fi networks and address dynamic access point selection. Our system model considers the penalty for users switching access points to access better transmission rates. We present an optimal offline dynamic programming algorithm and a 4-competitive online algorithm for a single user with multiple access points. For multiple users with multiple access points, we prove the NP-completeness of a model with bandwidth-constrained access points and present a 4- competitive online algorithm for a model with a constrained number of users allowed at each access point. Finally, our online algorithm is implemented with a varied parameter used in switching decisions. Results show that an optimal value of the decision parameter can be obtained based on the transmission rate changes in the current and available access points.
The contributions of this dissertation research are two-fold. Firstly, we lay out a framework for QoS-enabling queue management and scheduling techniques in multi-radio multi-channel mesh networks. Secondly, we present fundamental results for the problem of access point switching decisions in infra-structured Wi-Fi networks.
|Commitee:||Cheng, Xiuzhen, Gomes, Joseph, Subramaniam, Suresh, Youssef, Abdou|
|School:||The George Washington University|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 72/02, Dissertation Abstracts International|
|Keywords:||Queue management, Resource management, Scheduling, Wireless networks|
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