Maximizing Service Coverage of Adaptive Services in Wireless Mobile Ad-Hoc Networks using Non-Clustering Approach

non-clustering;ad-hoc;mobile;wireless

Thangavelu, Krithiga ; Dr. Douglas S. Reeves, Committee Chair,Dr. Munindar P.Singh, Committee Member,Dr. Gregory T. Byrd, Committee Member,Thangavelu, Krithiga ; Dr. Douglas S. Reeves ; Committee Chair ; Dr. Munindar P.Singh ; Committee Member ; Dr. Gregory T. Byrd ; Committee Member

University:North Carolina State University

关键词: non-clustering;    ad-hoc;    mobile;    wireless;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/1930/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

Wireless Mobile Ad-hoc Networks are characterized by dynamic network topology and lack of network infrastructure. The network fragments into smaller networks and merges over a period of time due to mobility. This makes provisioning solutions to common network problems, like routing and QoS provisioning, a challenging task.Services in ad-hoc networks face two-fold problems. Making nodes aware of the availability and the location of services in a dynamically changing network is difficult, especially when such services are not tightly coupled with a fixedinfrastructure. Servers may come and leave the network. Nodes may shutdown services to conserve energy. The problem is further exacerbated by the limitations posed by the wireless network on the bandwidth and by the limited computational capability of the wireless devices. This thesis addresses the problem of providing continuous and guaranteed access to such centralized services in a mobile wireless ad-hoc network.A distributed algorithm based on the exchange of service provider information is proposed to solve the problem. The previous work addressing the same problem assumes that the nodes move in long-term groups. Our solution does not make thisassumption and targets arbitrary motion. So, no attempt is made to correlate the movement of the nodes, in order to solve the problem. In this thesis, we illustrate that our approach achieves higher service availability than the previous methods at the cost of a higher number of service instances.The proposed algorithm converges after a time period equivalent to the average propagation delay of the service instance information from a service provider to its reachable nodes. The computational and communication complexity of the algorithm is theoretically proved to be O(slogn) and O(n[subscript g]²) where s is the number of service instances, n is the number of nodes in the ad-hoc network and n[subscript g] is the average number of nodes in a connected component of the graph formed by the nodes in the ad-hoc network.The service cost incurred in providing the necessary service coverage is proved through simulation to be in the order of the number of connected components in the graph formed by the nodes in the ad-hoc network.Simulation results are used to prove that the algorithm provides for maximum service coverage independent of the mobility pattern of thenodes in the ad-hoc network.