Title

A proactive management algorithm for self healing mobile ad hoc networks

Date of Award

2007

Availability

Article

Degree Name

Doctor of Philosophy (Ph.D.)

Department

Electrical and Computer Engineering

First Committee Member

Akmal A. Younis, Committee Chair

Abstract

The ability to proactively manage mobile ad-hoc network (MANET) devices is critical for supporting complex services such as quality of service (QoS), security and access control in these networks. This research focuses on the problem of managing high dynamic and resource constrained MANET environments through the introduction of a novel Proactive Management Algorithm (PMA) for self healing MANETs. PMA is based on the effective integration of autonomous, predictive and adaptive distributed management strategies. Proactive management is achieved through the distributed analysis of the current performance of the mobile nodes utilizing an optimistic discrete event simulation method, which is used to predict the mobile nodes' future status and execute a proactive fault tolerant management scheme. PMA takes advantage of distributed parallel processing, flexibility and intelligence of active packets to minimize the management overhead, while adapting to the highly dynamic and resource-constrained nature of MANETs.The performance of the proposed PMA is validated using analytical performance analysis and simulation based on Active Virtual Network Management Protocol. The simulation results demonstrate that PMA not only significantly reduces management control overhead but also substantially improves both the performance and the stability under highly dynamic and limited resource conditions, which are typical for military, disaster relief and civilian applications in MANET environments.

Keywords

Engineering, Electronics and Electrical; Engineering, System Science

Link to Full Text

http://access.library.miami.edu/login?url=http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3267701