​You are cordially invited by the COE Dept., to attend a Guest Seminar, on the above given title, by Mr. Abdullah Al-Fadhly, Full-Time PhD Student (ICS), on Tuesday, May 14th, 2013, at 09:30 A.M., in Building 22, Room 105.​

Abstract: Wireless sensor and actor networks (WSANs) have emerged recently in many Mission Critical Applications (MCA) such as military surveillance, research and rescue, and fire extinguishing, etc. These type of applications need to be deployed on robustness networks that can handle node failures in real time manner.  However, WSAN usually operate in harsh environment and thus become susceptible to breakage in connectivity due to the failure of one or multiple actor nodes. Given that WSANS are deployed in remote areas, restoring connectivity through self-reconfiguring the network topology becomes the most preferred solution. In this PhD dissertation, we investigate the requirements of Critical Mission Wireless Sensor and Actor Networks in terms of robustness and connectivity and provide analytically and by simulation central and distributed approaches to handle single and multiple node failures.  The central approach is based on Integer Linear Programming (ILP) formulation and uses traveled distance as its objective function. While minimizing the total traveled distance is the main goal of the ILP approach, other performance metrics are constrained such as the loss of coverage and the maximum traveled distance by a node. Since applying a central approach is not feasible in WSAN, we developed distributed approaches that depend on local information, and provide a restoration mechanism that can handle single and multiple node failures with minimized cost. Our first distributed approach is called Least Distance Movement Recovery approach (LDMR) which exploits non-critical nodes in the network in order to replace failed nodes. It has been enhanced to behave adaptively based on the network topology in order to achieve better performance in sparse and dense networks. The new adaptive approach which is based on LDMR is called Adaptive Connectivity Restoration Algorithm (ACRA). To restore network connectivity in case of multiple simultaneous failures, we developed a new approach called Simultaneous Failures Recovery Approach (SFRA). SFRA depends on constructing a recovery tree from the original network starting from a pre-assigned root. We show the effeteness and correctness of our approaches analytically and by extensive simulations.

Dr. M. El-Shafie, Professor, SE Department, is his thesis advisor.​