Papers by Yasser Almoghathawi
As demands are growing and networks are becoming more complex every day, the cost and consequence... more As demands are growing and networks are becoming more complex every day, the cost and consequences of even a small disruption in the network is going to be huge. Analyzing and prioritizing edges for the recovery of the complete network is essential for a successful continuity of business operation. Measuring the importance of network components is of significant value in prioritizing improvement efforts and planning recoverability. Prioritizing transportation network components for recovery based on topology based and flow based importance measures (IMs) will be useful for decision makers. In this project, we aim to create a multi-criteria decision making (MCDM) tool, i.e., PROMETHEE , to analyze and prioritize transportation network components for recovery based on multiple IMs: all pairs max flow edge count, min cutset count, edge flow centrality, flow capacity rate and damage impact, betweenness centrality, and information centrality. The proposed approach is validated through simulation and illustrated with an example. Also, a sensitivity analysis has been carried out for the proposed approach. Conclusion remarks are presented with some suggested future work too.
Wireless Networks, 2014
ABSTRACT In this paper, we study the problem of base stations location and configuration. Antenna... more ABSTRACT In this paper, we study the problem of base stations location and configuration. Antenna configuration includes number of antennas installed at the base station, the azimuth of each base station, the tilt, height, and transmitted power for each antenna for cellular mobile networks. Towards this end, a mathematical model is formulated using integer programming (IP).The objective of the model is to minimize the cost of the network. The model guarantees that each demand point is covered. A demand point represents a cluster of uniformly distributed multiple users. In addition, the signal-to-interference-plus-noise ratio at each demand point is set at a given threshold value. A none-line-of-site situation is considered while calculating the path loss using COST-231-Walfisch-Ikegami propagation model. To illustrate the capability of the formulated IP model, we use a discretized map of some area with demand points. The IP model is solved using a commercial software, LINGO 12. Possible future research directions are stated in the conclusion.
Advanced Materials Research, 2012
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Papers by Yasser Almoghathawi