International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.2, No.1, March 2011 DOI : 10.5121/ijasuc.2011.2114 169                Carlos E. Otero 1 , Ivica Kostanic 2 , Luis D. Otero 3 , Scott L. Meredith 2 , Matthew Whitt 1 1 Department of Mathematics and Computer Science, University of Virginia's College at Wise, Wise, Virginia cotero@mcs.uvawise.edu; mrw3g@uvawise.edu 2 Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, FL kostanic@fit.edu; smeredit@my.fit.edu 3 Department of Engineering Systems, Florida Institute of Technology, Melbourne, FL lotero@fit.edu ABSTRACT Due to reliance on stochastic deployment, delivery of large-scale WSN presents a major problem in the application of Wireless Sensor Networks (WSN) technology. When deployed in a stochastic manner, the WSN has the utmost challenge of guaranteeing acceptable operational efficiency upon deployment. This paper presents a methodology for stochastic deployment of WSN. The methodology uses simulation, statistical analysis, and the Analytical Hierarchy Process to provide an approach that helps decision- makers determine the best deployment strategies among competing alternatives. The methodology can be used to simplify the decision-making process and provide decision-makers the ability to consider all factors involved in the WSN deployment problem. The methodology is extensible and can be easily customized to include numerous quality factors to further compare deployment strategies and identify the one that best meet applications requirements. KEYWORDS Wireless Sensor Networks, Stochastic Deployments, Statistical Analysis, Analytical Hierarchy Process 1. Introduction Recent advances in micro electro-mechanical systems (MEMS) have led to the development of tiny low- power devices that are capable of sensing the world and communicating with each other. Such devices may be deployed in vast numbers over large geographical areas to form wireless sensor networks (WSN). WSN provide the means for autonomous monitoring of physical events in areas where human presence is not desirable or impossible. Therefore, they are expected to facilitate many existing applications and bring into existence entirely new ones. A few proposed applications of WSN include disaster relief, environmental control, military applications, and border security [1]. In each application, the sensor nodes are deployed over the area of interest and tasked with sensing the environment and communicating with each other. In multi-hop fashion, they transmit the information back to a base station, also known as the information sink [2]. From the sink, the information is collected and typically relayed to a central location, across remote sites, where it is processed and analyzed.