Masters Theses
Abstract
"Wireless Sensor Network (WSN) is a class of ad hoc networks that has capability of self-organizing, in-network data processing, and unattended environment monitoring. Sensor-cloud is a cloud of heterogeneous WSNs. It is attractive as it can change the computation paradigm of wireless sensor networks. In Sensor-Cloud, to gain profit from underutilized WSNs, multiple WSN owners collaborate to provide a cloud service. Sensor Cloud users can simply rent the sensing services which eliminates the cost of ownership, enabling the usage of large scale sensor networks become affordable. The nature of Sensor-Cloud enables resource sharing and allows virtual sensors to be scaled up or down. It abstracts different platforms hence giving the impression of a homogeneous network. Further in multi-application environment, users of different applications may require data based on different needs. Hence scheduling scheme in WSNs is required which serves maximum users of various applications. We have proposed a scheduling scheme suitable for the multiple applications in Sensor Cloud. Scheduling scheme is based on TDMA which considers fine granularity of tasks. The performance evaluation shows the better response time, throughput and overall energy consumption as compared to the base case we developed. On the other hand, to minimize the energy consumption in WSN, we design an allocation scheme. In Sensor Cloud, we consider sparsely and densely deployed WSNs working together. Also, in a WSN there might be sparsely and densely deployed zones. Based on spatial correlation and with the help of Voronoi diagram, we turn on minimum number of sensors hence increasing WSN lifetime and covering almost 100 percent area. The performance evaluation of allocation scheme shows energy efficiency by selecting fewer nodes in comparison to other work"--Abstract, page iv.
Advisor(s)
Madria, Sanjay Kumar
Committee Member(s)
Chellappan, Sriram
Zawodniok, Maciej Jan, 1975-
Department(s)
Computer Science
Degree Name
M.S. in Computer Science
Publisher
Missouri University of Science and Technology
Publication Date
Fall 2014
Pagination
xii, 82 pages
Note about bibliography
Includes bibliographical references (pages 80-81).
Rights
© 2014 Rashmi Dalvi, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Subject Headings
Sensor networksWireless sensor networks -- DesignComputer networks -- Energy conservationEnergy consumption
Thesis Number
T 10578
Electronic OCLC #
902730819
Recommended Citation
Dalvi, Rashmi, "Energy efficient scheduling and allocation of tasks in sensor cloud" (2014). Masters Theses. 7324.
https://scholarsmine.mst.edu/masters_theses/7324