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Adaptive Quality of Service and Trust Based Lightweight Secure Routing Algorithm for Dense Wireless Sensor Networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Adaptive Quality of Service and Trust Based Lightweight Secure Routing Algorithm for Dense Wireless Sensor Networks./
作者:	Pathak, Aditya Kalpesh.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	109 p.
附註:	Source: Masters Abstracts International, Volume: 83-06.
Contained By:	Masters Abstracts International83-06.
標題:	Cryptography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28859613
ISBN:	9798759930662

Adaptive Quality of Service and Trust Based Lightweight Secure Routing Algorithm for Dense Wireless Sensor Networks.
Pathak, Aditya Kalpesh.

Adaptive Quality of Service and Trust Based Lightweight Secure Routing Algorithm for Dense Wireless Sensor Networks. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 109 p.

Source: Masters Abstracts International, Volume: 83-06.

Thesis (M.Appl.Sc.)--The University of Regina (Canada), 2021.

This item must not be sold to any third party vendors.

Wireless Sensor Networks (WSNs) are group of wireless devices that are deployedin an adhoc manner and are generally left unattended. The main advantages of WSNsare that they are simple to use, allow the use of inexpensive sensor nodes, and havegood scalability. WSNs are useful in object tracking, periodic monitoring, and eventdetection applications. However, the inherent characteristics of the WSNs, such aslimited resources and low computation, make them vulnerable to various types of securityattacks. Therefore, security mechanisms are needed to secure the network andprotect against various security attacks. Conventional security mechanisms, such ascryptography (encryption/decryption) and authentication based systems, are generallyused to ensure the security of traditional networks. However, due to the resourceconstrained nature of WSNs, conventional security mechanisms can be too resourceheavyto allow the reliable and lightweight operation of a WSN. Therefore, providingsecurity, while maintaining Quality of Service (QoS) and energy efficiency, representsan important research challenge in the design of WSNs. In this thesis, we criticallyinvestigate the problem of security provisioning in WSNs. We identify challenges, limitations,and requirements for implementing security with QoS and energy efficiencyfor dense WSNs. We find that the security constraints for WSNs have not been welldiscussed in the literature. Also, the simultaneous optimization of energy, QoS, andsecurity has not gained much attention. We develop two novel algorithms that addressthe above issues in WSNs and optimize energy, QoS, and security using a metaheuristictechnique known as Ant Colony Optimization (ACO). These algorithms arecalled Dynamic Trust-aware Secure Routing (DTSR) and Lightweight Secure Routing(LSR). DTSR improves the connectivity and improves the tradeoff between coverageand lifetime for dense WSNs. Furthermore, LSR provides an improved method forthe detection and isolation of a compromised node by using direct and indirect trustcalculations for dense WSNs. We show through analytical and simulation results thatour presented algorithms can outperform existing techniques in terms of network lifetime,average routing delay, and packet delivery ratio. Also, we perform an analysisof network lifetime over varying network sizes to find a good range of nodes for theeffcient performance of the algorithm. Furthermore, we present a runtime analysisof the algorithms to understand the simulation time in the MATLAB environmentbased on changing network size.

ISBN: 9798759930662Subjects--Topical Terms:

532586
Cryptography.

Adaptive Quality of Service and Trust Based Lightweight Secure Routing Algorithm for Dense Wireless Sensor Networks.
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520 $a Wireless Sensor Networks (WSNs) are group of wireless devices that are deployedin an adhoc manner and are generally left unattended. The main advantages of WSNsare that they are simple to use, allow the use of inexpensive sensor nodes, and havegood scalability. WSNs are useful in object tracking, periodic monitoring, and eventdetection applications. However, the inherent characteristics of the WSNs, such aslimited resources and low computation, make them vulnerable to various types of securityattacks. Therefore, security mechanisms are needed to secure the network andprotect against various security attacks. Conventional security mechanisms, such ascryptography (encryption/decryption) and authentication based systems, are generallyused to ensure the security of traditional networks. However, due to the resourceconstrained nature of WSNs, conventional security mechanisms can be too resourceheavyto allow the reliable and lightweight operation of a WSN. Therefore, providingsecurity, while maintaining Quality of Service (QoS) and energy efficiency, representsan important research challenge in the design of WSNs. In this thesis, we criticallyinvestigate the problem of security provisioning in WSNs. We identify challenges, limitations,and requirements for implementing security with QoS and energy efficiencyfor dense WSNs. We find that the security constraints for WSNs have not been welldiscussed in the literature. Also, the simultaneous optimization of energy, QoS, andsecurity has not gained much attention. We develop two novel algorithms that addressthe above issues in WSNs and optimize energy, QoS, and security using a metaheuristictechnique known as Ant Colony Optimization (ACO). These algorithms arecalled Dynamic Trust-aware Secure Routing (DTSR) and Lightweight Secure Routing(LSR). DTSR improves the connectivity and improves the tradeoff between coverageand lifetime for dense WSNs. Furthermore, LSR provides an improved method forthe detection and isolation of a compromised node by using direct and indirect trustcalculations for dense WSNs. We show through analytical and simulation results thatour presented algorithms can outperform existing techniques in terms of network lifetime,average routing delay, and packet delivery ratio. Also, we perform an analysisof network lifetime over varying network sizes to find a good range of nodes for theeffcient performance of the algorithm. Furthermore, we present a runtime analysisof the algorithms to understand the simulation time in the MATLAB environmentbased on changing network size.
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