A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps

Achieving the end-to-end goals and objectives of Wireless Sensor Networks (WSN) is a highly challenging task. Such objectives include maximizing network lifetime, guaranteeing connectivity and coverage, and maximizing throughput. In addition, some of these goals are in conflict such as network lifet...

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Main Authors: Amr El-Mougy, Mohamed Ibnkahla
Format: Article
Language:English
Published: SAGE Publishing 2013-03-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2013/568580
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spelling doaj-d3ef3613adb24cacbb7424c1f2c38c1a2020-11-25T03:20:34ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772013-03-01910.1155/2013/568580A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive MapsAmr El-MougyMohamed IbnkahlaAchieving the end-to-end goals and objectives of Wireless Sensor Networks (WSN) is a highly challenging task. Such objectives include maximizing network lifetime, guaranteeing connectivity and coverage, and maximizing throughput. In addition, some of these goals are in conflict such as network lifetime and throughput. Cross-layer design can be efficient in proposing network management techniques that can consider different network objectives and conflicting constraints. This can be highly valuable in challenging applications where multiple Quality of Service (QoS) requirements may be demanded. In this paper, a novel cross-layer framework for network management is proposed that particularly targets WSN with challenging applications. The proposed framework is designed using the tool known as Weighted Cognitive Map (WCM). The inference properties of WCMs allow the system to consider multiple objectives and constraints while maintaining low complexity. Methods for achieving different objectives using WCMs are illustrated, as well as how system processes can operate coherently to achieve common end-to-end goals. Using extensive computer simulations, the proposed system is evaluated. The results show that it achieves good performance results in metrics of network lifetime, throughput, and Packet Loss Ratio (PLR).https://doi.org/10.1155/2013/568580
collection DOAJ
language English
format Article
sources DOAJ
author Amr El-Mougy
Mohamed Ibnkahla
spellingShingle Amr El-Mougy
Mohamed Ibnkahla
A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
International Journal of Distributed Sensor Networks
author_facet Amr El-Mougy
Mohamed Ibnkahla
author_sort Amr El-Mougy
title A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
title_short A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
title_full A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
title_fullStr A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
title_full_unstemmed A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps
title_sort cross-layer framework for network management in wireless sensor networks using weighted cognitive maps
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2013-03-01
description Achieving the end-to-end goals and objectives of Wireless Sensor Networks (WSN) is a highly challenging task. Such objectives include maximizing network lifetime, guaranteeing connectivity and coverage, and maximizing throughput. In addition, some of these goals are in conflict such as network lifetime and throughput. Cross-layer design can be efficient in proposing network management techniques that can consider different network objectives and conflicting constraints. This can be highly valuable in challenging applications where multiple Quality of Service (QoS) requirements may be demanded. In this paper, a novel cross-layer framework for network management is proposed that particularly targets WSN with challenging applications. The proposed framework is designed using the tool known as Weighted Cognitive Map (WCM). The inference properties of WCMs allow the system to consider multiple objectives and constraints while maintaining low complexity. Methods for achieving different objectives using WCMs are illustrated, as well as how system processes can operate coherently to achieve common end-to-end goals. Using extensive computer simulations, the proposed system is evaluated. The results show that it achieves good performance results in metrics of network lifetime, throughput, and Packet Loss Ratio (PLR).
url https://doi.org/10.1155/2013/568580
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