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Energy Efficient Association Method for Wireless Sensor Networks

Copyright © 2012. 25 pages.
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DOI: 10.4018/978-1-4666-1842-8.ch009
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MLA

Lee, Jae-Hyung and Dong-Sung Kim. "Energy Efficient Association Method for Wireless Sensor Networks." Energy-Aware Systems and Networking for Sustainable Initiatives. IGI Global, 2012. 181-205. Web. 1 Nov. 2014. doi:10.4018/978-1-4666-1842-8.ch009

APA

Lee, J., & Kim, D. (2012). Energy Efficient Association Method for Wireless Sensor Networks. In N. Kaabouch, & W. Hu (Eds.) Energy-Aware Systems and Networking for Sustainable Initiatives (pp. 181-205). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-1842-8.ch009

Chicago

Lee, Jae-Hyung and Dong-Sung Kim. "Energy Efficient Association Method for Wireless Sensor Networks." In Energy-Aware Systems and Networking for Sustainable Initiatives, ed. Naima Kaabouch and Wen-Chen Hu, 181-205 (2012), accessed November 01, 2014. doi:10.4018/978-1-4666-1842-8.ch009

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Abstract

This chapter describes an energy efficient association method for Wireless Sensor Networks (WSNs). The described method can be used to implement an association procedure by which an improved processing rate can be achieved by using a Beacon Only Period (BOP). The performance of mobile nodes is enhanced by using information on depth, traffic, and Received Signal Strength Indicator (RSSI). By using the Energy Efficient Association (EEA) method, trusted data can be transferred, and traffic overloads that occur at specific nodes can be prevented. In order to research the performance of the described method, the obtained information, such as depth, traffic rate, and RRSI from the relay nodes, is investigated and analyzed. Simulation results show that the EEA method can be used to obtain an efficient network configuration according to the mobility of nodes in WSNs.
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Introduction

Recently, wireless communication has been studied as a very attractive option for industrial and factory automation, power plant systems, distributed control systems, and other kinds of networked embedded systems (Taslidere, 2011; Han, 2011; Dimokas, 2011). Wireless technologies that can be adopted to develop WSNs (Wireless Sensor Networks) and Fieldbus systems include Wi-Fi (IEEE 802.11-WLANs), Bluetooth, and technologies based on the IEEE 802.15.4 standard (IEEE Standard for Information Technology, 2007).

Wi-Fi and Bluetooth technologies have penetrated small office and home office as well as large enterprise office. However, these wireless technologies may find their limited usage in industrial installations due to harsh environments, interference problems, safety, security, and energy consumption for battery lifetime. To respond to the need for standard for industrial solutions, there are some working groups, i.e., the ZigBee Alliance, WirelessHART (HART communication foundation) Communication Foundation (HCF), and ISA 100 that has been defined as ISA 100.11a (ISA100.11a Working Group) that is an open standard for process control in industrial automation and related applications. These specifications are all based on the IEEE 802.15.4 standard or its PHY layer. Thus, this chapter focuses the IEEE 802.15.4 standard for satisfying the following criteria in harsh environment:

  • Optimized load-balancing association method for maximum network lifetime;

  • Support of human waking-speed mobility for some particular network nodes (sinks);

  • Time critical association procedure for frequently joining and withdrawal by mobility.

In most cases, sensor nodes use batteries for energy supply. Batteries have a finite lifetime, although it is possible to prolong this lifetime by combining energy-harvesting system (Roundy, 2004). In recent years, the fundamental goal of a WSN is to produce information from raw local data obtained by individual sensor node by prolonging the lifetime of WSN as much as possible and prevent connectivity degradation by employing aggressive energy management techniques. For increasing battery lifetime, energy-efficiency can be considered as the single most important design goal for sensor network hardware, algorithms, protocols, and applications. In this research, we consider an energy efficient association method for adding new nodes or mobile nodes that are frequently associated by mobility in WSNs.

In the IEEE 802.15.4 standard, for every newly added node, a table comprising a list of neighbors at a distance of one hop from the node is created. Then, the association procedure is performed by the node with the lowest depth, we called DBA (Depth-Based Association) method, for which the RSSI (Received Signal Strength Indicator) is greater than the standard in neighboring table. For such a network configuration, the processing time required to create the neighboring table is high. Because only depth is considered in the procedure, inefficient configurations are produced by a beacon that lacks information on the network at the time when a node sends a request to join the network. As a result, the newly added node generates a packet in order to join the network through a node at which traffic is concentrated; therefore, the performance of the overall network may be degraded and only the energy of a specific node may be consumed. To increase sensor node’s battery life, the load-balancing association scheme is demanded on WSNs, when new nodes or mobile nodes join the network.

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Complete Chapter List

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Table of Contents
Foreword
Wayne S. Seames
Preface
Naima Kaabouch, Wen-Chen Hu
Chapter 1
Tapio Niemi, Jukka Kommeri, Ari-Pekka Hameri
The authors applied operations management principles on scheduling and allocation to scientific computing clusters to decrease energy consumption... Sample PDF
Improving Energy-Efficiency of Scientific Computing Clusters
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Chapter 2
Simon Kiertscher, Bettina Schnor, Jörg Zinke
In 2007, the Green500 list was introduced, which compares supercomputers by performance-per-watt. Since supercomputers consist of thousands of... Sample PDF
Power Consumption Aware Cluster Resource Management
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Chapter 3
Jason Mair, Zhiyi Huang, Haibo Zhang
This chapter discusses energy-aware scheduling techniques for parallel applications on multicore computers. Key techniques for developing an... Sample PDF
Energy-Aware Scheduling for Parallel Applications on Multicore Systems
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Chapter 4
Yang Ge, Qinru Qiu
High chip complexity and power consumption raise chip temperature, reduce lifetime, affect the reliability, and increase the cooling cost. Dynamic... Sample PDF
Dynamic Thermal Management for Multi-/Many-Core Systems
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Chapter 5
Koji Ando, Sumio Ikegawa, Keiko Abe, Shinobu Fujita, Hiroaki Yoda
Normally-off Computer (NOC) is a computer designed with a new concept in which most parts of a computer use non-volatile functionalities. The power... Sample PDF
Roles of Non-Volatile Devices in Future Computer Systems: Normally-Off Computers
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Chapter 6
Juejia Zhou, Mingju Li, Liu Liu, Xiaoming She, Lan Chen
A cellular network is a kind of dedicated distributed network with wireless radio access, and nowadays, it is widely used in people’s lives. The... Sample PDF
Energy Efficient Transmission in Cellular Networks
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Chapter 7
Haris I. Volos, Dinesh Datla, Xuetao Chen, An He, Ashwin Amanna, Timothy R. Newman, S. M. Shajedul Hasan, Jeffery H. Reed, Tamal Bose
The exponential growth of wireless systems makes their carbon footprint hard to ignore. This chapter presents statistics related to the energy... Sample PDF
Green Communications: Realizing Environmentally Friendly, Cost Effective, and Energy Efficient Wireless Systems
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Chapter 8
Blerim Qela, Hussein T. Mouftah
The purpose of this chapter is to explore and address the issues that are applicable to Smart Environments by encouraging and providing new insights... Sample PDF
Intelligent Systems for Energy Management in Wireless Sensor-Based Smart Environments
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Chapter 9
Jae-Hyung Lee, Dong-Sung Kim
This chapter describes an energy efficient association method for Wireless Sensor Networks (WSNs). The described method can be used to implement an... Sample PDF
Energy Efficient Association Method for Wireless Sensor Networks
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Chapter 10
Frédéric Giroire, Dorian Mazauric, Joanna Moulierac
Several studies exhibit that the traffic load of routers only has a small influence on their energy consumption. Hence, the power consumption in... Sample PDF
Energy Efficient Routing by Switching-Off Network Interfaces
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Chapter 11
Mamoun Guenach, Koen Hooghe, Michael Timmers, Jochen Maes, Dominique Singy, Oliver Lamparter
The second part of this chapter focuses on deployment practices and describes how different access network architectures can improve the energy... Sample PDF
Energy Optimizations in Broadband Access Networks
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Chapter 12
Hussein T. Mouftah, Burak Kantarci
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Greening the Survivable Optical Networks: Solutions and Challenges for the Backbone and Access
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Chapter 13
Aruna Prem Bianzino, Anand Raju, Dario Rossi
In this chapter, the authors perform a careful sensitivity analysis of a power model for the Internet core: their results show that, no matter how... Sample PDF
Power Profiling the Internet Core: A Sensitivity Analysis
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Chapter 14
Ali Muhtaroglu
Contemporary computing requires long battery life, low energy operation, and compact, low cost, light platforms, all at the same time. Good power... Sample PDF
Power Management and Energy Scavenging
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Chapter 15
Yukihiro Nakagawa, Takeshi Shimizu, Takeshi Horie, Yoichi Koyanagi, Osamu Shiraki, Takashi Miyoshi, Yasushi Umezawa, Akira Hattori, Yasuo Hidaka
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Energy-Aware Switch Design
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Chapter 16
Abdelghani Renbi
It is believed that data-stream-driven computing is power and energy efficient as compared to its counterpart, instruction-stream-driven computing.... Sample PDF
Data-Stream-Driven Computers are Power and Energy Efficient
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Chapter 17
Xun Zhang, Pierre Leray, Jacques Palicot
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