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Academic Editor:Zhangbing Zhou
Applied Network Technology (ANT) Laboratory, Department of Computer Science, Faculty of Science, Khon Kaen University, 123 Mitaparb Road, Naimuang, Muang, Khon Kaen 40002, Thailand
Received 10 October 2014; Revised 27 December 2014; Accepted 3 April 2015; 12 October 2015
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
The Internet of Things (IoT) and microelectromechanical systems (MEMS) technology [1] have become feasible in various applications given their distinctive features and characteristics, such as low power consumption with multisensing functionalities and high performance computing within a tiny sensor node embedded with self-contained operational criteria, that is, dedicated storage and transmission logic, for multifunctional uses and applications yielding cost-competitiveness in addition to compactness and portability, which leverage the concept of multipurpose self-organizing sensors [2].
For ubiquitous connectivity supports that alleviate deployment and placement issues, the sensors have integrated wireless transmission logic including the capability to connect a large number of these wireless sensor nodes and then to apply them in several real-world scenarios, leading to the conception of wireless sensor networks (WSNs) [3, 4].
Recently, there have been a diverse number of WSN applications ranging from civil to military, that is, animal tracking, disaster management, health monitoring, health care, inventory control, security and tactical surveillance, traceability, and weather monitoring services [5]. Nevertheless, considering the distinctive characteristics of WSN that have been adopted in diverse real-world applications, many aspects have been explored and investigated for the purpose of improvement, such as quality of service, scalability, data aggregation, fault tolerance, time synchronization, calibration, energy-aware computation, and real-time communication [6].
Moreover, one of the crucial challenges of WSNs is the location discovery, especially without knowledge of a specific location where data are obtained, that is, via global positioning system (GPS) services perhaps provided by satellite. In addition, if equipped in the tiny sensor, the overall overhead of wireless sensors may be increased, including hardware costs and a shortened lifetime of the battery source; thus, further analysis may be misleading and likely inadequate [7-9].
Traditionally, two main approaches have been adopted for WSN location estimation, especially for areas with limited GPS sensing coverage, that is,...