International Journal of Sensors Wireless Communications and Control - Volume 3, Issue 2, 2013

Rapid advances in sensing and wireless communication technologies have made attractive the deployment of inexpensive wireless sensor networks for various applications such as ecosystem monitoring and traffic and military surveillance. Efficient use of sensor node energy is a critical management consideration of a wireless sensor network. In this paper, we study the data collection problem in such network in order to improve network longevity. The problem involves selecting a set of representative sensor nodes (R-nodes) that covers all sensor nodes in the network for data collection purposes. We present a formal definition of the problem and develop for the first time, to the best of our knowledge, an integer programming formulation of the problem. Because of the computational complexity of the problem and the need to solve it repeatedly, we propose a heuristic algorithm aiming to maximize the bottleneck residual energy of the selected Rnodes while minimizing the number of the R-nodes with the ultimate goal of maximizing network lifetime. Extensive experimental tests on large wireless sensor networks show that the proposed algorithm significantly outperforms one of the best prior algorithms in key performances metrics, namely the network lifetime, the number of R-nodes and the energy savings.

Mobile ad hoc networks communicate in a self-organized way without depending on any fixed infrastructure. The issue of selfish nodes, which may refuse to cooperate, is a great challenge in such networks and may cause network throughput to drastically reduce. Energy-based selfishness is a category of selfishness in which a selfish node shows nondeterministic and probabilistic selfishness behaviors based on level of its energy. In this paper, we propose a mechanism for coping with this kind of selfishness. This mechanism called CEMDEEM not only detects and isolates energy-based and traditional selfish nodes, but also malicious behaviors like spoofing. We also evaluate performance of Dynamic Source Routing (DSR) protocol fortified by CEMDEEM in the presence of different percentages of selfish nodes. Results show that CEMDEEM noticeably improves network performance with a reasonable additional packet overhead and network delay especially when percentage of selfish nodes is not more than 40.

This paper introduces an intelligent and comprehensive monitoring system (ICMS) for swimming pool safety. The ICMS consists of underwater ultrasonic detection subsystem (UUDS), underwater video detection subsystem (UVDS) and virtual pool fence monitoring subsystem (VPFS). Multiple ultrasonic sensors in UUDS can detect drowning people in real time with a range up to 70 meters and cover the entire swimming pool. As a supplementary, UVDS can quickly find and locate drowning people by analyzing real time video sequences and assisting UUDS in realizing more accurate detection. The VPFS not only provides flexible and adjustable virtual pool fence which can detect pool intruders but also allows the hierarchical and cross domain video monitoring service for enhancing pool safety. The three subsystems are independent in operation but can complement one another in functionality. Distributed modular design based ICMS has good performances in flexibility, scalability and hierarchical monitoring. Besides, efficient network communication model and uniform data interface are employed to improve the robustness and high efficiency of the whole monitoring system. In addition, the ICMS provides client/server and browser/server hybrid structures which enables different network terminals to login to the system conveniently. Combined with a variety of technologies, ICMS can realize intelligent and comprehensive monitoring for pool safety.

In this paper, an overview of three well-known two-dimensional Direction Of Arrival (DOA) estimation algorithms, namely, MUltiple SIgnal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) and Propagator Method (PM) is presented. In order to reduce the computational complexity of 2-D methods, azimuth and elevation estimations are extracted from two one-dimensional estimations. As the main objective of this investigation, considering 1-D realization of 2-D DOA estimation algorithms and simulation them in MATLAB software, the Root Mean Square Error (RMSE) performance of these methods is compared in three cases, uncorrelated, correlated and coherent signals in the presence of white Gaussian noise as well as colored noise. Simulation results show that for uncorrelated signals, MUSIC in low Signal to Noise Ratios (SNRs) and ESPRIT in high SNRs offer lower RMSE. In the case of coherent and correlated signals, ESPRIT is the best choice in all SNRs. Finally, for colored noise scenario, PM provides more accurate estimation for low SNRs, while ESPRIT has a lower RMSE for high SNRs compared to two other methods.

Clustering in WSN proves to be phenomenal in maximizing network life. This paper comes up with a new clustering scheme with a mutual exclusion feature. A number of clustering protocols are employed in WSN, but none of the protocol has ensured or focused on mutual exclusion of a cluster head role over range of communication. The objective of this paper is to propose a new distributive clustering protocol which will also work like mutual exclusion algorithms. This mutual exclusive distributive protocol forms the cluster of sensors, and selects a cluster head which possesses the mutual exclusion property.

Underwater Sensor Networks (UWSNs) are being deployed for range of applications like collection of oceanic data for research, underwater exploration, surveillance, disaster prevention etc. UWSNs are different from terrestrial WSNs in terms of communication methods, network deployment and protocols used. In this paper, we present a localization based routing algorithm with distance and energy consideration. In our scheme, sender node selects a forwarding node on the basis of Routing Factor (Rf), a function of neighbor’s distance from destination node and its residual energy. Energy is scaled within a range to take heterogeneity of node energies into account. Priority packets and routing tables are also considered in our algorithm. Simulation results show improved performance of our routing algorithm in terms of network lifetime and end to end delays.