Event Based Data Gathering in Wireless Sensor Networks

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.

Wireless Sensor Network

Wireless Sensor Networks (WSNs) are becoming common in use, with a vast diversity of applications. Due to its resource constraints, it is hard to maintain Quality of Service (QoS) with WSNs. Though they contain a vast variety of applications, at the same time they are also required to provide different levels of QoS, for various types of applications. A number of different issues and challenges still persist ahead to maintain the QoS of WSN, especially in critical applications where the accuracy of timely, guaranteed data transfer is required, such as chemical, defense, and healthcare. Hence, QoS is required to ensure the best use of sensor nodes at any time. Researchers are trying to focus on QoS issues and challenges to get maximum benefit from their applications. With this chapter, the authors focus on operational and architectural challenges of handling QoS, requirements of QoS in WSNs, and they discuss a selected survey of QoS aware routing techniques by comparing them in WSNs. Finally, the authors highlight a few open issues and future directions of research for providing QoS in WSNs.

Interoperability in Wireless Sensor Networks Based on IEEE 1451 Standard

The syntactic and semantic interoperability is a challenge of the Wireless Sensor Networks (WSN) with smart sensors in pervasive computing environments to increase their harmonization in a wide variety of applications. This chapter contains a detailed description of interoperability in heterogeneous WSN using the IEEE 1451 standard. This work focuses on personal area networks (PAN) with smart sensors and actuators. Also, technical, syntactic, and semantic levels of interoperability based on IEEE 1451 standardization are established with common control commands. In this architecture, each node includes a Transducer Electronic Datasheets (TEDS) and intelligent functions. The authors explore different options to apply the IEEE 1451 standard using SOAP or REST Web service style in order to test a common syntactical interoperability that could be predominant in future WSNs.

A Game Theoretical Approach to Design

Game Theory provides a mathematical tool for the analysis of interactions between the agents with conflicting interests, hence it is a suitable tool to model some problems in communication systems, especially, to wireless sensor networks (WSNs) where the prime goal is to minimize energy consumption than high throughput and low delay. Another important aspect of WSNs are their ad-hoc topology. In such ad-hoc and distributed environment, selfish nodes can easily obtain the unfair share of the bandwidth by not following the medium access control (MAC) protocol. This selfish behavior, at the expense of well behaved nodes, can degrade the performance of overall network. In this chapter, the authors use the concepts of game theory to design an energy efficient MAC protocol for WSNs. This allows them to introduce persistent/non-persistent sift protocol for energy efficient MAC protocol and to counteract the selfish behavior of nodes in WSNs. Finally, the research results show that game theoretical approach with the persistent/non-persistent sift algorithm can improve the overall performance as well as achieve all the goals simultaneously for MAC protocol in WSNs.

Medium Access Control Protocols for Wireless Sensor Networks

This chapter provides an overall understanding of the design aspects of Medium Access Control (MAC) protocols for Wireless Sensor Networks (WSNs). A WSN MAC protocol shares the wireless broadcast medium among sensor nodes and creates a basic network infrastructure for them to communicate with each other. The MAC protocol also has a direct influence on the network lifetime of WSNs as it controls the activities of the radio, which is the most power-consuming component of resource-scarce sensor nodes. In this chapter, the authors first discuss the basics of MAC design for WSNs and present a set of important MAC attributes. Subsequently, authors discuss the main categories of MAC protocols proposed for WSNs and highlight their strong and weak points. After briefly outlining different MAC protocols falling in each category, the authors provide a substantial comparison of these protocols for several parameters. Lastly, the chapter discusses future research directions on open issues in this field that have mostly been overlooked.

Using Multi-Objective Particle Swarm Optimization for Energy-Efficient Clustering in Wireless Sensor Networks

In this chapter, the authors propose a multi-objective solution to the problem by using multi-objective particle swarm optimization (MOPSO) algorithm to optimize the number of clusters in a sensor network in order to provide an energy-efficient solution. The proposed algorithm considers the ideal degree of nodes and battery power consumption of the sensor nodes. The main advantage of the proposed method is that it provides a set of solutions at a time. The results of the proposed approach were compared with two other well-known clustering techniques: WCA and CLPSO-based clustering. Extensive simulations were performed to show that the proposed approach is an effective approach for clustering in WSN environments and performs better than the other two approaches.

Node Localization

Wireless sensor networks (WSNs) are taking a major share with almost all types of different applications and especially, it is most suited in very harsh and tough environments, where it is too hard to deploy conventional network applications, for example in the forest fire area, battlefields during the war, chemical and thermal sites, and also for few underwater applications. WSNs are now becoming part of almost all applications because of their ease in deployment and cheaper cost. These networks are resource constraints, very small in size, computation, and with much less communication capabilities. Nodes are normally deployed in random fashion, and it’s too hard to find their location because there is no any predefined way like conventional networks to discern location. Location is highly important to know the data correlation: for example its target tracking, and to know actual vicinity of the any event occurrence. This chapter describes the current available approaches, issues, and challenges with current approaches and future directions for node localization, one by one. Node localization is highly important for large sensor networks where users desire to know about the exact location of the nodes to know the data location.

Mitigation of Hot Spots on Wireless Sensor Networks

The use of Wireless Sensor Networks (WSNs) has increased over the past years, supporting applications such as environmental monitoring, security systems, and multimedia streaming. These networks are characterized by a many-to-one traffic pattern. Hence, sensor nodes near to the sink have higher energy consumption, being prone to earlier deaths and failures. Those areas overloaded with high traffic rates are called Hot Spots, and their emergence creates and expands energy holes that compromise network lifetime and data delivery rates, and may result in disconnected areas. This chapter provides an overview of techniques to mitigate Hot Spot impacts, such as the uneven distribution of sensors, routes that balance energy consumption, sink mobility, and the use of unequal clustering. Further, it depicts the approach for achieving mitigation of sink centered Hot Spots. Finally, this chapter presents conclusions and future research perspectives.

Wireless Sensor Network Testbeds

The rapid increase in WSN-Testbed deployments alongside intra-academic and inter-industrial collaboration are two healthy signs which not only affirm but also confirm that it is a matter of time before WSN technology becomes a preferred industrial norm. In this chapter, the authors help in realizing this very fact through reflecting on different experiences pertinent to WSN-Testbed deployments. To put this objective into perspective, first, the authors adopt and describe a classification methodology for WSN-Testbeds. Second, the authors present a generic architecture for the different classes of WSN-Testbeds. Third, the authors pinpoint some design challenges and evaluation criteria/benchmarking scheme pertinent to WSN-Testbeds. Fourth, the authors examine the literature and opt for a variety of 30 WSN-Testbeds. The selection of these WSN-Testbeds is carefully made to cover the various spectra of WSN applications while avoiding redundancy. Fifth, selected WSN-Testbeds are comparatively analyzed with highlights of architecture and distinctive features. Sixth, the authors apply the benchmarking scheme and properly evaluate the selected WSN-Testbeds. Then, the authors shed light on some of the most relevant challenges and drawbacks. Finally, interesting discussion is introduced where among the issues discussed are: vitality of WSN-Testbeds, design trade-offs, network model, WSN’s OS, topology control, power management, some real world deployment challenges, and confidentiality infringement. The authors believe that this chapter is a contribution towards realizing the important role that a WSN-Testbed plays in hastening the industrial adoption for the promising WSN technology.

A Taxonomy of Routing Techniques in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) are finding different applications for offshore exploration and ocean monitoring. In most of these applications, the network consists of a significant number of sensor nodes deployed at different depth levels throughout the area of interest. Sensor nodes on the sea bed cannot communicate directly with the nodes near the surface level, so they require multihop communication assisted by an appropriate routing scheme. However, this appropriateness not only depends on network resources and application requirements, but environment constraints are involved as well. These factors all provide a platform where a resource aware routing strategy plays a vital role in fulfilling different application requirements with dynamic environment conditions. Realizing this fact, much of the attention has been given to construct a reliable scheme, and many routing protocols have been proposed in order to provide efficient route discoveries between the source and sink. In this chapter, the authors present a review and comparison of different algorithms proposed recently for underwater sensor networks. Later on, all of these have been classified into different groups according to their characteristics and functionalities.