It is important to have continuous connectivity in a wireless

For the majority of the applications of WSNs, it is desirable to know the location of sensors. In WSNs, for obtaining this kind of information we need localization schemes. Localization techniques are used to determine the geographical position of sensor nodes. The position parameters of sensor nodes are also useful for many operations for network management, such as routing process, topology control, and security maintenance. So, it is very important that every node should reports its location information very accurately. As we know that GPS is very accurate in location determination but it is expensive in terms of cost and energy of nodes, so it is not useful in WSNs. There are so many localization techniques, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Accuracy of localization techniques is most important before implementing it. With specific hardware, the range-based schemes typically achieve high accuracy based on either nodeto-node distances or angles. In this paper, our main focus is on the range-based localization. Precisely, in order to helps the network designers to find out which techniques/algorithms are suitable for their applications, the most popular range-based localization techniques are classified and compared.

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Wireless sensor networks (WSNs) often consist of tiny devices and offer a variety of potential means to monitor the environment. However, WSNs are vulnerable to several types of attack because of their use in critical applications, their deployment in open and unprotected environments and their limited system resources. Therefore, security design is an important aspect of WSNs. In this work, we focus on detecting misbehaving nodes in WSNs. To the best of our knowledge, we are the first to present a complete and formal study on finding optimised monitor nodes and combining the organisation of the network with monitoring for misbehaviour detection in WSNs. The main idea of this work is to propose simple and efficient distributed monitoring algorithm capable of detecting misbehaviours based on a clustered architecture, where the cluster head is elected according to a new set of metrics. These new election metrics are based on a multiple-criteria decision approach in order to monitor the health status of cluster members and detect misbehaviour. Our proposed strategy ensures a good selection of the nodes responsible for monitoring, reduces energy consumption during the monitoring process-effectively reducing the amount of security information that flows through the network-and reduces latency. The efficiency of our method is evaluated through simulation experiments.

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