A Robust Frame of WSN Utilizing Localization Technique

Wireless sensor networks are becoming increasingly popular due to their low cost and wide applicability to support a large number of diverse application areas. Localization of sensor nodes is a fundamental requirement that makes the sensor data meaningful. A wireless sensor network (WSN) consist of spatially distributed autonomous devices using sensors to monitor cooperatively physical or environmental conditions such as temperature, sound, vibration, pressure, motion or pollutants at different locations. The development of wireless sensor networks was originally motivated by a military application like battlefield surveillance. Node localization is required to report the origin of events, assist group querying of sensors, routing and to answer questions on the network coverage. So one of the fundamental challenges in wireless sensor network is node localization. This paper discusses different approaches of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Keywords: Localization, Particle Swarm Optimization, Received Signal Strength, Angle of Arrival

Directional antennas for wireless sensor networks

Directional antennas provide angle-of-arrival information, which can be used for localization and routing algorithms in wireless sensor networks. We briefly describe three classical, major types of antennas: 1) the Adcock-pair antenna, 2) the pseudo-Doppler antenna, and 3) the electronically switched parasitic element antenna. We have found the last type to be the most suitable for wireless sensor networks, and we present here the early design details and beam pattern measurements of a prototype antenna for the 2.4-GHz ISM band, the SPIDA: SICS Parasitic Interference Directional Antenna

Secure Geographic Routing in Ad Hoc and Wireless Sensor Networks

Security in sensor networks is one of the most relevant research topics in resource constrained wireless devices and networks. Several attacks can be suffered in ad hoc and wireless sensor networks (WSN), which are highly susceptible to attacks, due to the limited resources of the nodes. In this paper, we propose innovative and lightweight localization techniques that allow for intrusion identification and isolation schemes and provide accurate location information. This information is used by our routing protocol which additionally incorporates a distributed trust model to prevent several routing attacks to the network. We finally evaluate our algorithms for accurate localization and for secure routing which have been implemented and tested in real ad hoc and wireless sensor networks

Social Network Analysis Based Localization Technique with Clustered Closeness Centrality for 3D Wireless Sensor Networks

[EN] In this paper, we proposed a new wireless localization technique based on the ideology of social network analysis (SNA), to study the different properties of networks as a graph. Centrality is a main concept in SNA, so we propose using closeness centrality (CC) as a measurement to denote the importance of the node inside the network due to its geo-location to others. The node with highest degree of CC is chosen as a cluster heads, then each cluster head can form its trilateration process to collect data from its cluster. The selection of closest cluster based on CC values, and the unknown node's location can be estimated through the trilateration process. To form a perfect trilateration, the cluster head chooses three anchor nodes. The proposed algorithm provides high accuracy even in different network topologies like concave shape, O shape, and C shape as compared to existing received signal strength indicator (RSSI) techniques. 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Optimization Based Self-localization for IoT Wireless Sensor Networks

In this paper we propose an embedded optimization framework for the simultaneous self-localization of all sensors in wireless sensor networks making use of range measurements from ultra-wideband (UWB) signals. Low-power UWB radios, which provide time-of-arrival measurements with decimeter accuracy over large distances, have been increasingly envisioned for realtime localization of IoT devices in GPS-denied environments and large sensor networks. In this work, we therefore explore different non-linear least-squares optimization problems to formulate the localization task based on UWB range measurements. We solve the resulting optimization problems directly using non-linear-programming algorithms that guarantee convergence to locally optimal solutions. This optimization framework allows the consistent comparison of different optimization methods for sensor localization. We propose and demonstrate the best optimization approach for the self-localization of sensors equipped with off-the-shelf microcontrollers using state-of-the-art code generation techniques for the plug-and-play deployment of the optimal localization algorithm. Numerical results indicate that the proposed approach improves localization accuracy and decreases computation times relative to existing iterative methods