Efficient Compressive Sampling of Spatially Sparse Fields in Wireless Sensor Networks

Wireless sensor networks (WSN), i.e. networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially sparse fields. In this paper, we present a novel bandwidth/energy efficient CS scheme for acquisition of spatially sparse fields in a WSN. The paper contribution is twofold. Firstly, we introduce a sparse, structured CS matrix and we analytically show that it allows accurate reconstruction of bidimensional spatially sparse signals, such as those occurring in several surveillance application. Secondly, we analytically evaluate the energy and bandwidth consumption of our CS scheme when it is applied to data acquisition in a WSN. Numerical results demonstrate that our CS scheme achieves significant energy and bandwidth savings wrt state-of-the-art approaches when employed for sensing a spatially sparse field by means of a WSN.Comment: Submitted to EURASIP Journal on Advances in Signal Processin

Enhanced delay-aware and reliable routing protocol for wireless sensor network

Wireless Sensor Networks (WSN) are distributed low-rate data networks, consist of small sensing nodes equipped with memory, processors and short range wireless communication. The performance of WSN is always measured by the Quality of Service (QoS) parameters that are time delay, reliability and throughput. These networks are dynamic in nature and affect the QoS parameters, especially when real time data delivery is needed. Additionally, in achieving end-to-end delay and reliability, link failures are the major causes that have not been given much attention. So, there is a demanding need of an efficient routing protocol to be developed in order to minimize the delay and provide on time delivery of data in real time WSN applications. An efficient Delay-Aware Path Selection Algorithm (DAPSA) is proposed to minimize the access end-to-end delay based on hop count, link quality and residual energy metrics considering the on time packets delivery. Furthermore, an Intelligent Service Classifier Queuing Model (ISCQM) is proposed to distinguish the real time and non-real time traffic by applying service discriminating theory to ensure delivery of real time data with acceptable delay. Moreover, an Efficient Data Delivery and Recovery Scheme (EDDRS) is proposed to achieve improved packet delivery ratio and control link failures in transmission. This will then improve the overall throughput. Based on the above mentioned approaches, an Enhanced Delay-Aware and Reliable Routing Protocol (EDARRP) is developed. Simulation experiments have been performed using NS2 simulator and multiple scenarios are considered in order to examine the performance parameters. The results are compared with the state-of-the-art routing protocols Stateless Protocol for Real-Time Communication (SPEED) and Distributed Adaptive Cooperative Routing Protocol (DACR) and found that on average the proposed protocol has improved the performance in terms of end-to-end delay (30.10%), packet delivery ratio (9.26%) and throughput (5.42%). The proposed EDARRP protocol has improved the performance of WSN

A joint routing and localization algorithm for emergency scenario

Wireless Sensor Networks (WSNs) have been adopted in a wide range of industrial and consumer applications such as environmental or industrial monitoring, health control, or military systems, for a decade. Main issues in WSN are represented by the large number of sensor nodes, multi-hop communication approach, and needs for an efficient use of available limited sensor energy. In this work an emergency scenario is considered and a WSN is used as a communication infrastructure. To limit the power consumption, the WSN is activated only when the emergency occurs. Few mobile nodes (the rescuers) are moving in the area. In these critical network scenarios, adaptive routing is essential to ensure reliable communication with first responders. At the same time, localizing both WSN nodes and moving nodes is an essential issue for routing the rescuers towards victims. In this paper, the authors jointly tackle routing and localization problems for reducing the network signaling communication as much as possible, which is the most power-consuming operation in WSNs. In particular, it is proposed a distributed localization algorithm, based on a ranging technique, designed by mapping the localization into a stochastic estimation problem for systems with uncertaintie