Efficient Distributed Detection for Wireless Sensor Networks

Negli ultimi anni si è assistito ad una crescita esponenziale delle tecnologie per la fabbricazione di micro dispositivi ed, in particolare, di sensori. Il costo di tali sensori si è ridotto, portando ad un crescente interesse in reti di sensori, ad esempio, per il monitoraggio ambientale. D'altro canto, l'utilizzo di reti di sensori nel campo militare ha una lunga storia. In tutti i casi, l'obiettivo di una rete di sensori è quello di identificare lo stato di un fenomeno di interesse attraverso l'azione collaborativo di più sensori. Un esempio di tale azione è la rivelazione distribuita. In questa tesi, viene studiato come incorporare le caratteristiche intrisìnseche del fenomeno sotto osservazione nella progettazione di algoritmi di rivelazione distribuita in reti di sensori.Recent years have witnessed an exponential growth of micro device manufacturing techniques and, in particular, of powerful sensor devices. The costs of these sensors have dropped, leading to an increasing interest on sensor networks for civilian applications, e.g., environmental monitoring. The use of sensor networks in the military field has, on the other hand, a long history. In all cases, the goal of a sensor network is to identify the status of a phenomenon of interest through a collaborative action of the sensors. An instance of this collaborative action is given by distributed detection. The increasing interest for sensor networks has, therefore, spurred a significant activity on the design of efficient distributed detection techniques. In this thesis, we investigate how the structural properties of the physical phenomenon under observation can be taken into account in designing distributed detection algorithms for sensor networks

Online) An Open Access

ABSTRACT The main concern in Wireless Sensor Networks is how to handle with their limited energy resources. The performance of Wireless Sensor Networks strongly depends on their lifetime. As a result, Dynamic Power Management approaches with the purpose of reduction of energy consumption in sensor nodes, after deployment and designing of the network. Recently, there have been a strong interest to use intelligent tools especially Neural Networks in energy efficient approaches of Wireless Sensor Networks, due to their simple parallel distributed computation, distributed storage, data robustness, auto-classification of sensor nodes and sensor reading. This paper presents a new centralized adaptive Energy Based Clustering protocol through the application of Self organizing map neural networks (called EBC-S) which can cluster sensor nodes, based on multi parameters; energy level and coordinates of sensor nodes. We applied some maximum energy nodes as weights of SOM map units; so that the nodes with higher energy attract the nearest nodes with lower energy levels. Therefore, formed clusters may not necessarily contain adjacent nodes. The new algorithm enables us to form energy balanced clusters and equally distribute energy consumption. Simulation results and comparison with previous protocols (LEACH and LEA2C) prove that our new algorithm is able to extend the lifetime of the network. Keywords: Energy Based Clustering, Self Organizing Map Neural Networks, Wireless Sensor Networks INTRODUCTION The most important difference of Wireless Sensor Network (WSNs) with other wireless networks may be constraints of their resources, especially energy which usually arise from small size of sensor nodes and their batteries which is a prerequisite to WSNs main applications. The main and most important reason of WSNs creation was continuous monitoring of environments where are too hard or impossible for human to access or stay. So there is often low possibility to replace or recharge the dead nodes as well. The other important requirement is that we need a continuous monitoring so the lifetime and network coverage of these networks are our great concerns. As a result, as energy conservation is the main concern in WSNs, but also it should be gained with balanced distribution in whole network space. Balanced distribution of energy in whole network will lead to balanced death of nodes in all regions preventing from lacking network coverage in a rather large part of the network. Energy conservation should be gained by wisely management of energy sources. Several energy conservation schemes have been proposed in the literature while there is a comprehensive survey of energy conservation methods for WSNs and the taxonomy of all into three main approaches (duty-cycling, data reduction, and mobility based approaches

Hierarchical Routing Protocols in Wireless Sensor Networks: A Survey and its Comparison

In Wireless Sensor Networks (WSN), profound research articles are presented to address the hierarchical routing protocols which reduce the energy consumption of sensor nodes and also prolong the life of the network. The state of art of this research article focus on the survey of different hierarchical routing protocols which is utilized to efficiently deliver the sensed data from source to sink node. This article presents a detailed survey on major clustering techniques LEACH, SEP, PEGASIS, and TEEN. Also, this article strongly examines about the advantages and limitations of each hierarchical routing protocol with its recent research issues. Finally, the paper concludes with some of the research issues in hierarchical routing protocols of wireless sensor networks

Energy and Delay Efficient Computation Offloading Solutions for Edge Computing

This thesis collects a selective set of outcomes of a PhD course in Electronics, Telecommunications, and Information Technologies Engineering and it is focused on designing techniques to optimize computational resources in different wireless communication environments. Mobile Edge Computing (MEC) is a novel and distributed computational paradigm that has emerged to address the high users demand in 5G. In MEC, edge devices can share their resources to collaborate in terms of storage and computation. One of the computational sharing techniques is computation offloading, which brings a lot of advantages to the network edge, from lower communication, to lower energy consumption for computation. However, the communication among the devices should be managed such that the resources are exploited efficiently. To this aim, in this dissertation, computation offloading in different wireless environments with different number of users, network traffic, resource availability and devices' location are analyzed in order to optimize the resource allocation at the network edge. To better organize the dissertation, the studies are classified in four main sections. In the first section, an introduction on computational sharing technologies is given. Later, the problem of computation offloading is defined, and the challenges are introduced. In the second section, two partial offloading techniques are proposed. While in the first one, centralized and distributed architectures are proposed, in the second work, an Evolutionary Algorithm for task offloading is proposed. In the third section, the offloading problem is seen from a different perspective where the end users can harvest energy from either renewable sources of energy or through Wireless Power Transfer. In the fourth section, the MEC in vehicular environments is studied. In one work a heuristic is introduced in order to perform the computation offloading in Internet of Vehicles and in the other a learning-based approach based on bandit theory is proposed

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios

Cluster Head Selection in a Homogeneous Wireless Sensor Network Ensuring Full Connectivity with Minimum Isolated Nodes

The research work proposes a cluster head selection algorithm for a wireless sensor network. A node can be a cluster head if it is connected to at least one unique neighbor node where the unique neighbor is the one that is not connected to any other node. If there is no connected unique node then the CH is selected on the basis of residual energy and the number of neighbor nodes. With the increase in number of clusters, the processing energy of the network increases; hence, this algorithm proposes minimum number of clusters which further leads to increased network lifetime. The major novel contribution of the proposed work is an algorithm that ensures a completely connected network with minimum number of isolated nodes. An isolated node will remain only if it is not within the transmission range of any other node. With the maximum connectivity, the coverage of the network is automatically maximized. The superiority of the proposed design is verified by simulation results done in MATLAB, where it clearly depicts that the total numbers of rounds before the network dies out are maximum compared to other existing protocols

Energy-Efficient Routing Control Algorithm in Large-Scale WSN for Water Environment Monitoring with Application to Three Gorges Reservoir Area

Published version of an article in the journal: The Scientific World Journal. Also available from the publisher at: http://dx.doi.org/10.1155/2014/802915 Open AccessThe typical application backgrounds of large-scale WSN (wireless sensor networks) for the water environment monitoring in the Three Gorges Reservoir are large coverage area and wide distribution. To maximally prolong lifetime of large-scale WSN, a new energy-saving routing algorithm has been proposed, using the method of maximum energy-welfare optimization clustering. Firstly, temporary clusters are formed based on two main parameters, the remaining energy of nodes and the distance between a node and the base station. Secondly, the algorithm adjusts cluster heads and optimizes the clustering according to the maximum energy-welfare of the cluster by the cluster head shifting mechanism. Finally, in order to save node energy efficiently, cluster heads transmit data to the base station in single-hop and multihop way. Theoretical analysis and simulation results show that the proposed algorithm is feasible and advanced. It can efficiently save the node energy, balance the energy dissipation of all nodes, and prolong the network lifetime

Recovery mechanism on sensor networks

On the completion of project, we propose novel recovery mechanisms which recovers limited-resource wireless sensor networks quickly from an malicious attack. The research outcomes include re-clustering algorithms, reprogramming techniques and authentications protocols developed and tested on both hardware and simulation platforms. The work is also well compared with other researchers

A Comparative Survey of VANET Clustering Techniques

© 2016 Crown. A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles - most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming - the lack of realistic vehicular channel modeling - is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated