Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

Designing a maintenance free multi-channel wireless sensor network protocol

Wireless sensors are low powered device that is scattered to monitor its surroundings. These energy-constrained devices are usually constructed in a hierarchical structured manner where after sometime some of the nodes may deplete energy resulting disruption of the routing topology in a wireless sensor network. A faulty parent node may cause the reconstruction of the network’s routing topology if a maintenance solution is not provided to the protocol. Thus this study focuses on the maintenance free environment for a multi-channel wireless sensor network. A tree-based solution is proposed for the multi-channel protocol and a route diversion is proposed for the maintenance solution. The multi-channel characteristics is used as a tool to determine the route diversion of the children node. A simulation is built to compare the proposed protocol with existing tree-based multi-channel protocol. The result of the proposed protocol shows an improvement to the packet delivery rate by 15%

An ultra-low duty cycle sleep scheduling protocol stack for wireless sensor networks

A wireless sensor network is a distributed network system consisting of miniature spatially distributed autonomous devices designed for using sensors to sense the environment and cooperatively perform a specific goal. Each sensor node contains a limited power source, a sensor and a radio through which it can communicate with other sensor nodes within its communication radius. Since these sensor nodes may be deployed in inaccessible terrains, it might not be possible to replace their power sources. The radio transceiver is the hardware component that uses the most power in a sensor node and the optimisation of this element is necessary to reduce the overall energy consumption. In the data link layer there are several major sources of energy waste which should be minimised to achieve greater energy efficiency: idle listening, overhearing, over-emitting, network signalling overhead, and collisions. Sleep scheduling utilises the low-power sleep state of a transceiver and aims to reduce energy wastage caused by idle listening. Idle listening occurs when the radio is on, even though there is no data to transmit or receive. Collisions are reduced by using medium reservation and carrier sensing; collisions occur when there are simultaneous transmissions from several nodes that are within the interference range of the receiver node. The medium reservation packets include a network allocation vector field which is used for virtual carrier sensing which reduces overhearing. Overhearing occurs when a node receives and decodes packets that are not destined to it. Proper scheduling can avoid energy wastage due to over-emitting; over-emitting occurs when a transmitter node transmits a packet while the receiver node is not ready to receive packets. A protocol stack is proposed that achieves an ultra-low duty cycle sleep schedule. The protocol stack is aimed at large nodal populations, densely deployed, with periodic sampling applications. It uses the IEEE 802.15.4 Physical Layer (PHY) standard in the 2.4 GHz frequency band. A novel hybrid data-link/network cross-layer solution is proposed using the following features: a global sleep schedule, geographical data gathering tree, Time Division Multiple Access (TDMA) slotted architecture, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), Clear Channel Assessment (CCA) with a randomised contention window, adaptive listening using a conservative timeout activation mechanism, virtual carrier sensing, clock drift compensation, and error control. AFRIKAANS : 'n Draadlose sensor-netwerk is 'n verspreide netwerk stelsel wat bestaan uit miniatuur ruimtelik verspreide outonome toestelle wat ontwerp is om in harmonie saam die omgewing te meet. Elke sensor nodus besit 'n beperkte bron van energie, 'n sensor en 'n radio waardeur dit met ander sensor nodusse binne hulle kommunikasie radius kan kommunikeer. Aangesien hierdie sensor nodusse in ontoeganklike terreine kan ontplooi word, is dit nie moontlik om hulle kragbronne te vervang nie. Die radio is die hardeware komponent wat van die meeste krag gebruik in 'n sensor nodus en die optimalisering van hierdie element is noodsaaklik vir die verminder die totale energieverbruik. In die data-koppelvlak laag is daar verskeie bronne van energie vermorsing wat minimaliseer moet word: ydele luister, a uistering, oor-uitstraling, oorhoofse netwerk seine, en botsings. Slaap-skedulering maak gebruik van die lae-krag slaap toestand van 'n radio met die doel om energie vermorsing wat veroorsaak word deur ydele luister, te verminder. Ydele luister vind plaas wanneer die radio aan is selfs al is daar geen data om te stuur of ontvang nie. Botsings word verminder deur medium bespreking en draer deteksie; botsings vind plaas wanneer verskeie nodusse gelyktydig data stuur. Die medium bespreking pakkies sluit 'n netwerk aanwysing vektor veld in wat gebruik word vir virtuele draer deteksie om a uistering te verminder. Afluistering vind plaas wanneer 'n nodus 'n pakkie ontvang en dekodeer maar dit was vir 'n ander nodus bedoel. Behoorlike skedulering kan energie verkwisting as gevolg van oor-uistraling verminder; oor-uistraling gebeur wanneer 'n sender nodus 'n pakkie stuur terwyl die ontvang nog nie gereed is nie. 'n Protokol stapel is voorgestel wat 'n ultra-lae slaap-skedule dienssiklus het. Die protokol is gemik op draadlose sensor-netwerke wat dig ontplooi, groot hoeveelhede nodusse bevat, en met periodiese toetsing toepassings. Dit maak gebruik van die IEEE 802.15.4 Fisiese-Laag standaard in die 2.4 GHz frekwensie band. 'n Nuwe baster datakoppelvlak/netwerk laag oplossing is voorgestel met die volgende kenmerke: globale slaap-skedulering, geogra ese data rapportering, Tyd-Verdeling-Veelvuldige-Toegang (TVVT) gegleufde argitektuur, Draer-Deteksie-Veelvuldige-Toegang met Botsing-Vermyding (DDVT/BV), Skoon-Kanaal-Assessering (SKA) met 'n wisselvallige twis-tydperk, aanpasbare slaap-skedulering met 'n konserwatiewe aktiverings meganisme, virtuele draer-deteksie, klok-wegdrywing kompensasie, en fout beheer. CopyrightDissertation (MEng)--University of Pretoria, 2012.Electrical, Electronic and Computer Engineeringunrestricte

Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

TRACKING OF MOVING OBJECT IN WIRELESS SENSOR NETWORK

A Wireless Sensor Network is a collection of sensor nodes distributed into a network to monitor the environmental conditions and send the sensed data to the Base Station. Wireless Sensor Network is one of the rapidly developing area in which energy consumption is the most important aspect to be considered while tracking, monitoring, reporting and visualization of data. An Energy Efficient Prediction-based Clustering algorithm is proposed to track the moving object in wireless sensor network. This algorithm reduces the number of hops between transmitter and receiver nodes and also the number of transmitted packets. In this method, the sensor nodes are statically placed and clustered using LEACH-R algorithm. The Prediction based clustering algorithm is applied where few nodes are selected for tracking which uses the prediction mechanism to predict the next location of the moving object. The Current Location of the target is found using Trilateration algorithm. The Current Location or Predicted Location is sent to active Cluster Head from the leader node or the other node. Based on which node send the message to the Cluster Head, the Predicted or Current Location will be sent to the base station. In real time, the proposed work is applicable in traffic tracking and vehicle tracking. The experiment is carried out using Network Stimulator-2 environment. Simulation result shows that the proposed algorithm gives a better performance and reduces the energy consumption

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

EMMON - EMbedded MONitoring

Despite the steady increase in experimental deployments, most of research work on WSNs has focused only on communication protocols and algorithms, with a clear lack of effective, feasible and usable system architectures, integrated in a modular platform able to address both functional and non–functional requirements. In this paper, we outline EMMON [1], a full WSN-based system architecture for large–scale, dense and real–time embedded monitoring [3] applications. EMMON provides a hierarchical communication architecture together with integrated middleware and command and control software. Then, EM-Set, the EMMON engineering toolset will be presented. EM-Set includes a network deployment planning, worst–case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset was crucial for the development of EMMON which was designed to use standard commercially available technologies, while maintaining as much flexibility as possible to meet specific applications requirements. Finally, the EMMON architecture has been validated through extensive simulation and experimental evaluation, including a 300+ nodes testbed