Hybrid Mac Protocol With Intra- Cluster Communications For Extending Wireless Sensor Network Lifetimes

Sensor network features low-cost tiny sensor devices with wireless network capability, limited battery energy and resource constraints. The communication in Wireless Sensor Network (WSN) is handled by routing protocols. Among the WSN routing protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH) is widely used benchmark cluster-based routing protocol. LEACH relies on the cluster head to perform data aggregation and transmission to the base stations. However, the performance of LEACH deteriorates with large-scale networks. Moreover, most of the current LEACH-based protocols uses Time Division Multiple Access Medium Access Control (TDMA MAC). Where slot for each cluster nodes has been assigned, even though some nodes might not have data to broadcast and that wastes the network resources. Furthermore, these protocols do not consider the cluster head (CH) overload problem. This study proposes adaptive clustering hierarchy routing protocol based on LEACH known as Energy-Efficient Scalable Routing Protocol (EESRP). The broad goal of proposing EESRP is to maintain the network-lifetime over the network expansion. EESRP introduces a three-layer hierarchy (i.e. sensors, congregations, and cluster heads) as well as applying multi-hop intra-clustering communication based on a hybrid MAC protocol. The EESRP is developed via a simulation testbed using MATLAB 2015a software. To assess the proposed protocol, a performance evaluation of EESRP with respect to Cell-LEACH, Multi-LEACH and BCDCP protocols is carried out

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Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

Performance Analysis of Hierarchical Routing Protocols in Wireless Sensor Networks

This work focusses on analyzing the optimization strategies of routing protocols with respect to energy utilization of sensor nodes in Wireless Sensor Network (WSNs). Different routing mechanisms have been proposed to address energy optimization problem in sensor nodes. Clustering mechanism is one of the popular WSNs routing mechanisms. In this paper, we first address energy limitation constraints with respect to maximizing network life time using linear programming formulation technique. To check the efficiency of different clustering scheme against modeled constraints, we select four cluster based routing protocols; Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP), and Distributed Energy Efficient Clustering (DEEC). To validate our mathematical framework, we perform analytical simulations in MATLAB by choosing number of alive nodes, number of dead nodes, number of packets and number of CHs, as performance metrics.Comment: NGWMN with 7th IEEE International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

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