161 research outputs found

    Q-LEACH: A New Routing Protocol for WSNs

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    Wireless Sensor Networks (WSNs) with their dynamic applications gained a tremendous attention of researchers. Constant monitoring of critical situations attracted researchers to utilize WSNs at vast platforms. The main focus in WSNs is to enhance network life-time as much as one could, for efficient and optimal utilization of resources. Different approaches based upon clustering are proposed for optimum functionality. Network life-time is always related with energy of sensor nodes deployed at remote areas for constant and fault tolerant monitoring. In this work, we propose Quadrature-LEACH (Q-LEACH) for homogenous networks which enhances stability period, network life-time and throughput quiet significantly

    Unified clustering and communication protocol for wireless sensor networks

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    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

    Hybrid Sine-Cosine Black Widow Spider Optimization based Route Selection Protocol for Multihop Communication in IoT Assisted WSN

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    In the modern era, Internet of Things (IoT) has been a popular research topic and it focuses on interconnecting numerous sensor-based devices primarily for tracking applications and collecting data. Wireless Sensor Networks (WSN) becomes a significant element in IoT platforms since its inception and turns out to be the most ideal platform for deploying various smart city application zones namely disaster management, home automation, intelligent transportation, smart buildings, and other IoT-enabled applications. Clustering techniques were commonly used energy-efficient methods with the main purpose that is to balance the energy between Sensor Nodes (SN). Routing and clustering are Non-Polynomial (NP) hard issues where bio-inspired approaches were used for a known time to solve these issues. This study introduces a Hybrid Sine-Cosine Black Widow Spider Optimization based Route Selection Protocol (HSBWSO-RSP) for Mulithop Communication in IoT assisted WSN. The presented HSBWSO-RSP technique aims to properly determine the routes to destination for multihop communication. Moreover, the HSBWSO-RSP approach enables the integration of variance perturbation mechanism into the traditional BWSO algorithm. Furthermore, the selection of routes takes place by a fitness function comprising Residual Energy (RE) and distance (DIST). The experimental result analysis of the HSBWSO-RSP technique is tested using a series of experimentations and the results are studied under different measures. The proposed methodology achieves 100% packet delivery ratio, no packet loss and 2.33 secs end to end delay. The comparison study revealed the betterment of the HSBWSO-RSP technique over existing routing techniques

    A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

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    The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

    Kinetic Gas Molecule Optimization based Cluster Head Selection Algorithm for minimizing the Energy Consumption in WSN

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    As the amount of low-cost and low-power sensor nodes increases, so does the size of a wireless sensor network (WSN). Using self-organization, the sensor nodes all connect to one another to form a wireless network. Sensor gadgets are thought to be extremely difficult to recharge in unfavourable conditions. Moreover, network longevity, coverage area, scheduling, and data aggregation are the major issues of WSNs. Furthermore, the ability to extend the life of the network, as well as the dependability and scalability of sensor nodes' data transmissions, demonstrate the success of data aggregation. As a result, clustering methods are thought to be ideal for making the most efficient use of resources while also requiring less energy. All sensor nodes in a cluster communicate with each other via a cluster head (CH) node. Any clustering algorithm's primary responsibility in these situations is to select the ideal CH for solving the variety of limitations, such as minimising energy consumption and delay. Kinetic Gas Molecule Optimization (KGMO) is used in this paper to create a new model for selecting CH to improve network lifetime and energy. Gas molecule agents move through a search space in pursuit of an optimal solution while considering characteristics like energy, distance, and delay as objective functions. On average, the KGMO algorithm results in a 20% increase in network life expectancy and a 19.84% increase in energy stability compared to the traditional technique Bacterial Foraging Optimization Algorithm (BFO)

    A Study of Medium Access Control Protocols for Wireless Body Area Networks

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    The seamless integration of low-power, miniaturised, invasive/non-invasive lightweight sensor nodes have contributed to the development of a proactive and unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health monitoring of a patient without any constraint on his/her normal dailylife activities. This monitoring requires low-power operation of invasive/non-invasive sensor nodes. In other words, a power-efficient Medium Access Control (MAC) protocol is required to satisfy the stringent WBAN requirements including low-power consumption. In this paper, we first outline the WBAN requirements that are important for the design of a low-power MAC protocol. Then we study low-power MAC protocols proposed/investigated for WBAN with emphasis on their strengths and weaknesses. We also review different power-efficient mechanisms for WBAN. In addition, useful suggestions are given to help the MAC designers to develop a low-power MAC protocol that will satisfy the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table

    Comparison of Energy Efficient Clustering Protocols in Wireless Sensor Networks –A Review

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    — Wireless sensor networks with hundreds of sensor nodes have emerged in recent years as important platforms for a wide spectrum of monitoring tasks ranging from environmental to military applications. Its growth is expeditiously increasing and that’s why there is an immense field for research in this area. Sensors depend entirely on the trust of their battery for power, which cannot be revitalized or substituted. So the design of energy aware protocol is essential in respect to enhance the network lifetime. LEACH, LEACH C and HEED are energy-efficient hierarchical based protocols that balances the energy expense, saves the node energy and hence prolongs the lifetime of the network. So this paper presents a detailed review and analysis of these energy efficient protocols. Comparison of various network parameters is done in the form of tables and graphs. In the last of the paper conclusions is drawn
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