15,837 research outputs found

    Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

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    The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

    Self-organization of Nodes using Bio-Inspired Techniques for Achieving Small World Properties

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    In an autonomous wireless sensor network, self-organization of the nodes is essential to achieve network wide characteristics. We believe that connectivity in wireless autonomous networks can be increased and overall average path length can be reduced by using beamforming and bio-inspired algorithms. Recent works on the use of beamforming in wireless networks mostly assume the knowledge of the network in aggregation to either heterogeneous or hybrid deployment. We propose that without the global knowledge or the introduction of any special feature, the average path length can be reduced with the help of inspirations from the nature and simple interactions between neighboring nodes. Our algorithm also reduces the number of disconnected components within the network. Our results show that reduction in the average path length and the number of disconnected components can be achieved using very simple local rules and without the full network knowledge.Comment: Accepted to Joint workshop on complex networks and pervasive group communication (CCNet/PerGroup), in conjunction with IEEE Globecom 201

    Scheduling for Multi-Camera Surveillance in LTE Networks

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    Wireless surveillance in cellular networks has become increasingly important, while commercial LTE surveillance cameras are also available nowadays. Nevertheless, most scheduling algorithms in the literature are throughput, fairness, or profit-based approaches, which are not suitable for wireless surveillance. In this paper, therefore, we explore the resource allocation problem for a multi-camera surveillance system in 3GPP Long Term Evolution (LTE) uplink (UL) networks. We minimize the number of allocated resource blocks (RBs) while guaranteeing the coverage requirement for surveillance systems in LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an Integer Linear Programming formulation for general cases to find the optimal solution. Moreover, we present a baseline algorithm and devise an approximation algorithm to solve the problem. Simulation results based on a real surveillance map and synthetic datasets manifest that the number of allocated RBs can be effectively reduced compared to the existing approach for LTE networks.Comment: 9 pages, 10 figure

    Improving energy consumption of commercial building with IoT and machine learning

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    Optimal Deployments of UAVs With Directional Antennas for a Power-Efficient Coverage

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    To provide a reliable wireless uplink for users in a given ground area, one can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another application, one can use UAVs to collect data from sensors on the ground. For a power-efficient and scalable deployment of such flying BSs, directional antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We consider a large-scale wireless path-loss model with a realistic angle-dependent radiation pattern for the directional antennas. Based on such a model, we determine the optimal 3-D deployment of N UAVs to minimize the average transmit-power consumption of the users in a given target area. The users are assumed to have identical transmitters with ideal omnidirectional antennas and the UAVs have identical directional antennas with given half-power beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For uniformly distributed ground users, we show that the UAVs have to share a common flight height in an optimal power-efficient deployment. We also derive in closed-form the asymptotic optimal common flight height of NN UAVs in terms of the area size, data-rate, bandwidth, HPBW, and path-loss exponent

    Energy Harvesting Wireless Communications: A Review of Recent Advances

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    This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer
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