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Optimal Stop Points for Data Gathering in Sensor Networks with Mobile Sinks
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作者 Junyoung Park Kyoungjin Moon +1 位作者 Sungjoo Yoo sunggu lee 《Wireless Sensor Network》 2012年第1期8-17,共10页
Given a wireless sensor network (WSN) in which a mobile sink is used to collect data from the sensor nodes, this paper addresses the problem of selecting a set of stop points that results in low energy usage by the se... Given a wireless sensor network (WSN) in which a mobile sink is used to collect data from the sensor nodes, this paper addresses the problem of selecting a set of stop points that results in low energy usage by the sensor nodes. This paper assumes an approach in which a mobile sink travels along a fixed path and uses a stop-and-collect protocol since this has previously been shown to be an efficient WSN data collection method. The problem of selecting an optimal set of stop points is shown to be an NP-hard problem. Then, an Integer Linear Programming (ILP) formulation is used to derive an optimal algorithm that can be used for small problem instances. Next, a polynomial-time Tabu-search-based heuristic algorithm is proposed. Simulations are used to compare the energy consumption values, computation times and expected network lifetimes when using the optimal ILP algorithm, the proposed heuristic algorithm and several other possible heuristic algorithms. The results show that the proposed heuristic algorithm results in near-optimal energy usage values with low computation times, thereby making it suitable for large-sized WSNs. 展开更多
关键词 Wireless Sensor Network (WSN) Mobile SINK Energy Efficiency Optimization Tabu Search HEURISTIC
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A Free Market Economy Model for Resource Management in Wireless Sensor Networks
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作者 Byeongwook Bae Junyoung Park sunggu lee 《Wireless Sensor Network》 2015年第6期76-82,共7页
This paper presents a free market economy model that can be used to facilitate fully distributed autonomous control of resources in massive heterogeneous wireless sensor networks (WSNs). In the future, it is expected ... This paper presents a free market economy model that can be used to facilitate fully distributed autonomous control of resources in massive heterogeneous wireless sensor networks (WSNs). In the future, it is expected that WSNs will exist as part of the global Internet of Things (IoT), and different WSNs can work together in a massive network of heterogeneous WSNs in order to solve common problems. Control of valuable processing, sensing and communication resources, determining which nodes will remain awake during specific time periods in order to provide sensing services, and determining which nodes will forward other nodes’ packets are difficult problems that must be dealt with. It is proposed that just as the free market economy model enables the global human society to function reasonably well when individuals simply attempt to trade money and services in order to maximize their individual profits, and a similar model and mechanism should enable a massive network of heterogeneous WSNs to function well in a fully distributed autonomous manner. The main contributions of this paper are the introduction of the free market economy model for use with WSNs, the formal definition of a maximum profit price problem for multihop packet relaying, and the proposal of a distributed genetic algorithm for the solution of the maximum profit price problem. Simulation results show that the proposed distributed solution produces results that are 70% - 80% similar to a pareto optimal solution for this problem. 展开更多
关键词 Distributed CONTROL WSN RESOURCES Free MARKET ECONOMY AUCTION Autonomous CONTROL
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Hardware-Efficient Approximate Dividers for Image Processing in WSN Edge Devices
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作者 Duhwan Kim sunggu lee 《Wireless Sensor Network》 2022年第1期1-22,共22页
This paper proposes a hardware-efficient implementation of division, which is useful for image processing in WSN edge devices. For error-resilient applications such as image processing, accurate calculations can be un... This paper proposes a hardware-efficient implementation of division, which is useful for image processing in WSN edge devices. For error-resilient applications such as image processing, accurate calculations can be unnecessary overhead, and approximate computing that obtains circuit benefits from inaccurate calculations is effective. Since there are studies showing sufficient performance with few bit operations, this paper proposes a combinational arithmetic circuit design of 16 bits or less. The proposed design is an approximate restoring division circuit implemented with a 2-dimensional array of 1-bit subtractor cells. The main drawback of such a design is the long “borrow-chain” that traverses all of the rows of the 2-dimensional subtractor array before a final stable quotient result can be produced, thereby resulting in a long delay and excessive power dissipation. This paper proposes two approximate subtractor cell designs, named ABSC and ADSC, that break this borrow chain: the first in the vertical direction and the second in the horizontal direction, respectively. The proposed approximate divider designs are compared with an accurate design and previous state-of-the-art designs based on accuracy and hardware overhead. The proposed designs have accuracy levels that are close to the best accuracy levels achieved by previous state-of-the-art approximate divider designs. In addition, the proposed ADSC design had the lowest delay, area, and power characteristics. Finally, the implementation of both proposed designs for two practical applications showed that both designs provide sufficient division accuracy. 展开更多
关键词 Approximate Computing DIVISION Energy Efficiency Low Latency Arithmetic
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