coverage, one of the most important performance metrics for wireless sensor networks, reflects on how well a sensor field is monitored. coverage problem is a devoted study of a node placement optimization problem in t...
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coverage, one of the most important performance metrics for wireless sensor networks, reflects on how well a sensor field is monitored. coverage problem is a devoted study of a node placement optimization problem in the coverage configuration before network deployment, where the objective is to find the optimal locations to place sensor nodes, such that the number of nodes (or the network cost) can be minimized and the coverage requirements can be satisfied. In this paper, we propose a harmony search (HS)-based deployment algorithm that can locate the optimal number of sensor nodes as well as their optimal locations for maximizing the network coverage and minimizing the network cost. The ability of HS is modified to automatically evolve the appropriate number of sensor nodes as well as their optimal locations. This can be accomplished by integrating the concept of adaptable length encoding in each solution vector to represent a variable number of candidate sensor nodes. Network coverage ratio, number of sensor nodes, and minimum distance between sensor nodes are the chief elements of a new objective function that has been offered to confirm the choice of the optimal number of sensor nodes and their positions. Experimental results show the ability of the proposed algorithm to find the appropriate number of sensor nodes and their locations. Furthermore, a comparative study with a metaheuristic Genetic-based algorithm and a random deployment technique has also been conducted and its results confirm the superiority of the proposed algorithm.
In this paper, the problem of maintaining sensing coverage by keeping a small number of active sensor nodes and a small amount of energy consumption in a wireless sensor network is studied. As opposed to the uniform s...
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In this paper, the problem of maintaining sensing coverage by keeping a small number of active sensor nodes and a small amount of energy consumption in a wireless sensor network is studied. As opposed to the uniform sensing model previously, we consider a large number of sensors with adjustable sensing radius that are randomly deployed to monitor a target area. A novel coverage control scheme based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed in a heterogeneous sensor network. By devising a cluster-based architecture, the algorithm is applied in a distributed way. Furthermore, an ameliorated binary coding is addressed to represent both sensing radius adjustment and sensor selection. Numerical and simulation results validate that the procedure to find the optimal balance point among the maximum coverage rate, the least energy consumption, as well as the minimum number of active nodes is fast and effective. (C) 2008 Elsevier Ltd. All rights reserved.
Exotic pests can cause US$1.4 trillion financial damage per year and threaten food security. Biological control is a natural phenomenon that regulates the number of plants and animals by means of natural enemies. The ...
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Exotic pests can cause US$1.4 trillion financial damage per year and threaten food security. Biological control is a natural phenomenon that regulates the number of plants and animals by means of natural enemies. The use of unmanned aerial vehicles (UAV) as a support platform for biological control is promising, since it can reduce operating costs and transposition of natural barriers, such as rivers and venomous animals. However, capsules with natural enemies are spread by a remotely piloted UAV and autonomous UAVs in a zigzag pattern, which incur low coverage efficiency and cannot cover areas of any shape. This article proposes an algorithm that calculates capsule deposition sites of areas of any shape. In the most complex situation, the algorithm showed 1.54% more of effectively covered area, 9.54% higher coverage efficiency, and 104.88% lower inefficiency, guaranteed 7.16% protection of the edge region, and required 13.56% of released capsules. Therefore, UAVs can be used for an efficient distribution of capsules for biological control in areas of any shape. Their main impacts are potential cost savings by the release of fewer capsules and better coverage of the border of the crop field.
Artificial plant optimization algorithm (APOA) is a recent proposed evolutionary computation in which the growing process of one tree is mapped into the optimized problem. In the standard version of APOA, the light re...
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Artificial plant optimization algorithm (APOA) is a recent proposed evolutionary computation in which the growing process of one tree is mapped into the optimized problem. In the standard version of APOA, the light responsive curve of photosynthesis operator is selected as rectangular hyperbolic model which is one general one. However, different light responsive curve may result in different performance, therefore, a hybrid photosynthesis operator is designed which combines three different light responsive curves: parabola model, updated rectangular hyperbolic model and straight line model. To testify the performance of this hybrid photosynthesis operator, the coverage optimization problem of wireless sense networks is used to test. Simulation results show it is effective than the standard version of APOA.
For efficient large-scale Web crawlers, URL duplication checking is an important technique since it is a significant bottleneck. In this paper, we propose a new URL duplication checking technique for a parallel Web cr...
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For efficient large-scale Web crawlers, URL duplication checking is an important technique since it is a significant bottleneck. In this paper, we propose a new URL duplication checking technique for a parallel Web crawler;we call it full-coverage two level URL duplication checking (full-coverage-2L-UDC). Full-coverage-2L-UDC provides efficient URL duplication checking while ensuring maximum coverage. First, we propose two-level URL duplication checking (2L-UDC). It provides efficiency in URL duplication checking by communicating at the Web site level rather than at the Web page level. Second, we present a solution for the so-called coverage problem, which is directly related to the recall of the search engine. It is the first solution for the coverage problem in the centralized parallel architecture. Third, we propose an architecture, FC2-LUDCbot, for a centralized parallel crawler using full-coverage-2L-UDC. We build a seven-agent FC2L-UDCbot for extensive experiments. We show that the crawling speed of FC2L-UDCbot is approximately proportional to the number of agents (Le., FC2L-UDCbot is faster than a single-machine crawler by 6.9 times). Full-coverage-2L-UDC allows FC2L-UDCbot to be scalable to the number of agents since it effectively deals with the overheads incurred in a parallel environment. Through an in-depth analysis, we construct a cost model for estimating the crawling speed of a scaled-up crawler. Using the model, we show that FC2L-UDCbot can crawl Google-scale Web pages within several days using dozens of agents.
The paper proposes a simulation-based procedure to determine the system reliability of a lamp problem. Suppose we have k lamps to light up a room, and each lamp can light a circular area of radius r. The system reliab...
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The paper proposes a simulation-based procedure to determine the system reliability of a lamp problem. Suppose we have k lamps to light up a room, and each lamp can light a circular area of radius r. The system reliability is the probability that there is no dark area in the room during time t. We obtain the system reliability function and the expected system lifetime through a simulation when the reliability and the coverage radius of the lamps are given. A Monte Carlo test method and an Intersection test method are used to check the system state (working or failure) for different situations. In numerical examples, Kaplan-Meier and Nelson estimators determine the system reliability function from system failure times generated by the simulation. Additionally, we compare the two methods with numerical examples.
In this study, we aim to cover a sensing area by deploying a minimum number of wireless sensors while maintaining the connectivity between the deployed sensors. The problem may be reduced to a two-dimensional critical...
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In this study, we aim to cover a sensing area by deploying a minimum number of wireless sensors while maintaining the connectivity between the deployed sensors. The problem may be reduced to a two-dimensional critical coverage problem which is an NP-Complete problem. We develop an integer linear programming model to solve the problem optimally. We also propose a local search (LS) algorithm and a genetic algorithm (GA) as approximate methods. We verify by computational experiments that the integer linear model, using Cplex, is able to provide an optimal solution of all our small and medium size problems. We also show that the proposed methods outperform some regular sensor deployment patterns. (C) 2014 Elsevier Ltd. All rights reserved.
In wireless sensor networks, query execution over a specific geographical region is an essential function for collecting sensed data. However, sensor nodes deployed in sensor networks have limited battery power. Hence...
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In wireless sensor networks, query execution over a specific geographical region is an essential function for collecting sensed data. However, sensor nodes deployed in sensor networks have limited battery power. Hence, the minimum number of connected sensor nodes that covers the queried region in a sensor network must be determined. This paper proposes an efficient distributed protocol to find a subset of connected sensor nodes to cover the queried region. Each node determines whether to be a sensing node to sense the queried region according to its priority. The proposed protocol can efficiently construct a subset of connected sensing nodes and respond the query request to the sink node. In addition, the proposed protocol is extended to solve the k-coverage request. Simulation results show that our protocol is more efficient and has a lower communication overhead than the existing protocol.
Wireless sensor networks have drawn considerable attention among researchers for providing a low-cost framework for Intelligent Transport Systems. coverage problem in wireless sensor networks measures quality a region...
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Wireless sensor networks have drawn considerable attention among researchers for providing a low-cost framework for Intelligent Transport Systems. coverage problem in wireless sensor networks measures quality a region or parts of it is sensed by the sensors. Definition of coverage metric depends on the applications for which sensors are deployed. In this paper, we introduce a new quality control metric/measure called road coverage to partially cover road networks. It can be used for measuring the efficiency of a sensor network, which is deployed for tracking moving/mobile objects in a road network. First, we propose different definitions of road coverage metrics. It is shown that the problem of deploying minimum number of sensors to achieve road coverage is NP-hard. It motivates to design centralized approximate solution. For axis-parallel road segments constant factor approximation algorithms are proposed for finding proper sensors positions. Experimental performance analyses of our algorithms are carried out through extensive simulations.
Deploying minimum sensors to construct a wireless sensor network such that critical areas in a sensing field can be fully covered has received much attention recently. In previous studies, a sensing field is divided i...
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Deploying minimum sensors to construct a wireless sensor network such that critical areas in a sensing field can be fully covered has received much attention recently. In previous studies, a sensing field is divided into square grids, and the sensors can be deployed only in the center of the grids. However, in reality, it is more practical to deploy sensors in any position in a sensing field. Moreover, the number of sensors may be limited due to a limited budget. This motivates us to study the problem of using limited sensors to construct a wireless sensor network such that the total weight of the covered critical square grids is maximized, termed the weighted-critical-square-grid coverage problem, where the critical grids are weighted by their importance. A reduction, which transforms our problem into a graph problem, termed the constrained node-weighted Steiner tree problem, is proposed and used to solve our problem. In addition, three heuristics, including the greedy algorithm (GA), the group-based algorithm (GBA), and the profit-based algorithm (PBA), are proposed for the constrained node-weighted Steiner tree problem. Simulation results show that the proposed reduction with the PBA provides better performance than the others. (C) 2015 Elsevier B.V. All rights reserved.
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