This paper considers the problem of constructing data aggregation trees in wireless sensor networks (WSNs)for a group of sensor nodes to send collected information to a single sink *** data aggregation tree contains t...
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This paper considers the problem of constructing data aggregation trees in wireless sensor networks (WSNs)for a group of sensor nodes to send collected information to a single sink *** data aggregation tree contains the sink node,all the source nodes,and some other non-source *** goal of constructing such a data aggregation tree is to minimize the number of non-source nodes to be included in the tree so as to save *** prove that the data aggregation tree problem is NP-hard and then propose an approximation algorithm with a performance ratio of four and a greedy *** also give a distributed version of the approximation *** simulations are performed to study the performance of the proposed *** results show that the proposed algorithms can find a tree of a good approximation to the optimal tree and has a high degree of scalability.
The Correlation Clustering Problem(CorCP) is a significant clustering problem based on the similarity of *** has significant applications in different fields,such as machine learning,biology,and data mining,and many d...
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The Correlation Clustering Problem(CorCP) is a significant clustering problem based on the similarity of *** has significant applications in different fields,such as machine learning,biology,and data mining,and many different problems in other *** this paper,the Balanced 2-CorCP(B2-CorCP) is introduced and examined,and a new interesting variant of the CorCP is *** goal of this clustering problem is to partition the vertex set into two clusters with equal size,such that the number of disagreements is *** first present a polynomial time algorithm for the B2-CorCP on M-positive edge dominant graphs(M≥ 3).Then,we provide a series of numerical experiments,and the results show the effectiveness of our algorithm.
Motivated by a transit line planning problem in transportation systems, we investigate the following capacitated assignment problem under a budget constraint. Our model involves L bins and P items. Each bin l has a ut...
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Motivated by a transit line planning problem in transportation systems, we investigate the following capacitated assignment problem under a budget constraint. Our model involves L bins and P items. Each bin l has a utilization cost cl and an nl-dimensional capacity vector. Each item p has an nl-dimensional binary weight vector r(lp), where the 1s in r(lp) (if any) appear in consecutive positions, and its assignment to bin l yields a reward v(lp). The objective is to maximize total rewards through an assignment that satisfies three constraints: (i) the total weights of assigned items do not violate any bin's capacity;(ii) each item is assigned to at most one open bin;and (iii) the overall utilization costs remain within a total budget B. We propose the first randomized rounding algorithm with a constant approximation ratio for this problem. We then apply our framework to the motivating transit line planning problem, presenting corresponding models and conducting numerical experiments using real-world data. Our results demonstrate significant improvements over previous approaches in addressing this critical transportation challenge. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
In this paper we consider how to collect data from sensors deployed in the Euclidean plane in a time-efficient way. We assume that all sensors could adjust their transmission ranges and aggregate data received from ot...
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In this paper we consider how to collect data from sensors deployed in the Euclidean plane in a time-efficient way. We assume that all sensors could adjust their transmission ranges and aggregate data received from other sensors. We adopt a collision-free transmission model using proper schedules for data transmission. We study the problem of finding the schedule under which data from all sensors could be transmitted to the data sink in the minimal time. We propose an approximation algorithm for this NP-hard problem whose performance ratio is bounded by a constant. This significantly improves the existing approximation algorithm that does not have a constant performance ratio.
A vertex subset S of a given graph G = (V, E) is called a connected k-path vertex cover (CVCPk) if every k-path of G contains at least one vertex from S, and the subgraph of G induced by S is connected. This concept h...
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A vertex subset S of a given graph G = (V, E) is called a connected k-path vertex cover (CVCPk) if every k-path of G contains at least one vertex from S, and the subgraph of G induced by S is connected. This concept has its background in the field of security and supervisory and the computation of a minimum CVCPk is NP-hard. In this paper, we give a (2 alpha + 1/2)-approximation algorithm for MinCVCP(3), where alpha is the performance ratio of an algorithm for MinVCP(3). (C) 2020 Elsevier B.V. All rights reserved.
In this paper, we consider the wireless sensor network in which the power of each sensor is adjustable. Given a set of sensors and a set of targets, we study a problem of minimizing the total power such that the cover...
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In this paper, we consider the wireless sensor network in which the power of each sensor is adjustable. Given a set of sensors and a set of targets, we study a problem of minimizing the total power such that the coverage of targets meets partial multi-cover requirement, that is, there are at least a given number of targets each covered by a given number of sensors (this number is called the covering requirement for the target). This is called the minimum power partial multi-cover problem (MinPowerPMC) in a wireless sensor network. Under the assumption that the covering requirements for all targets are upper bounded by a constant, we design the first PTAS for the MinPowerPMC problem, that is, for any epsilon > 0, a polynomial-time (1 + epsilon)-approximation.
Given a set of points on a line, a set of intervals along the line and an integer k, each point p is associated with a covering requirement cr(p), the goal of the minimum interval partial multi-cover (MinIPMC) problem...
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Given a set of points on a line, a set of intervals along the line and an integer k, each point p is associated with a covering requirement cr(p), the goal of the minimum interval partial multi-cover (MinIPMC) problem is to select the minimum number of intervals to fully cover at least k points, where a point p is fully covered if it belongs to at least cr(p) selected intervals. This paper presents a 2-approximation algorithm for the MinIPMC problem.
In Wireless Sensor Network (WSN), sensors are deployed to sense useful data from environment. To prolong the sensor network lifetime in large-scale network, mobile sinks are employed for collecting data from the senso...
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In Wireless Sensor Network (WSN), sensors are deployed to sense useful data from environment. To prolong the sensor network lifetime in large-scale network, mobile sinks are employed for collecting data from the sensors directly. The major drawback of the system is slow speed of the mobile sinks, which causes long data gathering delay from the sensors. Since, sensors have limited memory and hence it causes buffer overflow in the sensors. Therefore, to avoid buffer overflow the data must be gathered by the mobile sinks within a predefined time interval. Data gathering from mobile sensors using mobile sinks is more challenging problem than data gathering from static sensors. A set of mobile sensors are moving arbitrarily on a set of predefined paths. Our objective is to collect data periodically from all mobile sensors using minimum number of mobile sinks and subsequently the mobile sinks visit a base station (BS) for final data delivery. We show that the problem is NP-hard and two approximation algorithms are proposed. We extend the proposed algorithms, where mobile sensors can deliver their sensed data to mobile sink within their circular communication regions and present a recovery algorithm from mobile sink's failure. We analyze the performance and time complexity of the proposed algorithms. (C) 2018 Elsevier B.V. All rights reserved.
We consider a bistatic radar sensor network that consists of multiple separated radar transmitters and radar receivers, which are deployed to detect targets among a set of points of interest. Any transmitter-receiver ...
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We consider a bistatic radar sensor network that consists of multiple separated radar transmitters and radar receivers, which are deployed to detect targets among a set of points of interest. Any transmitter-receiver pair with the same frequency forms a bistatic radar. In contrast to the disk-based sensing model in a traditional sensor network, the detection probability of a bistatic radar depends on both locations of the transmitter and receiver. Given the radar transmitters' locations and illuminating frequencies, we study the problem of joint radar receiver placement and frequency selection to maximize the target detection probability. We first study the case where there is a set of candidate locations to place the radar receivers, and propose a simple algorithm with approximation ratio at least 0.63. We then consider the case where there is no constraint for radar receivers' locations, and develop an approximation algorithm which is provably close to optimal. Finally, the numerical results are presented to show the efficacy of our algorithms.
In this paper, we consider the parallel-machine scheduling problem with release dates and submodular rejection penalties. In this problem, we are given m identical parallel machines and n jobs. Each job has a processi...
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In this paper, we consider the parallel-machine scheduling problem with release dates and submodular rejection penalties. In this problem, we are given m identical parallel machines and n jobs. Each job has a processing time and a release date. A job is either rejected, in which case a rejection penalty has to be paid, or accepted and processed on one of the m identical parallel machines. The objective is to minimize the sum of the makespan of the accepted jobs and the rejection penalty of the rejected jobs which is determined by a submodular function. Our main work is to design a 2-approximation algorithm based on the primal-dual framework.
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