Column generation algorithm for sensor coverage scheduling under bandwidth constraints (original) (raw)
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A Column Generation based Heuristic for Maximum Lifetime Coverage in Wireless Sensor Networks
Several studies in recent years have considered many strategies for increasing sensor network lifetime. We focus on a centralised management scheme where a large number of sensors are randomly deployed in a region of interest to monitor a set of targets and we propose an adaptive scheduling by dividing sensors into non-disjoint cover sets, each cover set being active in different period of time. In this paper, we design a column generation (CG) method based heuristic for efficiently solving the maximum lifetime coverage problem. We first model the problem with a linear programming (LP) formulation for non-disjoint cover sets where the objective is to maximise the sum of activation times of cover sets, with respect the sensor's battery lifetime. As the number of cover sets may be exponential to the number of sensors and targets, an initial set of cover sets is constructed and other cover sets are generated through the resolution of an auxiliary problem formulated as a integer pro...
An exact approach for maximizing the lifetime of sensor networks with adjustable sensing ranges
Computers & Operations Research, 2012
This paper addresses the problem of target coverage for wireless sensor networks, where the sensing range of sensors can vary, thereby saving energy when only close targets need to be monitored. Two versions of this problem are addressed. In the first version, sensing ranges are supposed to be continuously adjustable (up to the maximum sensing range). In the second version, sensing ranges have to be chosen among a set of predefined values common to all sensors. An exact approach based on a column generation algorithm is proposed for solving these problems. The use of a genetic algorithm within the column generation scheme significantly decreases computation time, which results in an efficient exact approach.
A Column Generation based Heuristic to extend Lifetime in Wireless Sensor Network
Sensors & Transducers, 2012
Lifetime Optimization has received a lot of interest in wireless sensor networks. In our study we propose an energy-aware centralized method by organizing the nodes in non-disjoint cover sets where each cover set is capable of monitoring all the targets of the region of interest and by activate these cover sets successively. We first model the problem with a linear programming (LP) formulation for non-disjoint cover sets where the objective is to maximize the total work time of all cover sets, with respect the sensor's battery lifetime. As the number of cover sets may be huge, exponential to the number of sensors and targets, we develop a resolution method based on a column generation (CG) process. This method requires the resolution of an auxiliary problem formulated as an integer programming (IP) problem. We propose a heuristic for addressing the auxiliary problem which produces very good solutions in lower computational times compared to an exact resolution as shown in the si...
Journal of Network and Computer Applications, 2015
In this paper we face the problem of maximizing the amount of time over which a set of target points, located in a given geographic region, can be monitored by means of a wireless sensor network. The problem is well known in the literature as Maximum Network Lifetime Problem (MLP). In the last few years the problem and a number of variants have been tackled with success by means of different resolution approaches, including exact approaches based on column generation techniques. In this work we propose an exact approach which combines a column generation approach with a genetic algorithm aimed at solving efficiently its separation problem. The genetic algorithm is specifically aimed at the Maximum Network α-Lifetime Problem (α-MLP), a variant of MLP in which a given fraction of targets is allowed to be left uncovered at all times; however, since α-MLP is a generalization of MLP, it can be used to solve the classical problem as well. The computational results, obtained on the benchmark instances, show that our approach overcomes the algorithms, available in literature, to solve both MLP and α-MLP.
The aim of the Connected Maximum Lifetime Problem is to define a schedule for the activation intervals of the sensors deployed inside a region of interest, such that at all times the activated sensors can monitor a set of interesting target locations and route the collected information to a central base station, while maximizing the total amount of time over which the sensor network can be operational. Complete or partial coverage of the targets are taken into account. To optimally solve the problem, we propose a column generation approach which makes use of an appropriately designed genetic algorithm to overcome the difficulty of solving the subproblem to optimality in each iteration. Moreover, we also devise a heuristic by stopping the column generation procedure as soon as the columns found by the genetic algorithm do not improve the incumbent solution. Comparisons with previous approaches proposed in the literature show our algorithms to be highly competitive, both in terms of solution quality and computational time.
European Journal of Operational Research, 2012
Wireless sensor networks involve many different real-world contexts, such as monitoring and control tasks for traffic, surveillance, military and environmental applications, among others. Usually, these applications consider the use of a large number of low-cost sensing devices to monitor the activities occurring in a certain set of target locations. We want to individuate a set of covers (that is, subsets of sensors that can cover the whole set of targets) and appropriate activation times for each of them in order to maximize the total amount of time in which the monitoring activity can be performed (network lifetime), under the constraint given by the limited power of the battery contained in each sensor. A variant of this problem considers that each sensor can be activated in a certain number of alternative power levels, which determine different sensing ranges and power consumptions. We present some heuristic approaches and an exact approach based on the Column Generation technique. An extensive experimental phase proves the advantage in terms of solution quality of using adjustable sensing ranges with respect to the classical single range scheme.
Heuristic Optimization of a Sensor Network Lifetime Under Coverage Constraint
Springer eBooks, 2017
Control of a set of sensors disseminated in the environment to monitor activity is a subject of the presented research. Due to redundancy in the areas covered by sensor monitoring ranges a satisfying level of coverage can be obtained even if not all the sensors are on. Sleeping sensors save their energy, thus, one can propose schedules defining activity for each of sensors over time which offer a satisfying level of coverage for a period of time longer than a lifetime of a single sensor. A new heuristic algorithm is proposed which searches for such schedules maximizing the lifetime of the sensor network under a coverage constraint. The algorithm is experimentally tested on a set of test cases and effectiveness of its components is presented and statistically verified.
α-Coverage to extend network lifetime on wireless sensor networks
Optimization Letters, 2013
An important problem in the context of wireless sensor networks is the Maximum Network Lifetime Problem (MLP): find a collection of subset of sensors (cover) each covering the whole set of targets and assign them an activation time so that network lifetime is maximized. In this paper we consider a variant of MLP, where we allow each cover to neglect a certain fraction (1 − α) of the targets. We analyze the problem and show that the total network lifetime can be hugely improved by neglecting a very small portion of the targets. An exact approach, based on a Column Generation scheme, is presented and a heuristic solution algorithm is also provided to initialize the approach. The proposed approaches are tested on a wide set of instances. The experimentation shows the effectiveness of both the proposed problems and solution algorithms in extending network lifetime and improving target coverage time when some regularity conditions are taken into account.
Coverage problems in wireless sensor networks: designs and analysis
International Journal of Sensor Networks, 2008
Recently, a concept of wireless sensor networks has attracted much attention due to its widerange of potential applications. Wireless sensor networks also pose a number of challenging optimization problems. One of the fundamental problems in sensor networks is the coverage problem, which reflects the quality of service that can be provided by a particular sensor network. The coverage concept is defined from several points of view due to a variety of sensors and a wide-range of their applications. Several different designs and formulations of coverage problems have been proposed. They are subject to various topics such as types of interest regions (areas vs. targets) and different objectives (maximum network lifetime, minimum coverage breach) with other constraints. In this paper, we survey the state-of-the-art coverage formulations, present an overview and analysis of the solutions proposed in recent research literature.