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82
Dynamic point coverage problem in wireless sensor networks: a cellular learning automata approach
 Journal of Ad hoc and Sensors Wireless Networks
, 2010
"... One way to prolong the lifetime of a wireless sensor network is to schedule the active times of sensor nodes, so that a node is active only when it is really needed. In the dynamic point coverage problem, which is to detect some moving target points in the area of the sensor network, a node is need ..."
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Cited by 15 (9 self)
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One way to prolong the lifetime of a wireless sensor network is to schedule the active times of sensor nodes, so that a node is active only when it is really needed. In the dynamic point coverage problem, which is to detect some moving target points in the area of the sensor network, a node is needed to be active only when a target point is in its sensing region. A node can be aware of such times using a predicting mechanism. In this paper, we propose a solution to the problem of dynamic point coverage using irregular cellular learning automata. In this method, learning automaton residing in each cell in cooperation with the learning automata residing in its neighboring cells predicts the existence of any target point in the vicinity of its corresponding node in the network. This prediction is then used to schedule the active times of that node. In order to show the performance of the proposed method, computer experimentations have been conducted. The results show that the proposed method outperforms the existing methods such as LEACH, GAF, PEAS and PW in terms of energy consumption.
Routing correlated data with fusion cost in wireless sensor networks
 IEEE Transactions on Mobile Computing
"... In this paper, we propose a routing algorithm called Minimum Fusion Steiner Tree (MFST), for energy efficient data gathering with aggregation (fusion) in wireless sensor networks. Different from existing schemes, MFST not only optimizes over the data transmission cost, but also incorporates the cost ..."
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Cited by 15 (2 self)
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In this paper, we propose a routing algorithm called Minimum Fusion Steiner Tree (MFST), for energy efficient data gathering with aggregation (fusion) in wireless sensor networks. Different from existing schemes, MFST not only optimizes over the data transmission cost, but also incorporates the cost for data fusion which can be significant for emerging sensor networks with vectorial data and/or security requirements. By employing a randomized algorithm that allows fusion points to be chosen according to the nodes ’ data amount, MFST achieves an approximation ratio of 5 4 log(k + 1), where k denotes the number of source nodes, to the optimal solution for extremely general system setups provided that fusion cost and data aggregation are nondecreasing against the total input data. Consequently, in contrast to algorithms that only excel in full or nonaggregation scenarios without considering fusion cost, MFST can thrive in a wide range of applications.
Analysis of a Predictionbased Mobility Adaptive Tracking Algorithm
"... Abstract — Target tracking in wireless sensor networks requires efficient coordination among sensor nodes. Existing methods have focused on treebased collaboration, selective activation, and group clustering. This paper presents a predictionbased adaptive algorithm for tracking mobile targets. We ..."
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Cited by 14 (1 self)
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Abstract — Target tracking in wireless sensor networks requires efficient coordination among sensor nodes. Existing methods have focused on treebased collaboration, selective activation, and group clustering. This paper presents a predictionbased adaptive algorithm for tracking mobile targets. We use adaptive Kalman filtering to predict the future location and velocity of the target. This location prediction is used to determine the active tracking region which corresponds to the set of sensors that needs to be “lighted”. The velocity prediction is used to adaptively determine the size of the active tracking region, and to modulate the sampling rate as well. In this paper, we quantify the benefits of our approach in terms of energy consumed and accuracy of tracking for different mobility patterns. Our simulation results show that advance resource reservation coupled with adaptively changing the size of the active tracking region and the sampling rate reduces the overall energy consumed for tracking without affecting the accuracy in tracking.
Minimum Cost Data Aggregation with Localized Processing for Statistical Inference
 IN PROC. OF IEEE INFOCOM
, 2008
"... The problem of minimum cost innetwork fusion of measurements, collected from distributed sensors via multihop routing is considered. A designated fusion center performs an optimal statisticalinference test on the correlated measurements, drawn from a Markov random field. Conditioned on the deliver ..."
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Cited by 13 (9 self)
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The problem of minimum cost innetwork fusion of measurements, collected from distributed sensors via multihop routing is considered. A designated fusion center performs an optimal statisticalinference test on the correlated measurements, drawn from a Markov random field. Conditioned on the delivery of a sufficient statistic for inference to the fusion center, the structure of optimal routing and fusion is shown to be a Steiner tree on a transformed graph. This Steinertree reduction preserves the approximation ratio, which implies that any Steinertree approximation can be employed for minimum cost fusion with the same approximation ratio. The proposed fusion scheme involves routing packets of two types viz., raw measurements sent for local processing, and aggregates obtained on combining these processed values. The performance of heuristics for minimum cost fusion are evaluated through theory and simulations, showing a significant saving in routing costs, when compared to routing all the raw measurements to the fusion center.
A learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks. Computer Networks doi:10.1016/j
, 2010
"... The dynamic point coverage problem in wireless sensor networks is to detect some moving target points in the area of the network using as little sensor nodes as possible. One way to deal with this problem is to schedule sensor nodes in such a way that a node is activated only at the times a target p ..."
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Cited by 12 (6 self)
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The dynamic point coverage problem in wireless sensor networks is to detect some moving target points in the area of the network using as little sensor nodes as possible. One way to deal with this problem is to schedule sensor nodes in such a way that a node is activated only at the times a target point is in its sensing region. In this paper we propose SALA, a scheduling algorithm based on learning automata, to deal with the problem of dynamic point coverage. In SALA each node in the network is equipped with a set of learning automata. The learning automata residing in each node try to learn the maximum sleep duration for the node in such a way that the detection rate of target points by the node does not degrade dramatically. This is done using the information obtained about the movement patterns of target points while passing throughout the sensing region of the nodes. We consider two types of target points; events and moving objects. Events are assumed to occur periodically or based on a Poisson distribution and moving objects are assumed to have a static movement path which is repeated periodically with a randomly selected velocity. In order to show the performance of SALA, some experiments have been conducted. The experimental results show that SALA outperforms the existing methods such as LEACH, GAF, PEAS and PW in terms of energy consumption.
EASE: An EnergyEfficient InNetwork Storage Scheme for Object Tracking
 In Proceedings of IEEE SECON’05
, 2005
"... Abstract — Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in location data of tracked objects, this paper studies precisionconstrained approximat ..."
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Cited by 10 (4 self)
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Abstract — Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in location data of tracked objects, this paper studies precisionconstrained approximate queries that trade answer precision for energy efficiency. We develop an Energyconserving Approximate StoragE (EASE) scheme to efficiently answer approximate location queries by keeping errorbounded imprecise location data at some designated storage node. The data impreciseness is captured by a system parameter, i.e., approximation radius. We analyze the performance of EASE in terms of message complexity and derive the optimal setting of approximation radius. We show via extensive simulation experiments that, as compared to a conventional approach, the EASE scheme cuts down the network traffic by up to 96 % and, in most cases, prolongs the network lifetime by a factor of 2−5. I.
Efficient Sensor Network Design for Continuous Monitoring of Moving Objects
 Proceedings of the 3rd International Workshop on Algorithmic Aspects of Wireless Sensor Networks (ALGOSENSORS 2007
, 2007
"... We study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible number of sensors to be deployed, their positions and operation chatacteristics needed to perform the tracking task. To av ..."
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Cited by 10 (4 self)
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We study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible number of sensors to be deployed, their positions and operation chatacteristics needed to perform the tracking task. To avoid an expensive massive deployment, we try to take advantage of possible coverage ovelaps over space and time, by introducing a novel combinatorial model that captures such overlaps. Under this model, we abstract the tracking network design problem by a combinatorial problem of covering a universe of elements by at least three sets (to ensure that each point in the network area is covered at any time by at least three sensors, and thus being localized). We then design and analyze an efficient approximate method for sensor placement and operation, that with high probability and in polynomial expected time achieves a Θ(log n) approximation ratio to the optimal solution. Our network design solution can be combined with alternative collaborative processing methods, to suitably fit different tracking scenaria.
The SelfProtection Problem in Wireless Sensor Networks
"... Wireless sensor networks have recently been suggested for many surveillance applications such as object monitoring, path protection, or area coverage. Since the sensors themselves are important and critical objects in the network, a natural question is whether they need certain level of protection, ..."
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Cited by 10 (2 self)
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Wireless sensor networks have recently been suggested for many surveillance applications such as object monitoring, path protection, or area coverage. Since the sensors themselves are important and critical objects in the network, a natural question is whether they need certain level of protection, so as to resist the attacks targeting on them directly. If this is necessary, then who should provide this protection, and how it can be done? We refer to the above problem as selfprotection, as we believe the sensors themselves are the best (and often the only) candidates to provide such protection. In this paper, we for the first time present a formal study on the selfprotection problems in wireless sensor networks. We show that, if we simply focus on enhancing the quality of field or object covering, the sensors might not necessarily be selfprotected, which in turn makes the system extremely vulnerable. We then investigate different forms of selfprotections, and show that the problems are generally NPcomplete. We develop efficient approximation algorithms for centrallycontrolled sensors. We further extend the algorithms to fully distributed implementation, and introduce a smart sleepscheduling algorithm that minimizes the energy consumption.
A New Storage Scheme for Approximate Location Queries in Object Tracking Sensor Networks
 IEEE Trans. Parallel and Distributed Systems
, 2008
"... Abstract—Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in the location data of tracked objects, this paper studies precisionconstrained approxim ..."
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Cited by 10 (2 self)
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Abstract—Energy efficiency is one of the most critical issues in the design of wireless sensor networks. Observing that many sensor applications for object tracking can tolerate a certain degree of imprecision in the location data of tracked objects, this paper studies precisionconstrained approximate queries that trade answer precision for energy efficiency. We develop an Energyconserving Approximate StoragE (EASE) scheme to efficiently answer approximate location queries by keeping errorbounded imprecise location data at some designated storage node. The data impreciseness is captured by a system parameter called the approximation radius. We derive the optimal setting of the approximation radius for our storage scheme based on the mobility pattern and devise an adaptive algorithm to adjust the setting when the mobility pattern is not available a priori or is dynamically changing. Simulation experiments are conducted to validate our theoretical analysis of the optimal approximation setting. The simulation results show that the proposed EASE scheme reduces the network traffic from a conventional approach by up to 96 percent and, in most cases, prolongs the network lifetime by a factor of 25. Index Terms—Energy efficiency, data dissemination, data storage, location query, wireless sensor network. 1
Design and comparison of lightweight group management strategies in envirosuite
 In DCOSS ’05: International Conference on Distributed Computing in Sensor Networks
, 2005
"... Abstract. Tracking is one of the major applications of wireless sensor networks. EnviroSuite, as a programming paradigm, provides a comprehensive solution for programming tracking applications, wherein moving environmental targets are uniquely and identically mapped to logical objects to raise the l ..."
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Cited by 9 (4 self)
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Abstract. Tracking is one of the major applications of wireless sensor networks. EnviroSuite, as a programming paradigm, provides a comprehensive solution for programming tracking applications, wherein moving environmental targets are uniquely and identically mapped to logical objects to raise the level of programming abstraction. Such mapping is done through distributed group management algorithms, which organize nodes in the vicinity of targets into groups, and maintain the uniqueness and identity of target representation such that each target is given a consistent name. Challenged by tracking fastmoving targets, this paper explores, in a systematic way, various group management optimizations including semidynamic leader election, piggybacked heartbeats, and implicit leader election. The resulting tracking protocol, Lightweight EnviroSuite, is integrated into a surveillance system. Empirical performance evaluation on a network of 200 XSM motes shows that, due to these optimizations, Lightweight EnviroSuite is able to track targets more than 3 times faster than the fastest targets trackable by the original EnviroSuite even when 20 % of nodes fail. 1