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Power efficient monitoring management in sensor networks

Power efficient monitoring management in sensor networks,10.1109/WCNC.2004.1311452,P. Berman,G. Calinescu,C. Shah,A. Zelikovsky

Power efficient monitoring management in sensor networks   (Citations: 58)
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Optimizing the energy consumption in wireless sensor networks has recently become the most important performance objective. We assume the sensor network model in which sensors can interchange idle and active modes. Given monitoring regions, battery life and energy consumption rate for each sensor, we formulate the problem of maximizing sensor network lifetime, i.e., time during which the monitored area is (partially or fully) covered. Our contributions include (1) an efficient data structure to represent the monitored area with at most n2 points guaranteeing the full coverage which is superior to the previously used approach based on grid points, (2) efficient provably good centralized algorithms for sensor monitoring schedule maximizing the total lifetime including (1+ln(1-q)-1)-approximation algorithm for the case when a q-portion of the monitored area is required to cover, e.g., for the 90% area coverage our schedule guarantees to be at most 3.3 times shorter than the optimum, (4) a family of efficient distributed protocols with trade-off between communication and monitoring power consumption, (5) extensive experimental study of the proposed algorithms showing significant advantage in quality, scalability and flexibility.
Conference: Wireless Communications and Networking, IEEE Conference - WCNC , vol. 4, pp. 2329-2334 Vol.4, 2004
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    • ...In [4], the authors have formulated the lifetime problem and suggested another Linear Programming (LP) technique to solve this problem...

    Jacques M. Bahiet al. Distributed Lifetime Optimization in Wireless Sensor Networks

    • ...Efficient monitoring algorithms have been proposed to maximize the covered area while reducing the used energy [12], [13]...
    • ...Solving the problem in static conditions is similar to the minimum set covering problem, which is NP complete [12], [13]...
    • ...Arguably, the most intuitive approach is to formulate the optimization problem as an ILP equation set [12], [13]...
    • ...A good cost function for minimum set covering is to always select the candidate that covers most of the uncovered elements [12]...
    • ...This parameter is similar to traditional priorities in minimum set covering heuristics [12], which choose subsets with many uncovered elements...

    Codruta Istinet al. Stochastic Model-Based Heuristics for Fast Field of View Loss Recovery...

    • ...Area monitoring was previously studied by Berman et al. [1,2] and a superlinear algorithm for finding efficient schedules with a logarithmic approximation ratio was presented...
    • ...Later in [1], Berman et al. argue that area monitoring can be reduced to target monitoring of O(n 2 ) targets for a class of sensor models, given a network...
    • ...In [1,2], Berman et al. discuss the problem of area monitoring without enforcing constraints on the node sets or battery capacities as the previous authors did...
    • ...We refer to this problem as sensor network lifetime problem (SNLP) [1]...
    • ...input: parameter δ ∈ [0, 1], sensor nodes S ,a reaA, sensing range R output: set of covers C, set of corresponding durations t...
    • ...Lemma 1. Let δ ∈ [0, 1]. Algorithm 1 yields a feasible solution to problem (S, 1+ δ) with lifetime T �S , 1+ δ �≥ f · Topt�S , 1� . The running time outside algorithm A is O(|S|)...
    • ...Algorithm 2. Approximation Algorithm input: parameter δ ∈ [0, 1] ,� ∈ (0, 1], sensor nodes S ,a reaA, sensing range R output: set of covers C, set of corresponding durations t...
    • ...Berman et al. stated in [1,2] that the area monitoring problem can be reduced to a target monitoring problem for convex sensing ranges...
    • ...Since covering an area is equal to covering a set of points [1,2], this problem is equal to MCGDC with costs ci = wi and C =1 . �...

    Peter Sanderset al. Lifetime Maximization of Monitoring Sensor Networks

    • ...A number of researchers [4,5,6,11,15] have used this or related problems as an abstraction for the problem of deriving efficient sleep schedules in wireless networks...
    • ...researchers in the wireless networks community have either used heuristics [6], the O(log n)-approximation that works for general graphs [11], or have settled for a fractional solution obtained by solving the LP-relaxation of the problem [4]...

    Saurav Panditet al. Approximation Algorithms for Domatic Partitions of Unit Disk Graphs

    • ...[3,9] and others showed that using non-disjoint covers allows the lifetime to be extended further and this approach has been adopted since...

    Akshaye Dhawanet al. A distributed algorithmic framework for coverage problems in wireless ...

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