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Energy-efficient multiple itinerary planning for mobile agents-based data aggregation in WSNs

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Abstract

Data aggregation is recognized as a key method for reducing the amount of network traffic and the energy consumption on wireless sensor network nodes. Mobile agent (MA) technology represents a distributed computing paradigm which has been proposed as a means for increasing the energy efficiency of data aggregation tasks and addressing the scalability problems of centralized methods. Nevertheless, the itineraries followed by travelling MAs largely determine the overall performance of the data aggregation applications. Along this line, this article introduces a novel algorithmic approach for energy-efficient itinerary planning of MAs engaged in data aggregation tasks. Our algorithm adopts an iterated local search approach in deriving the hop sequence of multiple travelling MAs over the deployed source nodes. Simulation results demonstrate the performance gain of our method against existing multiple MA itinerary planning methods.

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Notes

  1. Iterated Local Search is based on building a sequence of locally optimal solutions by: (a) perturbing the current local minimum; (b) applying local search after starting from the modified solution.

  2. The impact factor \(G_{ij}\) between two nodes i and j is given by the following equation, with \(H_{j}^{i}\) denoting the estimated hop count between nodes: \(G_{ij}=e^{-\frac{\left( {H_j^i -1} \right) ^{2}}{2\cdot \sigma ^{2}}}\)

  3. In our implementation we assume that every node i in V is a source node. Nevertheless, our modeling also suits scenarios wherein the source nodes comprise a subset of V. Note that a source node may be visited multiple times. Once to actually retrieve sensory data and the remainder times in the process if migrating from one node to another (in the latter case, the node acts as intermediate node).

  4. https://github.com/ivenetis/Castalia-3.2-MIP.

  5. In the OP the objective is to determine a path, limited in length that visits some vertices and maximizes the sum of the collected scores.

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Acknowledgments

This research has been co-financed by the European Union (European Social Fund–ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program: Archimedes III. Investing in knowledge society through the European Social Fund.

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Authors and Affiliations

  1. Department of Cultural Technology and Communication, University of the Aegean, Mytilene, Greece

    Damianos Gavalas

  2. Department of Informatics, Technological Educational Institution of Athens, Athens, Greece

    Ioannis E. Venetis & Grammati Pantziou

  3. Department of Informatics, University of Piraeus, Piraeus, Greece

    Charalampos Konstantopoulos

Authors
  1. Damianos Gavalas
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  2. Ioannis E. Venetis
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  3. Charalampos Konstantopoulos
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  4. Grammati Pantziou
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Correspondence to Damianos Gavalas.

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Gavalas, D., Venetis, I.E., Konstantopoulos, C. et al. Energy-efficient multiple itinerary planning for mobile agents-based data aggregation in WSNs. Telecommun Syst 63, 531–545 (2016). https://doi.org/10.1007/s11235-016-0140-z

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