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Lee, Kyunghan
Mobile Systems and Networking Lab. (MSN)
Research Interests
  • Low-latency network, cloud computing, 5G network, mobile machine learning

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Max Contribution : An On-line Approximation of Optimal Resource Allocation in Delay Tolerant Networks

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Title
Max Contribution : An On-line Approximation of Optimal Resource Allocation in Delay Tolerant Networks
Author
Lee, KyunghanJeong, JaeseongYi, YungWon, HyungsukRhee, InjongChong, Song
Issue Date
2015-03
Publisher
IEEE COMPUTER SOC
Citation
IEEE TRANSACTIONS ON MOBILE COMPUTING, v.14, no.3, pp.592 - 605
Abstract
In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NPhard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed on-line approximation algorithm, Distributed Max-Contribution (DMC) that performs scheduling, routing and replication based only on locally and contemporarily available information. Through extensive simulations based on real GPS traces tracking over 4000 taxies and 500 taxies for about 30 days and 25 days in two different large cities, DMC is verified to perform closely to MC and outperform existing heuristically engineered resource allocation algorithms for DTNs.
URI
https://scholarworks.unist.ac.kr/handle/201301/9810
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6826508
DOI
10.1109/TMC.2014.2329001
ISSN
1536-1233
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