In this paper, we propose a distributed solution based on game-theoretic approaches to the topology formation problem for mobile wireless sensor networks with multi-source multicast flows. Our solution significantly reduces computational complexity by taking advantage of network coding. Finding an optimal topology for network coding in multi-source multicast flows is NP-hard problem, so the proposed algorithm provides a suboptimal solution with low computational complexity. We formulate the problem of distributed network topology formation as a network formation game by considering the nodes in the network as players that can take actions for making outgoing links. The proposed game, which consists of multiple players and multicast flows, can be decomposed into independent link formation games played by only two players with a unicast flow. The proposed algorithm is also guaranteed to converge, i.e., a stable network topology can be always formed. Our simulation results confirm that the computational complexity of the proposed solution is low enough for practical deployment in large-scale mobile, wireless sensor networks.
|Title of host publication||2017 IEEE International Conference on Communications, ICC 2017|
|Editors||Merouane Debbah, David Gesbert, Abdelhamid Mellouk|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 28 Jul 2017|
|Event||2017 IEEE International Conference on Communications, ICC 2017 - Paris, France|
Duration: 21 May 2017 → 25 May 2017
|Name||IEEE International Conference on Communications|
|Conference||2017 IEEE International Conference on Communications, ICC 2017|
|Period||21/05/17 → 25/05/17|
Bibliographical noteFunding Information:
This research was supported in part by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1007) supervised by the IITP (Institute for Information & Communications Technology Promotion) and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2014R1A2A1A11051257).
© 2017 IEEE.