Name
Abstract | ||
|---|---|---|
In this paper, a game-theoretical framework for the design of distributed algorithms that control the transmission range (TR) of nodes in order to maximize throughput in Wireless Multihop Networks (WMN) is proposed. It is based on the stability region of the link-scheduling policy adopted for the network. The stability region is defined as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). The goal of the TR-control algorithms is to adapt the stability region to a given set of end-to-end flows. In the algorithms, the flows control distributively the nodes' TRs using the stability region in order to enable higher end-to-end packet rates while guaranteeing stability. In order to demonstrate how the algorithms can be designed using the proposed game-theoretical framework, a new TR-control algorithm for IEEE-802.16 WMNs is developed. Its convergence is demonstrated, and a performance bound is calculated. Finally, simulation results show that the algorithm is able to find the optimal TRs more effectively. The TRs achieve throughput levels that are at least 90 percent of the optimal throughput for 72 percent of the simulated scenarios, whereas the classic approach of spatial-reuse maximization does this for 62 percent of the scenarios. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TPDS.2013.202 | Parallel and Distributed Systems, IEEE Transactions |
Keywords | DocType | Volume |
distributed algorithms,game theory,scheduling,telecommunication links,telecommunication standards,IEEE-802.16 WMN,TR-control algorithms,distributed algorithms,distributed throughput maximization,end-to-end packet rates,game-theoretical framework,input-packet rates,link-scheduling policy,stability region,transmission range,wireless multihop networks,wireless networks,Transmission-range control,potential games,stability region,transmission power | Journal | 25 |
Issue | ISSN | Citations |
7 | 1045-9219 | 0 |
PageRank | References | Authors |
0.34 | 40 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gustavo Vejarano | 1 | 7 | 2.82 |
| Dexiang Wang | 2 | 53 | 4.38 |
| Ritwik Dubey | 3 | 0 | 0.34 |
| Janise McNair | 4 | 369 | 40.57 |