Abstract
The problem of assigning a set of source nodes to a set of routes in wireless machine-to-machine (M2M) networks is addressed using a game theoretic approach. The objective is to minimize the maximum latency over all source nodes as far as possible while the game achieves a pure Nash Equilibrium (NE). To compute such an NE efficiently, we present a distributed dynamic pricing (DP) scheme, where each source node is assumed to pay for using any route so that the route has incentive to relay data for the source node. A loose upper bound is given for the convergence time of DP, and simulation results show that it performs much faster in practice. The price of anarchy in this game is also investigated by comparing DP with a cost-reducing path method; the results show that DP produces optimum assignment in more than 90% of the simulation runs.
Highlights
Features such as self-organization, ease of deployment, low cost, and infrastructurelessness bring to wireless M2M networks the advantages of robustness, easy maintenance, economy, and flexibility
Motivated by the general network congestion game [7,8,9] and pricing scheme [10], our study jointly considers the problems of routing congestion and incentive provision
Several parameters are investigated, including the number of source nodes, the ratio of source nodes to routes denoted by r, and the degree of source nodes, which is defined as the number of routes that each source node can connect to
Summary
Features such as self-organization, ease of deployment, low cost, and infrastructurelessness bring to wireless M2M networks the advantages of robustness, easy maintenance, economy, and flexibility. The network can be congested when there are a great many nodes that want to transmit data via a common set of routes. By joining the congestion control in the routing layer, this problem can be solved via the coordination among nodes [5, 6]. Motivated by the general network congestion game [7,8,9] and pricing scheme [10], our study jointly considers the problems of routing congestion and incentive provision. A distributed dynamic pricing (DP) scheme is developed for wireless M2M networks to minimize the maximum latency over all source nodes. Routing congestion is formulated as a dynamic game in which pricing is employed in the definition of players’ utility function.
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