Göbel J., Krzesinski A., Mandjes M.
Incentive-based control of ad hoc networks: A performance study
Department of Informatics, University of Hamburg, Vogt-Kölln-Str. 30, 22527 Hamburg, Germany; Department of Mathematical Sciences, University of Stellenbosch, 7600 Stellenbosch, South Africa; Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Plantage Muidergracht 24, 1018 TV Amsterdam, Netherlands
Göbel, J., Department of Informatics, University of Hamburg, Vogt-Kölln-Str. 30, 22527 Hamburg, Germany; Krzesinski, A., Department of Mathematical Sciences, University of Stellenbosch, 7600 Stellenbosch, South Africa; Mandjes, M., Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Plantage Muidergracht 24, 1018 TV Amsterdam, Netherlands
Ad hoc networks are self-configuring networks of mobile nodes, connected by wireless links. If a destination node is beyond the transmission range of an origin node, then the nodes must cooperate to provide a multi-hop route. Any node can act as a sender, receiver or transit node. It is clear that it is in a node's interest to be a sender or receiver, but it is less clear what the value is of forwarding traffic on behalf of other nodes. The nodes should therefore be given incentives to act as transit nodes, otherwise the network would fail to function. A way to do so is by introducing for each node a credit balance, where nodes use credits to pay for the costs of sending their own traffic, and earn credits by forwarding traffic from other nodes. However, nodes that are located near the edge of the network will attract little transit traffic and earn few credits. In contrast, nodes located near the centroid of the network will attract transit traffic and earn credits. We investigate various ways of providing nodes near the edge of the network with preferential treatment in order to improve their credit balance and their throughputs. We next focus on the situation where each node can move to improve its utility expressed in terms of either credit balance or throughput. Here radio interference plays an important role, as it defines an interesting trade-off: nodes may prefer to be close together in order to reduce the power needed to transmit data, but on the other hand proximity increases radio interference, and has therefore a negative effect on connectivity. Simulation experiments reveal that the positions of the nodes converge to non-trivial optimal positions on 2D and 3D surfaces. © 2009 Elsevier B.V. All rights reserved.
Autonomous motion; Congestion pricing; Credit incentives; Credit redistribution; Incentives for collaboration; Mobile ad-hoc networks; Mobility models; Radio interference
Autonomous motion; Congestion pricing; Credit incentives; Credit redistribution; Incentives for collaboration; Mobility models; Electromagnetic compatibility; Electromagnetic pulse; Mobile ad hoc networks; Radar interference; Radio interference; Three dimensional; Throughput; Traffic congestion; Two dimensional; Wireless telecommunication systems; Ad hoc networks