Performance of Different Routings in Online Environment

A recent trend in routing research is to avoid inefficiencies in network-level routing by allowing hosts to either choose routes themselves (e.g., source routing) or use overlay routing networks (e.g., Detour or RON). Such approaches result in selfish routing, because routing decisions are no longer based on system-wide criteria but are instead designed to optimize host-based or overlay-based metrics. A series of theoretical results showing that selfish routing can result in suboptimal system behavior have cast doubts on this approach. In this paper, we use a game-theoretic approach to investigate the performance of selfish routing in Internet-like environments based on realistic topologies and traffic demands in our simulations. We show that in contrast to theoretical worst cases, selfish routing achieves close to optimal average latency in such environments. However, such performance benefits come at the expense of significantly increased congestion on certain links. Moreover, the adaptive nature of selfish overlays can significantly reduce the effectiveness of traffic engineering by making network traffic less predictable

Effect of Selfish Behavior on Power Consumption in Mobile Ad Hoc Network

A multi hop mobile ad hoc network is a peer to peer network of wireless nodes where nodes are required to perform routing activity to provide end to end connectivity among nodes. As mobile nodes are constrained by battery power and bandwidth, some nodes may behave selfishly and deny forwarding packets for other nodes, even though they expect other nodes to forward packets to keep network connected. We simulate two selfish behaviors on top of Dynamic Source Routing (DSR) protocol: the first, selfish nodes do not forward data or control packets (routing packets) for other nodes and the second, selfish nodes turn off their network interface card when they have nothing to communicate. We compare the energy saving to the selfish nodes for both the misbehaviors and show that the second selfish behavior saves more energy. This is important result because most of the cooperation enforcement mechanisms in literature, except PCOM [2], address the first selfish behavior. Also, the second selfish behavior can be easily done by layman users without any protocol level changes. Secondly, with our simulation study we find that in dense mobile ad hoc networks where route breakages are frequent, routing control packets consume significant fraction of node energy and selfish behavior by certain number of nodes reduce the overall routing overhead in network which in turn result in energy saving for both, well behaving nodes and selfish nodes

Selfish traffic allocation for server farms

We study the price of selfish routing in noncooperative networks like the Internet. In particular, we investigate the price of selfish routing using the price of anarchy (a.k.a. the coordination ratio) and other (e.g., bicriteria) measures in the recently introduced game theoretic parallel links network model of Koutsoupias and Papadimitriou. We generalize this model toward general, monotone families of cost functions and cost functions from queueing theory. A summary of our main results for general, monotone cost functions is as follows: 1. We give an exact characterization of all cost functions having a bounded/unbounded price of anarchy. For example, the price of anarchy for cost functions describing the expected delay in queueing systems is unbounded. 2. We show that an unbounded price of anarchy implies an extremely high performance degradation under bicriteria measures. In fact, the price of selfish routing can be as high as a bandwidth degradation by a factor that is linear in the network size. 3. We separate the game theoretic (integral) allocation model from the (fractional) flow model by demonstrating that even a very small or negligible amount of integrality can lead to a dramatic performance degradation. 4. We unify recent results on selfish routing under different objectives by showing that an unbounded price of anarchy under the min-max objective implies an unbounded price of anarchy under the average cost objective and vice versa. Our special focus lies on cost functions describing the behavior of Web servers that can open only a limited number of Transmission Control Protocol (TCP) connections. In particular, we compare the performance of queueing systems that serve all incoming requests with servers that reject requests in case of overload. Our analysis indicates that all queueing systems without rejection cannot give any reasonable guarantee on the expected delay of requests under selfish routing even when the injected load is far away from the capacity of the system. In contrast, Web server farms that are allowed to reject requests can guarantee a high quality of service for every individual request stream even under relatively high injection rates

An Optimal Game Theoretical Framework for Mobility Aware Routing in Mobile Ad hoc Networks

Selfish behaviors are common in self-organized Mobile Ad hoc Networks (MANETs) where nodes belong to different authorities. Since cooperation of nodes is essential for routing protocols, various methods have been proposed to stimulate cooperation among selfish nodes. In order to provide sufficient incentives, most of these methods pay nodes a premium over their actual costs of participation. However, they lead to considerably large overpayments. Moreover, existing methods ignore mobility of nodes, for simplicity. However, owing to the mobile nature of MANETs, this assumption seems unrealistic. In this paper, we propose an optimal game theoretical framework to ensure the proper cooperation in mobility aware routing for MANETs. The proposed method is based on the multi-dimensional optimal auctions which allows us to consider path durations, in addition to the route costs. Path duration is a metric that best reflects changes in topology caused by mobility of nodes and, it is widely used in mobility aware routing protocols. Furthermore, the proposed mechanism is optimal in that it minimizes the total expected payments. We provide theoretical analysis to support our claims. In addition, simulation results show significant improvements in terms of payments compared to the most popular existing methods