3,732 research outputs found
Unilateral Altruism in Network Routing Games with Atomic Players
We study a routing game in which one of the players unilaterally acts
altruistically by taking into consideration the latency cost of other players
as well as his own. By not playing selfishly, a player can not only improve the
other players' equilibrium utility but also improve his own equilibrium
utility. To quantify the effect, we define a metric called the Value of
Unilateral Altruism (VoU) to be the ratio of the equilibrium utility of the
altruistic user to the equilibrium utility he would have received in Nash
equilibrium if he were selfish. We show by example that the VoU, in a game with
nonlinear latency functions and atomic players, can be arbitrarily large. Since
the Nash equilibrium social welfare of this example is arbitrarily far from
social optimum, this example also has a Price of Anarchy (PoA) that is
unbounded. The example is driven by there being a small number of players since
the same example with non-atomic players yields a Nash equilibrium that is
fully efficient
EGOIST: Overlay Routing Using Selfish Neighbor Selection
A foundational issue underlying many overlay network applications ranging from routing to P2P file sharing is that of connectivity management, i.e., folding new arrivals into an existing overlay, and re-wiring to cope with changing network conditions. Previous work has considered the problem from two perspectives: devising practical heuristics for specific applications designed to work well in real deployments, and providing abstractions for the underlying problem that are analytically tractable, especially via game-theoretic analysis. In this paper, we unify these two thrusts by using insights gleaned from novel, realistic theoretic models in the design of Egoist – a prototype overlay routing system that we implemented, deployed, and evaluated on PlanetLab. Using measurements on PlanetLab and trace-based simulations, we demonstrate that Egoist's neighbor selection primitives significantly outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, we demonstrate that Egoist is competitive with an optimal, but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overhead. Finally, we discuss some of the potential benefits Egoist may offer to applications.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CISE/CNS 0524477, CNS/NeTS 0520166, CNS/ITR 0205294; CISE/EIA RI 0202067; CAREER 04446522); European Commission (RIDS-011923
Design & Evaluation of Path-based Reputation System for MANET Routing
Most of the existing reputation systems in mobile ad hoc networks (MANET) consider only node reputations when selecting routes. Reputation and trust are therefore generally ensured within a one-hop distance when routing decisions are made, which often fail to provide the most reliable, trusted route. In this report, we first summarize the background studies on the security of MANET. Then, we propose a system that is based on path reputation, which is computed from reputation and trust values of each and every node in the route. The use of path reputation greatly enhances the reliability of resulting routes. The detailed system architecture and components design of the proposed mechanism are carefully described on top of the AODV (Ad-hoc On-demand Distance Vector) routing protocol. We also evaluate the performance of the proposed system by simulating it on top of AODV. Simulation experiments show that the proposed scheme greatly improves network throughput in the midst of misbehavior nodes while requires very limited message overhead. To our knowledge, this is the first path-based reputation system proposal that may be implemented on top of a non-source based routing scheme such as AODV
Resilience of Traffic Networks with Partially Controlled Routing
This paper investigates the use of Infrastructure-To-Vehicle (I2V)
communication to generate routing suggestions for drivers in transportation
systems, with the goal of optimizing a measure of overall network congestion.
We define link-wise levels of trust to tolerate the non-cooperative behavior of
part of the driver population, and we propose a real-time optimization
mechanism that adapts to the instantaneous network conditions and to sudden
changes in the levels of trust. Our framework allows us to quantify the
improvement in travel time in relation to the degree at which drivers follow
the routing suggestions. We then study the resilience of the system, measured
as the smallest change in routing choices that results in roads reaching their
maximum capacity. Interestingly, our findings suggest that fluctuations in the
extent to which drivers follow the provided routing suggestions can cause
failures of certain links. These results imply that the benefits of using
Infrastructure-To-Vehicle communication come at the cost of new fragilities,
that should be appropriately addressed in order to guarantee the reliable
operation of the infrastructure.Comment: Accepted for presentation at the IEEE 2019 American Control
Conferenc
The Network Improvement Problem for Equilibrium Routing
In routing games, agents pick their routes through a network to minimize
their own delay. A primary concern for the network designer in routing games is
the average agent delay at equilibrium. A number of methods to control this
average delay have received substantial attention, including network tolls,
Stackelberg routing, and edge removal.
A related approach with arguably greater practical relevance is that of
making investments in improvements to the edges of the network, so that, for a
given investment budget, the average delay at equilibrium in the improved
network is minimized. This problem has received considerable attention in the
literature on transportation research and a number of different algorithms have
been studied. To our knowledge, none of this work gives guarantees on the
output quality of any polynomial-time algorithm. We study a model for this
problem introduced in transportation research literature, and present both
hardness results and algorithms that obtain nearly optimal performance
guarantees.
- We first show that a simple algorithm obtains good approximation guarantees
for the problem. Despite its simplicity, we show that for affine delays the
approximation ratio of 4/3 obtained by the algorithm cannot be improved.
- To obtain better results, we then consider restricted topologies. For
graphs consisting of parallel paths with affine delay functions we give an
optimal algorithm. However, for graphs that consist of a series of parallel
links, we show the problem is weakly NP-hard.
- Finally, we consider the problem in series-parallel graphs, and give an
FPTAS for this case.
Our work thus formalizes the intuition held by transportation researchers
that the network improvement problem is hard, and presents topology-dependent
algorithms that have provably tight approximation guarantees.Comment: 27 pages (including abstract), 3 figure
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