How bad is selfish routing?

We study the degradation in network performance caused by the selfish behavior of noncooperative network users. We consider a directed network in which each edge possesses a latency function describing the common latency incurred by all traffic on the edge as a function of the edge congestion. Given a rate of traffic between each pair of nodes in the network, we aspire toward an assignment of traffic to paths in which the sum of all travel times (the total latency) is minimized; however, in many settings network users are free to route their traffic in a selfish manner, without regard to the total latency. We therefore assume that each network user routes its traffic on the minimum-latency path available to it, given the network congestion caused by the other users. In general such a selfishly motivated assignment of traffic to paths (a Nash equilibrium) will not minimize the total latency; hence, selfish behavior carries the cost of decreased network performance. We quantify this degradation in network performance via the price of anarchy, defined as the worst possible ratio between the total latency of a Nash equilibrium and of a minimum-latency routing of the traffic.In this paper, we show that the underlying network topology plays no role in the determination of the price of anarchy. Specifically, we show that under weak hypotheses on the class of allowable edge latency functions, the worst-case ratio between the total latency of a Nash equilibrium and of a minimum-latency routing for any multicommodity flow network is achieved by a single-commodity instance on a set of parallel links. In the special case where the class of allowable latency functions includes all of the constant functions, we prove that a network with only two parallel links suffices to achieve the worst-possible ratio. Informally, these results imply that the inefficiency inherent in a flow at Nash equilibrium stems from the inability of selfish users to discern which of two competing routes is superior and not from the topological complexity arising from the diverse intersections of many paths belonging to different commoditie.Our proof techniques also give powerful methods for computing the price of anarchy with respect to an arbitrary class of latency functions. We apply these methods to function classes that have been well studied in the literature (such as degree-bounded polynomials and functions of the form $\ell(x) = (u—x)—1} that are used to model edges with capacity u), thereby achieving the first tight analyses of the price of anarchy for significant classes of latency functions outside the class of linear functions.

We study the negative consequences of selfish behavior in a congested network and economic means of influencing such behavior. We consider a model of selfish routing in which the latency experienced by network traffic on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route traffic on minimum-latency paths. The quality of a routing of traffic is measured by the sum of travel times (the total latency).It is well known that the outcome of selfish routing (a Nash equilibrium) does not minimize the total latency. An ancient strategy for improving the selfish solution is the principle of marginal cost pricing, which asserts that on each edge of the network, each network user on the edge should pay a tax offsetting the congestion effects caused by its presence. By pricing network edges according to this principle, the inefficiency of selfish routing can always be eradicated.This result, while fundamental, assumes a very strong homogeneity property: all network users are assumed to trade off time and money in an identical way. The guarantee also ignores both the algorithmic aspects of edge pricing and the unfortunate possibility that an efficient routing of traffic might only be achieved with exorbitant taxes. Motivated by these shortcomings, we extend this classical work on edge pricing in several different directions and prove the following results.We prove that the edges of a single-commodity network can always be priced so that an optimal routing of traffic arises as a Nash equilibrium, even for very general heterogeneous populations of network users.When there are only finitely many different types of network users and all edge latency functions are convex, we show how to compute such edge prices efficiently.We prove that an easy-to-check mathematical condition on the population of heterogeneous network users is both necessary and sufficient for the existence of edge prices that induce an optimal routing while requiring only moderate taxes.

Nash equilibria in discrete routing games with convex latency functions

Computing the Critical Road Section for the Repair of a Transportation Network

Efficiency loss may exist at every stage of repeated play. With the rapid development of our society, how to improve the overall efficiency in repeated games becomes increasingly crucial. This paper studies the performance of a sequence of action profiles generated by repeated play in a multiple origin-destination network. To analyze the overall efficiency of these action profiles, the price of total anarchy (POTA), defined as the worst-case ratio of the average total latency over a period of time and the total latency of any optimal strategy, is adopted. First of all, it is shown that the sequence of action profiles generated by best response principle with inertia possesses almost sure no-regret property. Then, we identify the upper bound of POTA via smoothness arguments for both linear and nonlinear latency cases. After that, we analyze the effect of road pricing on POTA in traffic networks with linear latency function. It is shown that the road price we designed can reduce the upper bound of POTA compared with that without road price. In addition, how the inaccurate parameter information of the latency function affects the POTA is discussed for the linear latency case. Moreover, in a traffic network with heterogeneous players, we show that the upper bound of POTA is the same as that in a network with homogeneous players as time goes to infinity. Finally, the results are applied to a traffic routing problem based on the real traffic data of Singapore.

We study the problem of optimizing the performance of a system shared by selfish, noncooperative users. We consider the concrete setting of scheduling jobs on a set of shared machines with load-dependent latency functions specifying the length of time necessary to complete a job; we measure system performance by the total latency of the system.Assigning jobs according to the selfish interests of individual users (who wish to minimize only the latency that their own jobs experience) typically results in suboptimal system performance. However, in many systems of this type there is a mixture of “selfishly controlled” and “centrally controlled” jobs; as the assignment of centrally controlled jobs will influence the subsequent actions by selfish users, we aspire to contain the degradation in system performance due to selfish behavior by scheduling the centrally controlled jobs in the best possible way.We formulate this goal as an optimization problem via Stackelberg games, games in which one player acts a leader (here, the centralized authority interested in optimizing system performance) and the rest as followers (the selfish users). The problem is then to compute a strategy for the leader (a em Stackelberg strategy) that induces the followers to react in a way that (at least approximately) minimizes the total latency in the system.In this paper, we prove that it is NP-hard to compute the optimal Stackelberg strategy and present simple strategies with provable performance guarantees. More precisely, we give a simple algorithm that computes a strategy inducing a job assignment with total latency no more than a constant times that of the optimal assignment of all of the jobs; in the absence of centrally controlled jobs and a Stackelberg strategy, no result of this type is possible.

In mobile network, it is likely that many mobile nodes handover at the same time, which is defined as group handover. The problem of network selection arises for group handover since each mobile node will selfishly select the best network based on individual information and consideration which may cause network congestion and performance degradation. In this paper, three network selection algorithms are proposed for group handover. The performance of these algorithms is studied with regard to the concept of social cost introduced in game theory.

본 논문에서는 디바이스의 이동으로 인한 WiMedia 네트워크의 성능 저하를 개선하기 위한 릴레이 통신 기법을 제안하였다. WiMedia 프로토콜은 고속의 전송속도를 지원하기 때문에, 선박 네트워크(Ship Area Network)등과 같은 환경에서 고속의 전송률을 요구하는 실시간 멀티미디어 서비스 제공과 같은 응용분야에 적합하다. 하지만, 디바이스의 이동은 네트워크 토폴로지와 디바이스간 링크 상태의 급격한 변화를 야기하며, 네트워크의 성능 저하의 원인이 되기도 한다. 본 논문에서는 기존의 WiMedia 프로토콜에서는 채널의 링크 상태 변화를 적절하게 대처하지 못하여 발생하는 네트워크 성능저하를 해결하는 릴레이 통신 기법을 제안하였다. In this paper, a relay communication scheme for enhancing the WiMedia network performance by device's mobility is proposed. WiMedia protocol is suitable for the application that supports the real-time multimedia service in Ship Area Network since it supports high speed data transfer. However, the device's mobility is caused the dramatic change of link state and network topology, and is occurred the degradation of network performance. Therefore, a relay communication scheme for WiMedia network is proposed in this paper. The proposed technique can intelligently treat the change of link state, and solve the degradation of network performance.

Critical node discovery plays a vital role in assessing the vulnerability of a computer network to malicious attacks and failures and provides a useful tool with which one can greatly improve network security and reliability. In this paper, we propose a new metric to characterize the criticality of a node in an arbitrary computer network which we refer to as the Combined Banzhaf & Diversity Index (CBDI). The metric utilizes a diversity index which is based on the variability of a node׳s attributes relative to its neighbours and the Banzhaf power index which characterizes the degree of participation of a node in forming shortest paths. The Banzhaf power index is inspired from the theory of voting games in game theory. The proposed metric is evaluated using analysis and simulations. The criticality of nodes in a network is assessed based on the degradation in network performance achieved when these nodes are removed. We use several performance metrics to evaluate network performance including the algebraic connectivity which is a spectral metric characterizing the connectivity robustness of the network. Extensive simulations in a number of network topologies indicate that the proposed CBDI index chooses more critical nodes which, when removed, degrade network performance to a greater extent than if critical nodes based on other criticality metrics were removed.

Quantifying the resilience of community structures in networks

In the immediate aftermath of devastating earthquakes such as in the 6 February 2023 Kahramanmaraş sequence in southcentral Türkiye, key stakeholders and the public demand timely and accurate earthquake information. Especially for large events, finite-fault models provide important insights into the rupture process and enable interpretation of the observed ground shaking, which can improve situational awareness and facilitate rapid assessment of future hazards. Using strong-motion waveforms recorded during the Kahramanmaraş sequence, we simulate a real-time playback and calculate how a finite-source model computed with the Finite-fault rupture Detector (FinDer) algorithm would evolve for the Mw 7.8 Pazarcık, Mw 7.6 Elbistan, and Mw 6.4 Yayladağı earthquakes. Using template matching FinDer compares observed and predicted ground-motion acceleration amplitudes to determine the orientation and spatial extent of fault rupture. We test both generic crustal and fault-specific templates from ground-motion models and rupture geometries of the east Anatolian and Çardak–Sürgü faults. In the second step, we estimate the seismic slip along the source models from the backprojection of the seismic displacement amplitudes. The algorithms achieve excellent performance for all three earthquakes, and the final source models and slip profiles available within tens of seconds of the rupture nucleation match well with models computed days to weeks after the events occurred. The temporal evolution of the source models for the Pazarcık and Elbistan earthquakes suggests that FinDer can provide insight into the rupture kinematics of large earthquakes. Cascading instrument failures as well as power and data telemetry interruptions during the Pazarcık earthquake led to an early termination of signals at a significant number of near-source stations. We show that FinDer is robust enough to cope with this type of degradation in network performance that can occur in large earthquakes, in general.

This paper presents the design, implementation and evaluation of Limiting Greedy Connections (LGC), an active mechanism for controlling unresponsive connections and minimizing the degradation in network performance caused by bandwidth‐greedy applications. The primary objectives of the LGC mechanism are to limit the impact of greedy connections on a congested node, to keep a loose upper bound on the packet queue occupancy at the intermediate nodes of the network and to minimize packet loss. The LGC mechanism is evaluated for a variety of network topologies, transmitting sources and node queue parameters, using a Java‐based active network testbed. Copyright © 2003 John Wiley &Sons, Ltd.

Fundamental to the Network Administrator's consideration of risk on a network are issues of security namely; confidentiality, integrity and availability of information assets. The ability to effectively and efficiently manage the network and make room for growth without degradation in network performance are equally considerable concerns. The segmentation of a significantly large Local Area Network with a possible annual growth rate of over 10% is undoubtedly the surest way to effectively manage the network, ensure security of information assets and make it scalable. This paper seeks to assess the Pentecost University College(PUC) campus network at Sowutuom to determine how optimally segmented it is and the most practical option of using Virtual LANs to optimize the segmentation for effective and efficient security, management and scalability. Based on the information gathered and analysis carried out on the network, a proposal is advanced to enhance the segmentation of the campus network with an eye towards the future growth.

Broadcasting has many important uses and several mobile ad hoc networks (MANETs) protocols assume the availability of an underlying broadcast service. Applications, which make use of broadcasting, include LAN emulation, paging a particular node. However, broadcasting induces what is known as the "broadcast storm problem" which causes severe degradation in network performance, due to excessive redundant retransmission, collision, and contention. Although probabilistic flooding has been one of the earliest suggested approaches to broadcasting. There has not been so far any attempt to analyse its performance behaviour in MANETs. This paper investigates using extensive ns-2 simulations the effects of a number of important parameters in a MANET, including node speed, pause time and, traffic load, on the performance of probabilistic flooding. The results reveal that while these parameters have a critical impact on the reachability achieved by probabilistic flooding, they have relatively a lower effect on the number of saved rebroadcast packets

As the importance of the Internet increases, developing technologies for data transmission at higher bit rates became as important as challenging. Optical Transport Networks (OTN), based on Wavelength Division Multiplexing (WDM), emerged to meet this need. ITU has standardized OTN, including its management functions. Network elements in OTN store performance monitoring information as time series of performance events, which could be explored to enable more efficient preventive maintenance and better resource provisioning. With the use of time series forecasting models, faults could even be avoided, along with Service Level Agreement breaches. In this work, we propose the use of time series forecasting in performance monitoring of OTN, investigating how three forecasting methods behave in scenarios of stability and degradation in network performance and how the number of monitoring intervals affects their accuracy. In accordance with results we state recommendations for application of tested time series forecasting methods in managing OTN.