We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agents ’ interests are best served by behaving correctly. Following notions from the field of mechanism design, we suggest a framework for studying such algorithms. Our main technical contribution concerns the study of a representative task scheduling problem for which the standard mechanism design tools do not suffice. Journal of Economic Literature

We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route traffic such that the sum of all travel times—the total latency—is minimized. In many settings, it may be expensive or impossible to regulate network traffic so as to implement an optimal assignment of routes. In the absence of regulation by some central authority, we 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 will not minimize the total latency; hence, this lack of regulation carries the cost of decreased network performance. In this article, we quantify the degradation in network performance due to unregulated traffic. We prove that if the latency of each edge is a linear function of its congestion, then the total latency of the routes chosen by selfish network users is at most 4/3 times the minimum possible total latency (subject to the condition that all traffic must be routed). We also consider the more general setting in which edge latency functions are assumed only to be continuous and nondecreasing in the edge congestion. Here, the total

We describe ways in which the transmission control protocol of the Internet may evolve to support heterogeneous applications. We show that by appropriately marking packets at overloaded resources and by charging a fixed small amount for each mark received, end-nodes are provided with the necessary information and the correct incentive to use the network efficiently.

Accurate network traffic measurement is required for accounting, bandwidth provisioning and detecting DoS attacks. These applications see the traffic as a collection of flows they need to measure. As link speeds and the number of flows increase, keeping a counter for each flow is too expensive (using SRAM) or slow (using DRAM). The current state-of-the-art methods (Cisco’s sampled NetFlow) which count periodically sampled packets are slow, inaccurate and resourceintensive. Previous work showed that at different granularities a small number of “heavy hitters” accounts for a large share of traffic. Our paper introduces a paradigm shift by concentrating the measurement process on large flows only — those above some threshold such as 0.1 % of the link capacity. We propose two novel and scalable algorithms for identifying the large flows: sample and hold and multistage filters, which take a constant number of memory references per packet and use a small amount of memory. If M is the available memory, we show analytically that the errors of our new algorithms are proportional to 1/M; by contrast, the error of an algorithm based on classical sampling is proportional to 1 / √ M, thus providing much less accuracy for the same amount of memory. We also describe further optimizations such as early removal and conservative update that further improve the accuracy of our algorithms, as measured on real traffic traces, by an order of magnitude. Our schemes allow a new form of accounting called threshold accounting in which only flows above a threshold are charged by usage while the rest are charged a fixed fee. Threshold accounting generalizes usage-based and duration based pricing.

A simple approach, called PMP (Paris Metro Pricing), is suggested for providing differentiated services in packet networks such as the Internet. It is to partition a network into several logically separate channels, each of which would treat all packets equally on a best effort basis. There would be no formal guarantees of quality of service. These channels would differ only in the prices paid for using them. Channels with higher prices would attract less traffic, and thereby provide better service. Price would be the primary tool of traffic management. PMP is the simplest differentiated services solution. It is designed to accommodate user preferences at the cost of sacrificing some of the utilization efficiency of the network.

This paper presents the design of a new Internet routing architecture (NIRA). In today’s Internet, users can pick their own ISPs, but once the packets have entered the network, the users have no control over the overall routes their packets take. NIRA aims at providing end users the ability to choose the sequence of Internet service providers a packet traverses. User choice fosters competition, which imposes an economic discipline on the market, and fosters innovation and the introduction of new services. This paper explores various technical problems that would have to be solved to give users the ability to choose: how a user discovers routes and whether the dynamic conditions of the routes satisfy his requirements, how to efficiently represent routes, and how to properly compensate providers if a user chooses to use them. In particular, NIRA utilizes a hierarchical provider-rooted addressing scheme so that a common type of domainlevel route can be efficiently represented by a pair of addresses. In NIRA, each user keeps track of the topology information on domains that provide transit service for him. A source retrieves the topology information of the destination on demand and combines this information with his own to discover end-to-end routes. This route discovery process ensures that each user does not need to know the complete topology of the Internet.

We solve a shortest path problem that is motivated by recent interest in pricing networks or other computational resources. Informally, how much is an edge in a network worth to a user who wants to send data between two nodes along a shortest path? If the network is a decentralized entity, such as the Internet, in which multiple self-interested agents own different parts of the network, then auctionbased pricing seems appropriate. A celebrated result from auction theory shows that the use of Vickrey pricing motivates the owners of the network resources to bid truthfully. In Vickrey's scheme, each agent is compensated in proportion to the marginal utility he brings to the auction. In the context of shortest path routing, an edge's utility is the value by which it lowers the length of the shortest path---the difference between the shortest path lengths with and without the edge. Our problem is to compute these marginal values for all the edges of the network efficiently. The na ve method requires solving the single-source shortest path problem up to n times, for an n-node network. We show that the Vickrey prices for all the edges can be computed in the same asymptotic time complexity as one single-source shortest path problem. This solves an open problem posed by Nisan and Ronen [12]. 1.

We consider applying network coding in settings where there is a cost associated with network use.

Abstract — Given the need to provide users with reasonable feedback about the “costs ” their network usage incurs and the increasingly commercial nature of the Internet, we believe that the allocation of cost among users will play an important role in future networks. This paper discusses cost allocation in the context of multicast flows. The question we discuss is this. When a single data flow is shared among many receivers, how does one split the cost of that flow among the receivers? Multicast routing increases network efficiency by using a single shared delivery tree. We address the issue of how these savings are allocated among the various members of the multicast group. We first consider an axiomatic approach to the problem, analyzing the implications of different distributive notions on the resulting allocations. We then consider a “one-pass ” mechanism to implement such allocation schemes and investigate the family of allocation schemes such mechanisms can support. Index Terms—Cost allocation, cost sharing, Internet economics, multicast, network accounting, quality of service (QoS).

Multicast and unicast traffic share and compete for network resources. A cost-based approach to multicast pricing, based on accurate characterization of multicast scalability, will facilitate the efficient and equitable resource allocation between traffic types. Through the quantification of link usage, this paper establishes a multicast scaling relationship: the cost of a multicast distribution tree varies at the 0.8 power of the multicast group size. This result is validated with both real and generated networks, and is robust across topological styles and network sizes. Since multicast cost can be accurately predicted given the membership size, there is strong motivation to price multicast according to membership size. Furthermore, a price ceiling should be set to account for the effect of tree saturation. This tariff structure is superior to either a purely membership-based or a flat-rate pricing scheme, since it reflects the actual tree cost at all group membership levels. Keywords: multicast pricing, multicast scaling 1.