TPRC-07: Complexity of Internet Interconnections: Technology, Incentives and Implications for Policy
End-to-End (E2E) packet delivery in the Internet is achieved through a system of interconnections between many different types of entities called Autonomous Systems (ASs), entities that have ownership and administrative control over their networks. Historically the motivation behind and realizations of these interconnections began simple but have become significantly more abundant and complex than is commonly understood. For instance, large content networks, with mainly outbound traffic, are emerging which changes the nature of interconnections. As a consequence settlements are evolving with different allocative goals and mechanisms. The current models fail to accurately reflect the diversity of these and other possible interconnections among ASs that comprise today's actual Internet. In this paper, we present a more accurate picture of what Internet interconnection looks like today and discuss the implications of this for interconnection incentives, contractual arrangements, and public policy.
Specifically, as of March 2007 IANA had allocated 48,126 AS numbers, representing a significant feasible set of interconnections. However, besides the obvious geographical constraints, further preferential, architectural and settlement constraints induce a relatively smaller possible set of interconnections than the feasible set. An AS is most often an ISP but can also be enterprises, governmental or educational institutions and increasingly large content providers with mostly outbound traffic such as Google, Yahoo, YouTube and overlay networks such as Akamai, Savvis and Limelight. Each AS is also autonomous and controls and administers its own domain but must physically interconnect with other networks to provide services. A key problem discussed in this paper is the role of preferences among different types of ASs that induce the system of interconnections, or who has both ex-ante and ex-post incentive to interconnect to who given the different AS types. If interconnection is mutually stable then the fixed costs of a physical interconnection are then committed by investing in the physical links or collocations. Each AS then strategically uses the Internet routing algorithm (the Border Routing Protocol, BGP) to control usage-based costs by managing how packets exit and enter their network.
Not surprisingly, the challenge of recovering the fixed and usage-sensitive costs of E2E transport have given rise to a more complex settlements mechanism than the simple bifurcated model of tran sit (where gsmallh networks pay glargerh ones) and peering (revenue-neutral interconnection among similar size networks). We will demonstrate the emerging developments in this new settlement mechanism, emphasizing their ( ex-ante and ex-post ) difference from settlement mechanisms employed in the telephone network, in which interconnection is heavily regulated and significant carrier resources are devoted to the metering and billing of intercarrier payments.
In particular, we will use case histories, simple formal models and design principles to demonstrate: 1) how the architectural choices motivated by technical desiderata have induced the currently implemented ex-post settlement mechanism, 2) how the two standard settlement mechanism based on a system of bilateral transfers fails to send relevant price signals that can be used to internalize potential indirect externalities across markets, leading to closure of viable markets, 3) the arbitrarily complex ex-ante and ex-post interconnection strategy space available to ASs of different types within that mechanism and 4) how the evolving interconnection preferences of different types of ASs has led to the emergence of potentially more dominant and non-standard settlement mechanism in the market that further extend the strategy space of ASs.
The outcomes of this work will be relevant to not only Internet architects, but also the policy community (e.g., those engaged in debates over Network Neutrality) by highlighting how Internet architecture constrains the options and complexity of interconnection mechanisms and policy.
NETECON-07: Economics of Overlay Networks: An Industrial Organization Perspective on Network Economics
We use theory of Industrial Organization to demonstrate the demand and cost conditions on entry and scaling incentives of Internet overlay networks, restricting the problem to Internet content distribution. We describe the market structure, the nature of demand and the cost-allocation mechanism in both wholesale and retail markets. We show how the end-to-end coordination failures of the ISPs and content providers has resulted in wholesale market failures, inducing entry by propriety content distribution gmiddleboxesh that act as intermediaries, coordinating unmet demands. We also show that the intermediary has incentives to strategically use the Internet cost-allocation mechanism to internalize and scale using these indirect externalities from trade. The scaling incentives of such overlay markets is also briefly compared with bargaining institutions implemented by P2P content networks. [.pdf]
In recent years, we have seen the emergence of numerous types of so-called "overlay" networks in the internet. There are many diverse examples of such overlay networks including the content-delivery-caching networks, implemented by companies like Akamai, the peer-to-peer file sharing networks associated with applications such as BitTorrent, the voice-over-IP services offered via Skype, and various testbed networks such as PlanetLab. Such overlays have important technological and policy implications for the evolution of next generation internet architecture. This paper provides a first attempt to understand the implications of such overlays for internet architecture, industry structure, and policy. We introduce a taxonomy for thinking about these overlays with some examples of their scale and growing importance in the internet, and suggest some preliminary thoughts on the implications of these overlays for industry structure and policy. [.pdf]
HotNets-06: Interconnection Discrimination: A Two-Sided Perspective
We first motivate a methodological approach to network economics research using tools from Industrial Organization (IO). We then demonstrate the utility of such models in light of an increasingly important problem of interconnection failures that includes network neutrality problem. In particular, we focus on a subset of the problem by focusing on direct interconnection failures when ISPs price discriminate between content providers and content users. We informally show how viewing the problem as a Two-Sided Market can lead to a discrimination rule which highlights the structural/distributional nature of the interconnection problem. Structural consideration has not only policy and antitrust consequences but can also be highly informative to engineering choices. [.pdf]
NetEcon-06: Assessing the assumptions underlying mechanism design for the Internet
Mechanism design seeks to create incentives that align the interests of selfish agents with the interests of a principal designer. Critical to aligning these interests is the principal's assumptions about the agents that will be playing the game induced by the mechanism. In this paper, we critically examine two classes of assumptions in mechanism design for the Internet: 1) assumptions about agent preferences and 2) assumptions about the number of times an agent plays the game induced by a mechanism. We appeal to both methodological arguments and general theoretical results in exploring the limits and strength of claims in networking that are based upon mechanism design. We demonstrate how previous research [7,15] proves properties that may not hold true on the actual Internet if selfish agents do not conform to a principal's assumptions.
NIC-06: Annealing Protocol for Negotiating Complex Contracts
Work to date on negotiation protocols has focused almost exclusively on defining contracts consisting of one or a few independent issues and relatively small number of possible contracts. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal social welfare for negotiations with binary issue dependencies.
TPRC-05: The Growth of Internet Overlay Networks: Implications for Architecture, Industry Structure and Policy
Over the past several years, we have seen the emergence of numerous types of so- called "overlay" networks in the Internet. There are many diverse examples of such overlay networks including the content-delivery-caching networks, implemented by companies like Akamai, the peer-to-peer file sharing networks associated with applications such as BitTorrent, the voice-over-IP services offered via Skype, and various testbed networks such as PlanetLab. These overlay networks enhance or modify the basic functioning of traffic handling within the Internet. Overlays exist in the blurry boundary between what we think of as "the Internet" (a globally interconnected network of IP networks) and the applications that exist on top of the Internet. Overlays also blur the boundaries between the network edges (what we think of as being associated with customer end-nodes) and the network core (what we think of as associated with the services that support the Internet). As such, overlays have important technological and policy implications for the evolution of next generation Internet architecture that historically has been based on the so-called "end-to-end" principle ([SRC84], [BC01]) which relied on a relatively clear demarcation between applications and network services, and edge and core responsibilities. Because of the Internet's growing role as basic infrastructure and increasingly central role in the communications industry, and hence, obvious focus for regulation, changes in Internet architecture have important policy and industry structure implications. For example, from a regulatory perspective, the debate over overlays in Internet space is analogous to the on-going debate over "layered regulation" (see [Fre02], [Sic02], [Wer02]) and how one might distinguish between "basic telecom services" (which may be regulated under Title II as common carriers) and "enhanced" or "information" services (which are unregulated). From an industry structure perspective, overlays are relevant to the tussle over what services are provided by ISPs as opposed to other third party service providers (so-called ESPs) or by customer-managed layers. Since these overlays are important to the future industry structure of our communications industry and its regulation, including issues of VoIP, intercarrier compensation, universal service, and market-power regulation, we need a clearer understanding of what overlays are and might be. This paper provides a first attempt to help frame the issue. Herein we introduce a taxonomy for thinking about these overlays with some examples of their scale and growing importance in the Internet, and we suggest some preliminary thoughts on the implications of these overlays for industry structure and policy. [.pdf]
PINS-05: Practice and Theory of Incentives in Networked Systems [.pdf]
AAMAS-04: Learning User Preferences for Wireless Services Provisioning
The problem of interest is how to dynamically allocate wireless access services in a competitive market which implements a take-it-or-leave-it allocation mechanism. In this paper we focus on the subproblem of preference elicitation, given a mechanism. The user, due to a number of cognitive and technical reasons, is assumed to be initially uninformed over their preferences in the wireless domain. The solution we have developed is a closed-loop user-agent system that assists the user in application, task and context dependent service provisioning by adaptively and interactively learning to select the best wireless data service. The agent learns an incrementally revealed user preference model given explicit or implicit feedback on its decisions by the user. We model this closed-loop system as a Markov Decision Process, where the agent actions are rewarded by the user, and show how a reinforcement learning algorithm can be used to learn a model of the user’s preferences on-line in the given allocation mechanism. We evaluate the performance and value of the agent in a series of empirical user studies[.pdf]
Connectivity is central to pervasive computing environments. We seek to catalyze a world of rich and diverse connectivity through technologies that drastically simplify the task of providing, choosing, and using wireless network services; creating a new and more competitive environment for these capabilities. A critical requirement is that users are able to benefit from this rich environment, rather than simply being overloaded with choices. We address this with an intelligent software agent that transparently and continually chooses from among available network services based on its user's individual needs and preferences, while requiring only minimal guidance and user interaction. In this paper, we present an overview and model of the network service selection problem. We then describe an adaptive user agent that learns its user's network service preferences from a very minimal, intuitive set of inputs, and autonomously and continually select the service that best meets the user's needs. Results from preliminary user experiments are presented that demonstrate the effectiveness of our agent.[.pdf]
Work to date on negotiation protocols has focused almost exclusively on defining contracts consisting of one or a few independent issues and relatively small number of possible contracts. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal outcomes for negotiations with binary issue dependencies.[.pdf]
Work to date on computational models of negotiation has focused almost exclusively on defining agreements consisting of one or a few independent issues. The negotiation involved in collaborative design, by contrast, is much more complex, consisting of multiple inter-dependent issues and intractably large design spaces. This paper describes a simulated annealing based approach appropriate for collaborative design negotiations that achieves near-optimal outcomes with binary issue dependencies.[.pdf]
We present a dynamic and adaptive decision model for an autonomous user agent whose task is to dynamically negotiate and procure wireless access for a mobile user. A user is assumed to have cognitive and motivational costs associated to providing subjective preference information to the agent. Therefore the task of the personal agent is to dynamically model the user, update its knowledge of a market of wireless service providers and select service providers that satisfies the user's expected preferences based on minimal, or missing, information that is derived from a simple user interface. In this paper we show how this user modeling problem can be represented as a Markov Decision Process. Adaptive reinforcement learning solutions are then evaluated for two subclasses of tractable MDPs via simulations of some representative user models.[.pdf]
GDN-03: Negotiating Complex Contracts
Work to date on computational models of negotiation has focused almost exclusively on defining contracts consisting of one or a few independent issues and tractable contract spaces. Many real-world contracts, by contrast, are much more complex, consisting of multiple inter-dependent issues and intractably large contract spaces. This paper describes a simulated annealing based approach appropriate for negotiating such complex contracts that achieves near-optimal social welfares for negotiations with binary issue dependencies.
[.pdf]AIJ-03: Using Similarity Criteria to Make Negotiation Trade-Offs
Automated negotiation is a key form of interaction in systems that are composed of multiple autonomous agents. The aim of such interactions is to reach agreements through an iterative process of making offers. The content of such proposals are, however, a function of the strategy of the agents. Here we present a strategy called the trade-off strategy where multiple negotiation decision variables are traded-off against one another (e.g., paying a higher price in order to obtain an earlier delivery date or waiting longer in order to obtain a higher quality service). Such a strategy is commonly known to increase the social welfare of agents. Yet, to date, most computational work in this area has ignored the issue of trade-offs, instead aiming to increase social welfare through mechanism design. The aim of this paper is to develop a heuristic computational model of the trade-off strategy and show that it can lead to an increased social welfare of the system. A novel linear algorithm is presented that enables software agents to make trade-offs for multi-dimensional goods for the problem of distributed resource allocation. Our algorithm is motivated by a number of real-world negotiation applications that we have developed and can operate in the presence of varying degrees of uncertainty. Moreover, we show that on average the total time used by the algorithm is linearly proportional to the number of negotiation issues under consideration. This formal analysis is complemented by an empirical evaluation that highlights the operational effectiveness of the algorithm in a range of negotiation scenarios. The algorithm itself operates by using the notion of fuzzy similarity to approximate the preference structure of the other negotiator and then uses a hill-climbing technique to explore the space of possible trade-offs for the one that is most likely to be acceptable.[.ps][.pdf]
Socially Intelligent Agents Abstract: Multi-Agent Contract Negotiation
Two computational decision models are presented for the problem of de-centralized contracting of multi-dimensional services and goods between autonomous agents. The assumption of the models is that agents are bounded in both information and computation. Heuristic and approximate solution techniques from Artificial Intelligence are used for the design of decision mechanism that approach mutual selection of efficient contracts.[.ps][.pdf]
AAMAS 2002 Abstract: Agent Preference Relations: Strict, Equivalents and Incomparables
A fuzzy model is presented for representing ordered and incomparable preferences over alternatives. In this model a userbamically through a gradual transition between any of the strict, indifferent and incomparable class of preference structures. This transition is defined as a function of demand levels on the inclusion of one alternative over another. A model of reasoning is also presented for the resolution of such incomparabilities by an agent who forms beliefs over the expected orderings. The application and novelty of this model are motivated with reference to class of multi-criteria decision problems. [.pdf]
ATAL-01 Abstract: Simple Negotiating Agents in Complex Games: Emergent Equilibria and Dominance of Strategies
We present a simple model of distributed multi-agent multi-issued contract negotiation for open systems where interactions are competitive and information is private and not shared. We then investigate via simulations two different approximate optimization strategies and quantify the contribution and costs of each towards the quality of the solutions reached. To evaluate the role of knowledge the obtained results are compared to more cooperative strategies where agents share more information. Interesting social dilemmas emerge that suggest the design of incentive mechanisms.[.ps][.pdf]
IJCAI-01 Abstract: Automated Contract Negotiation and Execution as a System of Constraints
A classification of constraints is proposed that represents not only the individual and negotiated decisions of multiple agents as constraints, but also the exceptions that can occur at execution time. A design of an exception mechanism is then proposed based on task-environment constraints. This mechanism is composed of an informative and a normative component. The informative component functions to update the beliefs of agents about possible exceptions during the negotiation or execution stages of a joint activity. The normative component, on the other hand, places requirements on the agent to reason about such exceptions. The interaction of such an informative mechanism on a bargaining mechanism is elaborated in this paper. A simple additive model of future events is assumed to reasonably model this information. Different agent bargaining strategies, characterized as different attitudes towards the original constraints of the local problem given this belief, are then evaluated for a concession solver in an alternating sequential protocol. [.ps][.pdf]
PhD Thesis Abstract: Automated Service Negotiation between Autonomous Computational Agents
ICMAS-00 Abstract: Using Similarity Criteria to Make Negotiation Trade-Offs
PAAM-00 Abstract: A Service-Oreinted Negotiation Model between Autonomous Agents