Selected Issues of QoS Provision in Heterogenous Military Networks

Tactical ad-hoc networks are evolving today towards complex heterogeneous networks in terms of architecture, protocols and security. Due to the difference in network resources and reliability, end-to-end quality of service provisioning becomes very challenging. If we also take into account communication issues such as unpredictable connectivity, preferential forwarding for special traffic classes, intermittency due to node or communication link failure, the problem is further aggravated.In this article, we examine the major challenges that must be solved in order to provide efficient QoS provisioning in the heterogeneous network. Finally we describe QoS-aware mechanisms for inter-domain and intra-domain heterogeneous networks, also including real-time services provision in highly mobile environments.

On the problem of revenue sharing in multi-domain federations

Part 5: Cooperation and CollaborationInternational audienceAutonomous System alliances or federations are envisioned to emerge in the near future as a means of selling end-to-end quality assured services through interdomain networks. This collaborative paradigm mainly responds to the ever increasing Internet traffic volumes that requires assured quality, and constitutes a new business opportunity for Network Service Providers (NSPs). However, current Internet business rules are not likely to satisfy all involved partners in this emerging scenario. How the revenue is shared among NSPs must be agreed in advance, and should enforce economical incentives to join an alliance and remain in it, so that the alliance remains stable. In this paper, we work on the scenario of such federations, where service selling is formulated as a Network Utility Maximization (NUM) problem. In this context, we formally formulate the properties the revenue sharing (RS) method should fulfill and argue why the existing methods are not suitable. Finally, we propose a family of solutions to the RS problem such that the economical stability and efficiency of the alliance in the long term is guaranteed. The proposed method is based on solving a series of Optimization Problems and considering statistics on the incomes

Systems-compatible Incentives

Originally, the Internet was a technological playground, a collaborative endeavor among researchers who shared the common goal of achieving communication. Self-interest used not to be a concern, but the motivations of the Internet's participants have broadened. Today, the Internet consists of millions of commercial entities and nearly 2 billion users, who often have conflicting goals. For example, while Facebook gives users the illusion of access control, users do not have the ability to control how the personal data they upload is shared or sold by Facebook. Even in BitTorrent, where all users seemingly have the same motivation of downloading a file as quickly as possible, users can subvert the protocol to download more quickly without giving their fair share. These examples demonstrate that protocols that are merely technologically proficient are not enough. Successful networked systems must account for potentially competing interests. In this dissertation, I demonstrate how to build systems that give users incentives to follow the systems' protocols. To achieve incentive-compatible systems, I apply mechanisms from game theory and auction theory to protocol design. This approach has been considered in prior literature, but unfortunately has resulted in few real, deployed systems with incentives to cooperate. I identify the primary challenge in applying mechanism design and game theory to large-scale systems: the goals and assumptions of economic mechanisms often do not match those of networked systems. For example, while auction theory may assume a centralized clearing house, there is no analog in a decentralized system seeking to avoid single points of failure or centralized policies. Similarly, game theory often assumes that each player is able to observe everyone else's actions, or at the very least know how many other players there are, but maintaining perfect system-wide information is impossible in most systems. In other words, not all incentive mechanisms are systems-compatible. The main contribution of this dissertation is the design, implementation, and evaluation of various systems-compatible incentive mechanisms and their application to a wide range of deployable systems. These systems include BitTorrent, which is used to distribute a large file to a large number of downloaders, PeerWise, which leverages user cooperation to achieve lower latencies in Internet routing, and Hoodnets, a new system I present that allows users to share their cellular data access to obtain greater bandwidth on their mobile devices. Each of these systems represents a different point in the design space of systems-compatible incentives. Taken together, along with their implementations and evaluations, these systems demonstrate that systems-compatibility is crucial in achieving practical incentives in real systems. I present design principles outlining how to achieve systems-compatible incentives, which may serve an even broader range of systems than considered herein. I conclude this dissertation with what I consider to be the most important open problems in aligning the competing interests of the Internet's participants

Modelling and analysis of Internet pricing and revenue distribution.

Cheung, Yang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 85-89).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 2 --- Related Works --- p.4Chapter 2.1 --- Pricing Mechanisms --- p.4Chapter 2.1.1 --- Current Situation --- p.4Chapter 2.1.2 --- Proposed Pricing Mechanisms --- p.6Chapter 2.1.3 --- Congestion Pricing --- p.9Chapter 2.1.4 --- Bandwidth Allocation Mechanism --- p.10Chapter 2.2 --- Revenue Distribution Mechanisms --- p.12Chapter 2.2.1 --- Current Situation --- p.12Chapter 2.2.2 --- Novel Revenue Distribution Mechanisms --- p.13Chapter 3 --- Problems in Revenue Collecting Stage --- p.16Chapter 3.1 --- Introduction --- p.17Chapter 3.1.1 --- Desirable Characteristics of Internet Pricing Mechanism --- p.19Chapter 3.1.2 --- Existing Solution --- p.21Chapter 3.1.3 --- Applying Insurance into Internet Pricing --- p.22Chapter 3.2 --- The Internet Pricing Model --- p.25Chapter 3.2.1 --- System Model --- p.25Chapter 3.2.2 --- Decisions Time Scales --- p.27Chapter 3.2.3 --- Micro Time Scale Pricing --- p.28Chapter 3.2.4 --- Macro Time Scale Pricing --- p.29Chapter 3.3 --- Actuarially Fair Coinsurance Function --- p.30Chapter 3.3.1 --- The Actuarially Fair Coinsurance Function --- p.32Chapter 3.3.2 --- Properties of the Actuarially Fair Coinsurance Function --- p.34Chapter 3.3.3 --- How Much Insurance Should a User Buy? --- p.35Chapter 3.3.4 --- Numerical Examples --- p.37Chapter 3.4 --- Premium Coinsurance Function --- p.40Chapter 3.4.1 --- Problems of Allowing Pull Insurance --- p.41Chapter 3.4.2 --- The Premium Coinsurance Function --- p.43Chapter 3.4.3 --- Properties of the premium coinsurance function --- p.44Chapter 3.4.4 --- Numerical Example --- p.46Chapter 4 --- Problems in Revenue Distributing Stage --- p.48Chapter 4.1 --- Introduction --- p.50Chapter 4.2 --- System Models --- p.52Chapter 4.2.1 --- Topology Model --- p.52Chapter 4.2.2 --- Traffic Model --- p.54Chapter 4.3 --- Settlement Model and Definition of Fair Price --- p.55Chapter 4.3.1 --- Bilateral Settlement --- p.55Chapter 4.3.2 --- Shapley Settlement --- p.58Chapter 4.4 --- Fair Price Achieving the Shapley Value: The Symmetric Case --- p.61Chapter 4.5 --- Properties of the Fair Prices in the Symmetric Case --- p.65Chapter 4.5.1 --- Sensitivity to traffic pattern α --- p.65Chapter 4.5.2 --- Sensitivity to network topology parame- ters p and d --- p.67Chapter 4.6 --- Fair Price Achieving the Shapley Value: The Asym- metric Case --- p.70Chapter 4.7 --- Distributed and Local Approximation of the Fair Price --- p.71Chapter 5 --- Conclusions --- p.74Chapter A --- Mathematical Proofs --- p.77Chapter A.l --- Mathematical Proof for Chapter 3 --- p.77Chapter A.1.1 --- Proof of Theorem 3.3.2 --- p.77Chapter A.1.2 --- Proof of Proposition 3.3.5 --- p.77Chapter A.1.3 --- Proof of Proposition 3.3.6 --- p.78Chapter A.1.4 --- Proof of Proposition 3.3.7 --- p.78Chapter A.1.5 --- Proof of Proposition 3.4.1 --- p.79Chapter A.1.6 --- Proof of Proposition 3.4.3 --- p.79Chapter A.1.7 --- Proof of Proposition 3.4.5 --- p.80Chapter A.2 --- Mathematical Proof for Chapter 4 --- p.81Chapter A.2.1 --- Proof of Theorem 4.4.2 --- p.81Chapter A.2.2 --- Proof of Theorem (4.6.1) --- p.83Chapter A.2.3 --- Terms Description of Equation (4.1) --- p.84Bibliography --- p.8