Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

A Framework For Efficient Data Distribution In Peer-to-peer Networks.

Peer to Peer (P2P) models are based on user altruism, wherein a user shares its content with other users in the pool and it also has an interest in the content of the other nodes. Most P2P systems in their current form are not fair in terms of the content served by a peer and the service obtained from swarm. Most systems suffer from free rider\u27s problem where many high uplink capacity peers contribute much more than they should while many others get a free ride for downloading the content. This leaves high capacity nodes with very little or no motivation to contribute. Many times such resourceful nodes exit the swarm or don\u27t even participate. The whole scenario is unfavorable and disappointing for P2P networks in general, where participation is a must and a very important feature. As the number of users increases in the swarm, the swarm becomes robust and scalable. Other important issues in the present day P2P system are below optimal Quality of Service (QoS) in terms of download time, end-to-end latency and jitter rate, uplink utilization, excessive cross ISP traffic, security and cheating threats etc. These current day problems in P2P networks serve as a motivation for present work. To this end, we present an efficient data distribution framework in Peer-to-Peer (P2P) networks for media streaming and file sharing domain. The experiments with our model, an alliance based peering scheme for media streaming, show that such a scheme distributes data to the swarm members in a near-optimal way. Alliances are small groups of nodes that share data and other vital information for symbiotic association. We show that alliance formation is a loosely coupled and an effective way to organize the peers and our model maps to a small world network, which form efficient overlay structures and are robust to network perturbations such as churn. We present a comparative simulation based study of our model with CoolStreaming/DONet (a popular model) and present a quantitative performance evaluation. Simulation results show that our model scales well under varying workloads and conditions, delivers near optimal levels of QoS, reduces cross ISP traffic considerably and for most cases, performs at par or even better than Cool-Streaming/DONet. In the next phase of our work, we focussed on BitTorrent P2P model as it the most widely used file sharing protocol. Many studies in academia and industry have shown that though BitTorrent scales very well but is far from optimal in terms of fairness to end users, download time and uplink utilization. Furthermore, random peering and data distribution in such model lead to suboptimal performance. Lately, new breed of BitTorrent clients like BitTyrant have shown successful strategic attacks against BitTorrent. Strategic peers configure the BitTorrent client software such that for very less or no contribution, they can obtain good download speeds. Such strategic nodes exploit the altruism in the swarm and consume resources at the expense of other honest nodes and create an unfair swarm. More unfairness is generated in the swarm with the presence of heterogeneous bandwidth nodes. We investigate and propose a new token-based anti-strategic policy that could be used in BitTorrent to minimize the free-riding by strategic clients. We also proposed other policies against strategic attacks that include using a smart tracker that denies the request of strategic clients for peer listmultiple times, and black listing the non-behaving nodes that do not follow the protocol policies. These policies help to stop the strategic behavior of peers to a large extent and improve overall system performance. We also quantify and validate the benefits of using bandwidth peer matching policy. Our simulations results show that with the above proposed changes, uplink utilization and mean download time in BitTorrent network improves considerably. It leaves strategic clients with little or no incentive to behave greedily. This reduces free riding and creates fairer swarm with very little computational overhead. Finally, we show that our model is self healing model where user behavior changes from selfish to altruistic in the presence of the aforementioned policies

Providing incentive to peer-to-peer applications

Cooperative peer-to-peer applications are designed to share the resources of participating computers for the common good of ail users. However, users do not necessarily have an incentive to donate resources to the system if they can use the system's resources for free. As commonly observed in deployed applications, this situation adversely affects the applications' performance and sometimes even their availability and usability. While traditional resource management is handled by a centralized enforcement entity, adopting similar solution raises new concerns for distributed peer-to-peer systems. This dissertation proposes to solve the incentive problem in peer-to-peer applications by designing fair sharing policies and enforcing these policies in a distributed manner. The feasibility and practicability of this approach is demonstrated through numerous applications, namely archival storage systems, streaming systems, content distribution systems, and anonymous communication systems

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

Robust peer-to-peer systems

textPeer-to-peer (p2p) approaches are an increasingly effective way to deploy services. Popular examples include BitTorrent, Skype, and KaZaA. These approaches are attractive because they can be highly fault-tolerant, scalable, adaptive, and less expensive than a more centralized solution. Cooperation lies at the heart of these strengths. Yet, in settings where working together is crucial, a natural question is: "What if users stop cooperating?" After all, cooperative services are typically deployed over multiple administrative domains, and thus vulnerable to Byzantine failures and users who may act selfishly. This dissertation explores how to construct p2p systems to tolerate Byzantine participants while also incentivizing selfish participants to contribute resources. We describe how to balance obedience against choice in building a robust p2p live streaming system. Imposing obedience is desirable as it leaves little room for peers to attack or cheat the system. However, providing choice is also attractive as it allows us to engineer flexible and efficient solutions. We first focus on obedience by using Nash equilibria to drive the design of BAR Gossip, the first gossip protocol that is resilient to Byzantine and selfish nodes. BAR Gossip relies on verifiable pseudo-random partner selection to eliminate non-determinism, which can be used to game the system, while maintaining the robustness and rapid convergence of traditional gossip. A novel fair enough exchange primitive entices cooperation among selfish peers on short timescales, thereby avoiding the need for distributed reputation schemes. We next focus on tempering obedience with choice by using approximate equilibria to guide the construction of a novel p2p live streaming system. These equilibria allow us to design incentives to limit selfish behavior rigorously, yet provide sufficient flexibility to build practical systems. We show the advantages of using an [element of]-Nash equilibrium, instead of an exact Nash, to design and implement FlightPath, our live streaming system that uses bandwidth efficiently, absorbs flash crowds, adapts to sudden peer departures, handles churn, and tolerates malicious activity.Computer Science

Design of Overlay Networks for Internet Multicast - Doctoral Dissertation, August 2002

Multicast is an efficient transmission scheme for supporting group communication in networks. Contrasted with unicast, where multiple point-to-point connections must be used to support communications among a group of users, multicast is more efficient because each data packet is replicated in the network – at the branching points leading to distinguished destinations, thus reducing the transmission load on the data sources and traffic load on the network links. To implement multicast, networks need to incorporate new routing and forwarding mechanisms in addition to the existing are not adequately supported in the current networks. The IP multicast are not adequately supported in the current networks. The IP multicast solution has serious scaling and deployment limitations, and cannot be easily extended to provide more enhanced data services. Furthermore, and perhaps most importantly, IP multicast has ignored the economic nature of the problem, lacking incentives for service providers to deploy the service in wide area networks. Overlay multicast holds promise for the realization of large scale Internet multicast services. An overlay network is a virtual topology constructed on top of the Internet infrastructure. The concept of overlay networks enables multicast to be deployed as a service network rather than a network primitive mechanism, allowing deployment over heterogeneous networks without the need of universal network support. This dissertation addresses the network design aspects of overlay networks to provide scalable multicast services in the Internet. The resources and the network cost in the context of overlay networks are different from that in conventional networks, presenting new challenges and new problems to solve. Our design goal are the maximization of network utility and improved service quality. As the overall network design problem is extremely complex, we divide the problem into three components: the efficient management of session traffic (multicast routing), the provisioning of overlay network resources (bandwidth dimensioning) and overlay topology optimization (service placement). The combined solution provides a comprehensive procedure for planning and managing an overlay multicast network. We also consider a complementary form of overlay multicast called application-level multicast (ALMI). ALMI allows end systems to directly create an overlay multicast session among themselves. This gives applications the flexibility to communicate without relying on service provides. The tradeoff is that users do not have direct control on the topology and data paths taken by the session flows and will typically get lower quality of service due to the best effort nature of the Internet environment. ALMI is therefore suitable for sessions of small size or sessions where all members are well connected to the network. Furthermore, the ALMI framework allows us to experiment with application specific components such as data reliability, in order to identify a useful set of communication semantic for enhanced data services