Analysis of P2P File Sharing Network's Credit System For
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Analysis of P2P File Sharing Network’s Credit System for Fairness Management Yunzhao Li Don Gruenbacher Electrical and Computer Engineering Electrical and Computer Engineering Kansas State University Kansas State University [email protected] [email protected] Abstract- Fairness is an important management issue for For example, in [2], the global reputation scores of all nodes peer-to-peer file sharing systems. In this paper, we study the in the current unstructured P2P network are collected, credit system of the P2P file sharing network eMule (http://www.emule-project.net) through a simple queueing calculated, and then distributed in the whole system. network model. Numerical analysis and experimental results Unlike the previous fairness policies, the eMule P2P file show that this local credit strategy could effectively deal with free sharing application adopts a simple local trust system called a riders and provide fairness for the system during a single file credit system to encourage peers to exchange information exchange. Using this model, we also investigate different while restricting free riders. The eMule network is a local management strategies for dealing with the newcomer fairness issue. We propose a simple, private history-based scheme to reputation system that only allows credit to be exchanged balance the fairness between two types of newcomers. between the uploader and its downloader. This is different from a global reputation system that allows credit to be exchanged among all peers. While almost all of the current P2P research contributes to I. INTRODUCTION multiple aspects of BitTorrent, eMule’s fairness issue is The recent popularity and success of peer-to-peer (P2P) file lightly addressed even though it significantly impacts whole sharing has established its importance while also contributing system performance. Currently, global and public history- a majority of the traffic on the Internet. In contrast to the based reputation approaches can be regarded as possible traditional client-server content distribution system, every solutions for P2P network’s fairness management. However, member of a P2P file sharing network has an equivalent role. compared to the complexity of the global system, the simple, Not only can each peer download from other peers, but it is local, and private history-based approach also needs to be also responsible for uploading content as a server. This often carefully investigated. Therefore, the work presented here results in fairness issues as many peers called free riders may evaluates eMule’s local and private history-based credit only want to download without uploading or sharing their own system for maintaining fairness. The primary contributions of content. This paper evaluates the performance of two types of this paper are: peers that are subjected to a fairness management policy 1) a simple queueing network model is developed to which gives download priority to users who also upload their investigate the impact of credit on system fairness; content to the network. both the numerical analysis and the experiments in the The distributed architecture of a P2P system does not easily real world illustrate that even if the incentive algorithm lend itself to control free riders in order to maintain fairness. is local-based, it can still deal with free riders and In fact, as a somewhat autonomous system, the file sharing provide fairness during a single file exchange when performance of a P2P network greatly depends on each peer’s compared to BitTorrent’s “TFT” incentive algorithm; cooperation. A peer should be willing to voluntarily donate 2) our model is used to compare two different types of resources in exchange for content that it would like from other credit strategies for providing fairness to the newcomer. peers. However, selfish peers exist who benefit from other A simple, long-duration, and private history-based peers’ contribution yet refuse to offer in exchange their own credit scheme is proposed which will better reward the resources. generous newcomer while limiting the selfish free rider. Such selfish behavior will result in the eventual collapse of The paper is organized as follows. Section 2 discusses the whole system. In an attempt to dissuade this behavior, important related work. In section 3, a queueing network various incentive management strategies are introduced to model is presented to study the fairness of eMule. The current P2P file sharing networks to reward general peers numerical analysis and corresponding experiment results are which share their information and penalize free riders. For shown in section 4. Section 5 discusses the newcomer example, a BitTorrent client prefers to allocate upload management issue and an improved fairness design is bandwidth to peers who send data to it with a rate-based tit- presented for providing fairness to newcomers, followed by for-tat fairness policy [1]. Another fairness control strategy is summary and future work in section 6. to build a global trust management system, which could help peers choose their neighbors based on different trust levels. 978-1-4244-5367-2/10/$26.00 c 2010 IEEE 88 II. RELATED WORK eMule employs an incentive fairness algorithm based on a There are a large number of publications related to various local private history credit record to encourage uploading, aspects of peer-to-peer file sharing such as performance, which means the credit is used to reward a peers’ sharing fairness, and security. The work in this paper is motivated by behavior and provide benefit for future downloading. For [3] and [4]. In [3], a mathematical model is developed for example, if peer A uploades a resource to peer B, peer B will studying BitTorrent’s performance, and the authors find the give some credit to peer A, and this credit record is only held distribution of download peers into the system takes the form by peer B. When peer A later wants to download content from of an asymmetric U-shaped curve. This means there are more peer B, it will be given higher priority service from peer B peers blocked at the beginning and end segments of the than other neighbors of B without credit. Because credit download process than peers at the other download time rewards can only be exchanged between the downloader and period. In [4], a general stochastic analytic framework for its directed uploader, the credit information is not spread incentive-based file-swarming research is proposed, and the among other peers. Thus eMule’s credit is a local private first-chunk problem is also shown in the authors’ analytical history-based credit system and not a global public history- bound and simulation result. The first-chunk problem is based system like some kinds of social reputation networks. related to how the system manages newcomers for which a Compared with BitTorrent’s use of a simple accept or reject more detail discussion will be given in the following section. policy for each requester which is unfair for low-bandwidth Other works are also given attention to P2P system fairness. users, eMule has implemented a complicated priority queue In [5] and [6], game theory is used to investigate the component to cache various requests independent of the relationship among peers. The fairness policy of a current customer’s upload bandwidth. The positions of peers in an peer-to-peer file sharing system such as BitTorrent is shown to eMule uploading queue are determined by their past credit not be robust in [7], and the free rider could obtain a higher from the service provider. Because the entire download download rate than a tit-for-tat compliant client [8]. In [2] and process is chunk-based, and each chunk can be independently [9], global reputation approaches are suggested for dealing exchanged among peers, eMule’s credit operations naturally with free riders and malicious peers. However, reputation is follow this exchange process. Moreover, the unconsumed always vulnerable when the free rider repeatedly changes its credit will reside with peers for a long time period (several ID for additional benefit, or more than one free rider work months) [17], and this credit can also be used for future file together as a coalition [10]. Furthermore, because of the exchanges. complexity of implementation, the global reputation approach B. Mathematical Model hasn’t been popularly employed from existing P2P file sharing systems in the real world. We extend the established model in [3] [4] which only focus Although BitTorrent has gathered more attention than on the general behavior for P2P file sharing, and distinguish eMule in the research community, there are a number of the peers into two types within the model: the general peer papers that do address eMule’s performance. In [11], a fluid who obeys the incentive rule to download and upload, and the model is developed for the analysis of a system like eMule, free rider who is the extreme malicious peer only downloading and an optimal upload strategy is given. In [12], the authors from others and refusing to contribute. Most general peers investigate file diffusion through an epidemic method, and the possess positive credit due to their incessant sharing behavior, influence from corrupted files is shown. The projects in both and as long as a peer has credit, the amount of credit does not [13] and [14] respectively measure P2P networks such as differentiate one peer from another. eMule from both the client viewpoint and the ISP’s viewpoint. If a shared file has K chunks, the peer’s entire downloading The measurements include eMule’s traffic characterization, progress could be described by the completion of a task for the whole system’s capacity, and sharing files’ distribution. each chunk downloaded. The file will be completely downloaded at the completion of the Kth task. A simple tandem queueing network that uses a total of K service III.