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Little q download torrent games. Little Q Download torrent search. We use cookies to offer you a better experience, personalize content, tailor advertising, provide social media features, and better understand the use of our services. To learn more or modify/prevent the use of cookies, see our Cookie Policy and Privacy Policy. BitTorrent (BT) is one of the most popular Peer-to-Peer (P2P) network applications. Most characteristics (except the topology) of BT network have been examined extensively by measurement approaches. In this work, we deploy a measurement system to study the performance-related properties of BT topologies. We also use our measurement system to verify some previous simulation and experiment results obtained by other researchers. Different from previous results, we observe that a BT swarm has short distance, low clustering coefficient and Gaussian-like degree-frequency distribution. This indicates that a BT swarm is very close to a random network rather than a scale-free network or a small world. We observe that the diameter of a BT network at the initial stage is small even when 95% of peers use the peer exchange extension but the networks are not fully connected at the steady stages. Understanding the Topologies of BitTorrent Networks: A Measurement View Abstract ?BitTorrent (BT) is one of the most popular Peer-to- Peer (P2P) network applications. Most ch aracteristics (except the topology) of BT network have been examined extensively by measurement approaches. We also use ou r measurement system to verify some previous simulation and experiment results obtain ed by other researchers. Different from previous results, we observe that a BT swarm has short distance, lo w clustering coefficient and Gaussian-like degree-frequenc y distribution. We observe that the diameter of a BT network at the initial stage is small even when 95% of peers use the peer exchange extension but the networks are not fully connected at the steady st ages. Keywords? BitTorrent; topology; measurement; performance I. I NTRODUCTION During the last decade, BitTo rrent (BT) has been widely used in file-sharing for its efficiency and robustness. Researchers and developers have been working to improve its performance, and lots of measurement studies have been performed on the swarm evolution [1], popularit y [2], and availability [3], etc. Despite it is import to better understand BT networks and analyze BT performance, however, little is known about the topology character istics of real BT networks. Unlike other P2P systems, BT does not provide a global topology discovering mechanism. Both trackers and peers do not have the knowledge about all peers and their connect ions. Fortunately, the BT peer exchange extension (PEX) [4], which allows peers to exchange the information of newly connected and disconnected peers periodically, provides an opportunity to learn the connectivity between pees. Therefore we design a measurement system to collect the peers from trackers and connections from PEX to form topologies of BT net works. In this paper, we analyze some topology properties of BT overlay by measurement results of real world. Our goal is to provide a measurement view of existing BT topologie s and verify the previous results of theoretical analysis [5], simulations [6] and controlled experiments [7]. We examine the peer degree distribution, peer distance and clustering coefficient in different swarm e volution stages. We also try to explain the potential influential factors of some results and its effects on BT performance from the protocol design and cl ient implementation perspectives. Our main findings can be summarized as follows: (1) We observe that there is no large amount of low- degree peers to form a power-law distribution. Especially in the steady stage, the peer degree di stribution of large-scale swarm follows a Gaussian distribution. This result suggest s BT network is more likely random other than scale-free, w hich is different from previous results. (2) The connection limitation of BT clients limi t the connection number of many peers in the initial stage but affect less in the steady stage. More than 70% of peers have the degrees less than 50 in the steady stage. (3) In the steady st age, the peer distances between most peers are small (larger than the initial stage), and the clustering coefficient of network is low (lower than the initial stag e), further confirming the BT is more likely a random network and suggesting that the BT is not a small world. Especiall y, the networks are not fully connected at the steady stages. (4) Different from [7], we find out that the diameter of BT networks in the initial stage are still very small (<6) although more than 95% of peers applying PEX in exi sting BT networks. The rest of this paper is organized as follows. We introduce some related work in section II and present our measurement methodology in section III. In section IV, we anal yze the measurement results and study the properties of BT topologi es. We conclude this paper in section V. II. R ELATED W ORK There are many measurement studies on characterizing the overlay topologies of P2P networks [8] [9] except B itTorrent. Despite some work [10]-[12] focus on the locality distribution of BT, however, only a small number of papers [5]-[ 7], [13] examine the properties of BT topologies extensively. Out of these, only [10] uses the measurement approach. Al-Hamra et al. [6] analyze how the overlay properties impact BT efficiency by extens ive simulations. They show that the BT overlay is robust but not a random graph. They also find that the BT PEX generates larg e-diameter chain-like overlays in the initial swarm stages. However, Wu et al. [4] do not Majing Su 1, Hongli Zhang 1, Xiaojiang Du 2, Binxing Fang 1, Mohsen Guizani 3 1 School of Computer Science and Technology, Ha rbin Institute of Technology, Harbin, China {sumajing, zhl, bxfang} 2 Dept. of Computer and Information Sciences, Temple University, Phila delphia, PA, 19122, USA 3 Qatar University, Doha, Qatar, 978-1-4673-0921-9/12/$31. 00 ©2012 IEEE Globecom 2012 - Communications Software, Services and Multimedia Symposium 1994 observe the chain-like topology in their PlanetLab [14] experiments. Dale et al. [7] study the topology properti es by deploying experimental swarms with a m odified BT client on more than 400 PlanetLab nodes. Their results show that the network of peers that are unchoked by others is scale-free. They find out that there are no clear evidences of persistent clustering and presences of small word. However, in real world, due to the Network Address Translations (NATs) and fire walls, the connectivity between peers is much worse than that of PlanetLab nodes, which may lead different peer degree distribution. Besides, the swarm size and diversity of BT clients may also affect the peer connections. Zhong et al. [5] analyze the topological properties by a directed weighted graph model. They find that the node strength of BT network fol lows a power-law distribution. When the seeder proportion incre ases, a BT network tends to be less clustered. The average shortest path length grows as network size expands. Fauzie’s work [13] is the closest one to ours. Fauzi e et al. collect the information of peers and connections by a modified rasterbar libtorrent client [15]. They join 35 TV series torrents and take the snapshots with 3-minutes duration for about 8 day s. They find out that the degree distribution is a power-l aw with exponential cutoff and the clustering is not obvi ously. However, we argue that the 3 minutes duration may not be sufficient to find all peers of hot torrents due to the discovering ability of the BT client. Different from [5]-[7], in this paper, we study the topology characteristics of real BT networks by measurement rather than theoretical analyses [5], simula tions [6] or experiments [7]. Unlike [13], we design a measur ement system that uses both active and passive approaches to get comprehensive temporal topologies of BT networks in a short time. Furthermore, we provide more detail analysis on th e topology charact eristics (e. g. peer degree distribution and clustering) than Fauzie et al. [13]. In addition, we focus on thes e characteristics in different swarm stages and give some potential explanations t o our results. III. T OPOLOGY M EASUREMENT A. Design of Our Measurement System We design a measurement syst em to capture snapshots of BT swarms, shown in Fig. 1. A snaps hot is a temporal situation of a BT swarm observed at a pa rticular moment, and it includes peers, the status of each peer (e. g., its download percentage) and connections among peers. We crawl peers from tracker and collect connection information by exchanging PEX messages with peers. We use both active and passive approaches to fast capture snapshots. The dynamic and large scales of BT networks are major challenges. The active measurement of each snapshot consists of a peer finding stage and a peer detecting stage. In the peer finding stage, the system requests peer lists from trackers extracted from the torrents, and then conn ects with these peers to find more peers from PEX messages. Repeat this process until the stop condition is met. In the peer detecting stage, the system connects to all the peers (found in the first stage), exchanges BT messages, and records the BITFIELD (from BITFIELD Fig. 1: Illustration of our approach message) and neighbors (from PEX messages) of each connected peer. To save the bandwidth, the system does not download any file data. We apply a passive approach to get PEX and BITFIELD of the unreachable peers (e. behind firewalls or NATs). The system listens and responds to requests from these peers and logs their BITFIELD and ne ighbors. The system keeps connections with all connected peer s to track their status. In our post-processing, the logs are sp lit according to the start time and end time of each s
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