Johan A. Pouwelse

The bittorrent p2p file-sharing system: measurements and analysis

Of the many P2P file-sharing prototypes in existence, BitTorrent is one of the few that has managed to attract millions of users. BitTorrent relies on other (global) components for file search, employs a moderator system to ensure the integrity of file data, and uses a bartering technique for downloading in order to prevent users from freeriding. In this paper we present a measurement study of BitTorrent in which we focus on four issues, viz. availability, integrity, flashcrowd handling, and download performance. The purpose of this paper is to aid in the understanding of a real P2P system that apparently has the right mechanisms to attract a large user community, to provide measurement data that may be useful in modeling P2P systems, and to identify design issues in such systems.

TRIBLER: a social-based peer-to-peer system

Most current peer‐to‐peer (P2P) file‐sharing systems treat their users as anonymous, unrelated entities, and completely disregard any social relationships between them. However, social phenomena such as friendship and the existence of communities of users with similar tastes or interests may well be exploited in such systems in order to increase their usability and performance. In this paper we present a novel social‐based P2P file‐sharing paradigm that exploits social phenomena by maintaining social networks and using these in content discovery, content recommendation, and downloading. Based on this paradigms main concepts such as taste buddies and friends, we have designed and implemented the TRIBLER P2P file‐sharing system as a set of extensions to BitTorrent. We present and discuss the design of TRIBLER, and we show evidence that TRIBLER enables fast content discovery and recommendation at a low additional overhead, and a significant improvement in download performance. Copyright

Dynamic voltage scaling on a low-power microprocessor

Power consumption is the limiting factor for the functionality of future wearable devices. Since interactive applications like wireless information access generate bursts of activities, it is important to match the performance of the wearable device accordingly. This paper describes a system with a microprocessor whose speed can be varied (frequency scaling) as well as its supply voltage. Voltage scaling is important for reducing power consumption to very low values when operating at low speeds. Measurements show that the energy per instruction at minimal speed is 1/5 of the energy required at full speed. The frequency and voltage can be scaled dynamically from user space in only 140 μs. This allows power-aware applications to quickly adjust the performance level of the processor whenever the workload changes. Experiments with an H.263 video benchmark show that the power-aware decoder outperforms a static fixed-frequency policy as well as a dynamic interval-based scheduler.

Give-to-Get : free-riding resilient video-on-demand in P2P systems

Centralised solutions for Video-on-Demand (VoD) services, which stream pre-recorded video content to multiple clients who start watching at the moments of their own choosing, are not scalable because of the high bandwidth requirements of the central video servers. Peer-to-peer (P2P) techniques which let the clients distribute the video content among themselves, can be used to alleviate this problem. However, such techniques may introduce the problem of free-riding, with some peers in the P2P network not forwarding the video content to others if there is no incentive to do so. When the P2P network contains too many free-riders, an increasing number of the well-behaving peers may not achieve high enough download speeds to maintain an acceptable service. In this paper we propose Give-to-Get, a P2P VoD algorithm which discourages free-riding by letting peers favour uploading to other peers who have proven to be good uploaders. As a consequence, free-riders are only tolerated as long as there is spare capacity in the system. Our simulations show that even if 20% of the peers are free-riders, Give-to-Get continues to provide good performance to the well-behaving peers. In particular, they show that Give-to-Get performs very well for short videos, which dominate the current VoD traffic on the Internet.

Application-directed voltage scaling

Clock (and voltage) scheduling is an important technique to reduce the energy consumption of processors that support voltage scaling. It is difficult, however, to achieve good results using only statistics from the operating system level when applications show bursty (unpredictable) behavior. We take the approach that such applications must be made power-aware and specify their average execution time (AET) and the deadline to the scheduler controlling the clock speed and processor voltage. This paper describes our energy priority scheduling (EPS) algorithm supporting power-aware applications. EPS orders tasks according to how tight their deadlines are and how often tasks overlap. Low-priority tasks are scheduled first, since they can be easily preempted to accommodate for high-priority tasks later. The EPS algorithm does not always yield the optimal schedule, but has a low complexity. We have implemented EPS on a StrongARM-based variable-voltage platform. We conducted experiments with a modified video decoder that estimates the AET of each frame. Measurements show that application-directed voltage scaling reduces processor power consumption with 50% for the bursty video decoder without missing any frame deadlines.

Correlating Topology and Path Characteristics of Overlay Networks and the Internet

Real-world IP applications such as peer-to-peer file-sharing are now able to benefit from network and location awareness. It is therefore crucial to understand the relation between underlay and overlay networks and to characterize the behavior of real users with regard to the Internet. For this purpose, we have designed and implemented MULTI-PROBE, a framework for large-scale P2P file-sharing measurements. Using this framework, we have performed measurements of BitTorrent, which is currently the P2P file sharing network with the largest amount of Internet traffic. We analyze and correlate these measurements to provide new insights into the topology, the connectivity, and the path characteristics of the Internet parts underlying P2P networks, as well as to present unique information on the BitTorrent throughput and connectivity

Free-Riding, Fairness, and Firewalls in P2P File-Sharing

Peer-to-peer file-sharing networks depend on peers uploading data to each other. Some peers, called free-riders, will not upload data unless there is an incentive to do so. Algorithms designed to prevent free-riding typically assume that connectivity is not a problem. However, on the Internet, a large fraction of the peers resides behind a firewall or NAT, making them unable to accept incoming connections. In this paper, we will prove that it is impossible to prevent free-riding when more than half of the peers are firewalled, and we will provide bounds on the sharing ratios (defined as the number of bytes uploaded divided by the number of bytes downloaded) of both firewalled and non-firewalled peers. Firewall puncturing techniques are complex but can be used to connect two firewalled peers; we will provide a bound on their required effectiveness in order to achieve fairness.We confirm our theory by simulating individual BitTorrent swarms (sets of peers that download the same file), and show that the theoretical bounds can be met in systems with many firewalled peers. We have also collected statistics covering thousands of BitTorrent swarms in several communities, both open and closed; the latter ban peers if their sharing ratios drop below a certain treshhold. We found 45% of the peers to be firewalled in the closed communities, as opposed to 66% in the open communities, which correlates with our theory that to obtain fair sharing ratios for all peers, at most half of them can be behind firewalls.

The Design and Deployment of a BitTorrent Live Video Streaming Solution

The BitTorrent protocol is by far the most popular protocol for offline peer-to-peer video distribution on the Internet. BitTorrent has previously been extended to support the streaming of recorded video, that is, Video-on-Demand (VoD). In this paper, we take this support for video streaming a step further by presenting extensions to BitTorrent for supporting live video streaming, which we have implemented in our BitTorrent client called Tribler. We have tested our extensions both by running simulations, and by deploying our implementation in a public trial in the Internet, using the optimal values of several parameters as found in the simulations. We analyse the performance of Tribler in systems with varying values for the percentage of peers behind a firewall or NAT, which we consider to be one of the key parameters in the performance of deployed P2P systems. Our public trial lasted 9 days, during which 4555 unique peers participated from around the globe. We found 61% of the peers to be behind a firewall, a level at which our simulations still indicate acceptable performance. Most of the peers indeed obtained good performance, with for instance a very low prebuffering time before playback starts, indicating the feasibility of our approach. The median prebuffering time we measured was 3.6 seconds, which is 3--10 times shorter than the prebuffering time measured in other deployed peer-to-peer systems.

Personalization on a peer-to-peer television system

We introduce personalization on Tribler, a peer-to-peer (P2P) television system. Personalization allows users to browse programs much more efficiently according to their taste. It also enables to build social networks that can improve the performance of current P2P systems considerably, by increasing content availability, trust and the realization of proper incentives to exchange content. This paper presents a novel scheme, called BuddyCast, that builds such a social network for a user by exchanging user interest profiles using exploitation and exploration principles. Additionally, we show how the interest of a user in TV programs can be predicted from the zapping behavior by the introduced user-item relevance models, thereby avoiding the explicit rating of TV programs. Further, we present how the social network of a user can be used to realize a truly distributed recommendation of TV programs. Finally, we demonstrate a novel user interface for the personalized peer-to-peer television system that encompasses a personalized tag-based navigation to browse the available distributed content. The user interface also visualizes the social network of a user, thereby increasing community feeling which increases trust amongst users and within available content and creates incentives of to exchange content within the community.

Design space analysis for modeling incentives in distributed systems

Distributed systems without a central authority, such as peer-to-peer (P2P) systems, employ incentives to encourage nodes to follow the prescribed protocol. Game theoretic analysis is often used to evaluate incentives in such systems. However, most game-theoretic analyses of distributed systems do not adequately model the repeated interactions of nodes inherent in such systems. We present a game-theoretic analysis of a popular P2P protocol, Bit-Torrent, that models the repeated interactions in such protocols. We also note that an analytical approach for modeling incentives is often infeasible given the complicated nature of most deployed protocols. In order to comprehensively model incentives in complex protocols, we propose a simulation-based method, which we call Design Space Analysis (DSA). DSA provides a tractable analysis of competing protocol variants within a detailed design space. We apply DSA to P2P file swarming systems. With extensive simulations we analyze a wide-range of protocol variants and gain insights into their robustness and performance. To validate these results and to demonstrate the efficacy of DSA, we modify an instrumented BitTorrent client and evaluate protocols discovered using DSA. We show that they yield higher system performance and robustness relative to the reference implementation.