In this paper, we consider Peer-to-Peer Video-on-Demand (P2P VoD) systems based on the BitTorrent file sharing protocol. Since the Rarest First policy adopted in the original BitTorrent protocol frequently fails to collect pieces corresponding to a video file by their playback time, we need to develop a new piece selection rule particularly designed for P2P VoDs. In the proposed scheme, we assume the existence of a media server which can upload any piece upon request, and try to bound the load of such media server with two techniques. The first technique is to estimate pieces which are not held by any peer and prefetch them from the media server. The second technique is to switch the mode of each peer according to the estimated size of the P2P network. The performance of the proposed scheme is evaluated by simulation.
Peer-to-peer (P2P) technology has gained popularity as a way to enhance system performance. Nodes in a P2P network work together by providing network resources to one another. In this study, we examine the use of P2P technology for video streaming and develop a distributed incentive mechanism to prevent free-riding. Our proposed solution combines WebTorrent and the Solana blockchain and can be accessed through a web browser. To incentivize uploads, some of the received video chunks are encrypted using AES. Smart contracts on the blockchain are used for third-party verification of uploads and for managing access to the video content. Experimental results on a test network showed that our system can encrypt and decrypt chunks in about 1/40th the time it takes using WebRTC, without affecting the quality of video streaming. Smart contracts were also found to quickly verify uploads in about 860 milliseconds. The paper also explores how to effectively reward virtual points for uploads.
Satoshi FUJITA Masafumi YAMASHITA
In this paper, we consider the static multiprocessor scheduling problem for a class of multiprocessor systems consisting of m ( 1) identical processors connected by a complete network. The objective of this survey is to give a panoramic view of theoretical and/or practical approaches for solving the problem, that have been extensively conducted during the past three decades.
Taishi NAKASHIMA Satoshi FUJITA
This paper proposes a consistency maintenance scheme for P2P file sharing systems. The basic idea of the proposed scheme is to construct a static tree for each shared file to efficiently propagate the update information to all replica peers. The link to the root of the trees is acquired by referring to a Chord ring which stores the mapping from the set of shared files to the set of tree roots. The performance of the scheme is evaluated by simulation. The simulation result indicates that: 1) it reduces the number of messages in the Li's scheme by 54%, 2) it reduces the propagation delay of the scheme by more than 10%, and 3) the increase of the delay due to peer churns is effectively bounded provided that the percentage of leaving peers is less than 40%.
This paper proposes a method to reduce the playback suspension in a Video-on-Demand system based on the Peer-to-Peer technology (P2P VoD). Our main contribution is twofold. The first is the proposal of a hierarchical P2P architecture with the notion of dynamic swarms. Swarm is a group of peers to have similar playback position and those swarms are connected with an overlay so that requested pieces are forwarded from a swarm to another swarm in a bucket brigade manner, where the forward of pieces is regulated by the super-peer (SP) of each swarm. The second contribution is the proposal of a match making scheme between requests and uploaders. The simulation result indicates that the proposed scheme reduces the total waiting time of a randomized scheme by 24% and the load of the media server by 76%.
In this paper, we consider cloud-assisted Peer-to-Peer (P2P) video streaming systems, in which a given video stream is divided into several sub-streams called stripes and those stripes are delivered to all subscribers through different spanning trees of height two, with the aid of cloud upload capacity. We call such a low latency delivery of stripes a 2-hop delivery. This paper proves that if the average upload capacity of the peers equals to the bit rate of the video stream and the video stream is divided into a stripes, then 2-hop delivery of all stripes to n peers is possible if the upload capacity assisted by the cloud is 3n/a. If those peers have a uniform upload capacity, then the amount of cloud assistance necessary for the 2-hop delivery reduces to n/a.
This paper proposes a method to absorb flash crowd in P2P video streaming systems. The idea of the proposed method is to reduce the time before a newly arrived node becoming an uploader by explicitly constructing a group of newly arrived nodes called flash crowd absorber (FCA). FCA grows continuously while serving a video stream to the members of the group, and it is explicitly controlled so that the upload capacity of the nodes is fully utilized and it attains a nearly optimal latency of the stream during a flash crowd. A numerical comparison with a naive tree-based scheme is also given.
In this paper, we propose a new buffer map notification scheme for Peer-to-Peer Video-on-Demand systems (P2P VoDs) which support VCR operations such as fast-forward, fast-backward, and seek. To enhance the fluidity of such VCR operations, we need to refine the size of each piece as small as possible. However, such a refinement significantly degrades the performance of buffer map notification schemes with respect to the overhead, piece availability and the efficiency of resource utilizations. The basic idea behind our proposed scheme is to use a piece-based buffer map with a segment-based buffer map in a complementary manner. The result of simulations indicates that the proposed scheme certainly increases the accuracy of the information on the piece availability in the neighborhood with a sufficiently low cost, which reduces the intermittent waiting time of each peer by more than 40% even under a situation in which 50% of peers conduct the fast-forward operation over a range of 30% of the entire video.
In this paper, we consider a problem of assigning n independent tasks onto m identical processors in such a way that the overall execution time of the tasks will be minimized. Unlike conventional task assignment problem, we assume that the execution time of each task is not fixed in advance, and merely upper and lower bounds of the execution time are given at the compile time. In the following, we first provide a theoretical analysis of several conventional scheduling policies in terms of the worst case slowdown compared with the outcome of an optimal off-line scheduling policy. It is shown that the best known algorithm in the literature achieves a worst case performance ratio of 1 + 1/f(n) where f(n) = O(n2/3) for any fixed m, which approaches to one by increasing n to the infinity. We then propose a new scheme that achieves better worst case ratio of 1 + 1/g(n) where g(n) = Θ (n/log n) for any fixed m, which approaches to one more quickly than previous schemes.
Takahiro ARIYOSHI Satoshi FUJITA
In this paper, we study the problem of efficient processing of conjunctive queries in Peer-to-Peer systems based on Distributed Hash Tables (P2P DHT, for short). The basic idea of our approach is to cache the search result for the queries submitted in the past, and to use them to improve the performance of succeeding query processing. More concretely, we propose to adopt Bloom filters as a concrete implementation of such a result cache rather than a list of items used in many conventional schemes. By taking such an approach, the cache size for each conjunctive query becomes as small as the size of each file index. The performance of the proposed scheme is evaluated by simulation. The result of simulation indicates that the proposed scheme is particularly effective when the size of available memory in each peer is bounded by a small value, and when the number of peers is 100, it reduces the amount of data transmissions of previous schemes by 75%.