On the Shapley-like Payoff Mechanisms in Peer-Assisted Services with Multiple Content Providers

This paper studies an incentive structure for cooperation and its stability in peer-assisted services when there exist multiple content providers, using a coalition game theoretic approach. We first consider a generalized coalition structure consisting of multiple providers with many assisting peers, where peers assist providers to reduce the operational cost in content distribution. To distribute the profit from cost reduction to players (i.e., providers and peers), we then establish a generalized formula for individual payoffs when a "Shapley-like" payoff mechanism is adopted. We show that the grand coalition is unstable, even when the operational cost functions are concave, which is in sharp contrast to the recently studied case of a single provider where the grand coalition is stable. We also show that irrespective of stability of the grand coalition, there always exist coalition structures which are not convergent to the grand coalition. Our results give us an important insight that a provider does not tend to cooperate with other providers in peer-assisted services, and be separated from them. To further study the case of the separated providers, three examples are presented; (i) underpaid peers, (ii) service monopoly, and (iii) oscillatory coalition structure. Our study opens many new questions such as realistic and efficient incentive structures and the tradeoffs between fairness and individual providers' competition in peer-assisted services.Comment: 13 pages, 4 figures, an extended version of the paper to be presented in ICST GameNets 2011, Shanghai, China, April 201

Business model with discount incentive in a P2P-cloud multimedia streaming system

Today P2P faces two important challenges: design of mechanisms to encourage users' collaboration in multimedia live streaming services; design of reliable algorithms with QoS provision, to encourage the multimedia providers employ the P2P topology in commercial live streaming systems. We believe that these two challenges are tightly-related and there is much to be done with respect. This paper analyzes the effect of user behavior in a multi-tree P2P overlay and describes a business model based on monetary discount as incentive in a P2P-Cloud multimedia streaming system. We believe a discount model can boost up users' cooperation and loyalty and enhance the overall system integrity and performance. Moreover the model bounds the constraints for a provider's revenue and cost if the P2P system is leveraged on a cloud infrastructure. Our case study shows that a streaming system provider can establish or adapt his business model by applying the described bounds to achieve a good discount-revenue trade-off and promote the system to the users

Network Awareness of P2P Live Streaming Applications: A Measurement Study

Abstract: Early P2P-TV systems have already attracted millions of users, and many new commercial solutions are entering this market. Little information is however available about how these systems work, due to their closed and proprietary design. In this paper, we present large scale experiments to compare three of the most successful P2P-TV systems, namely PPLive, SopCast and TVAnts. Our goal is to assess what level of "network awareness" has been embedded in the applications. We first define a general framework to quantify which network layer parameters leverage application choices, i.e., what parameters mainly drive the peer selection and data exchange. We then apply the methodology to a large dataset, collected during a number of experiments where we deployed about 40 peers in several European countries. From analysis of the dataset, we observe that TVAnts and PPLive exhibit a mild preference to exchange data among peers in the same autonomous system the peer belongs to, while this clustering effect is less intense in SopCast. However, no preference versus country, subnet or hop count is shown. Therefore, we believe that next-generation P2P live streaming applications definitively need to improve the level of network-awareness, so to better localize the traffic in the network and thus increase their network-friendliness as well

Design of Scalable On-Demand Video Streaming Systems Leveraging Video Viewing Patterns

The explosive growth in on-demand access of video across all forms of delivery (Internet, traditional cable, IPTV, wireless) has renewed the interest in scalable delivery methods. Approaches using Content Delivery Networks (CDNs), Peer-to-Peer (P2P) approaches, and their combinations have been proposed as viable options to ease the load on servers and network links. However, there has been little focus on how to take advantage of user viewing patterns to understand their impact on existing mechanisms and to design new solutions that improve the streaming service quality. In this dissertation, we leverage on the observation that users watch only a small portion of videos to understand the limits of existing designs and to optimize two scalable approaches -- the content placement and P2P Video-on-Demand (VoD) streaming. Then, we present our novel scalable system called Joint-Family which enables adaptive bitrate streaming (ABR) in P2P VoD, supporting user viewing patterns. We first provide evidence of such user viewing behavior from data collected from a nationally deployed VoD service. In contrast to using a simplistic popularity-based placement and traditionally proposed caching strategies (such as CDNs), we use a Mixed Integer Programming formulation to model the placement problem and employ an innovative approach that scales well. We have performed detailed simulations using actual traces of user viewing sessions (including stream control operations such as pause, fast-forward, and rewind). Our results show that the use of segment-based placement strategy yields substantial savings in both disk storage requirements at origin servers/VHOs as well as network bandwidth use. For example, compared to a simple caching scheme using full videos, our MIP-based placement using segments can achieve up to 71% reduction in peak link bandwidth usage. Secondly, we note that the policies adopted in existing P2P VoD systems have not taken user viewing behavior -- that users abandon videos -- into account. We show that abandonment can result in increased interruptions and wasted resources. As a result, we reconsider the set of policies to use in the presence of abandonment. Our goal is to balance the conflicting needs of delivering videos without interruptions while minimizing wastage. We find that an Earliest-First chunk selection policy in conjunction with the Earliest-Deadline peer selection policy allows us to achieve high download rates. We take advantage of abandonment by converting peers to "partial seeds"; this increases capacity. We minimize wastage by using a playback lookahead window. We use analysis and simulation experiments using real-world traces to show the effectiveness of our approach. Finally, we propose Joint-Family, a protocol that combines P2P and adaptive bitrate (ABR) streaming for VoD. While P2P for VoD and ABR have been proposed previously, they have not been studied together because they attempt to tackle problems with seemingly orthogonal goals. We motivate our approach through analysis that overcomes a misconception resulting from prior analytical work, and show that the popularity of a P2P swarm and seed staying time has a significant bearing on the achievable per-receiver download rate. Specifically, our analysis shows that popularity affects swarm efficiency when seeds stay "long enough". We also show that ABR in a P2P setting helps viewers achieve higher playback rates and/or fewer interruptions. We develop the Joint-Family protocol based on the observations from our analysis. Peers in Joint-Family simultaneously participate in multiple swarms to exchange chunks of different bitrates. We adopt chunk, bitrate, and peer selection policies that minimize occurrence of interruptions while delivering high quality video and improving the efficiency of the system. Using traces from a large-scale commercial VoD service, we compare Joint-Family with existing approaches for P2P VoD and show that viewers in Joint-Family enjoy higher playback rates with minimal interruption, irrespective of video popularity

Discovering multiple resource holders in query-incentive networks

Session - Content Distribution and Peer-to-Peer NetworksIn this paper, we study the problem of discovering multiple resource holders and how to evaluate a node's satisfaction in query incentive networks. Utilizing an acyclic tree, we show that query propagation has a nature of exponential start, polynomial growth, and eventually becoming a constant. We model the query propagation as an extensive game, obtain nodes' greedy behaviors from Nash equilibrium analysis, and show the impairment of greedy behaviors via a repeated Prisoner's Dilemma. We demonstrate that cooperation enforcement is required to achieve the optimal state of resource discovery. © 2011 IEEE.published_or_final_versionThe 8th IEEE Consumer Communications and Networking Conference (CCNC 2011), Las Vegas, NV., 9-12 January 2011. In Proceedings of the 8th CCNC, 2011, p. 1000-100