Incentivized Peer-Assisted Streaming for On-Demand Services

Abstract

Abstract-As an efficient distribution mechanism, Peer-to-Peer (P2P) technology has become a tremendously attractive solution to offload servers in large-scale video streaming applications. However, in providing on-demand asynchronous streaming services, P2P streaming design faces two major challenges: how to schedule efficient video sharing between peers with asynchronous playback progresses? how to provide incentives for peers to contribute their resources to achieve a high level of system-wide Quality-of-Experience (QoE)? In this paper, we present iPASS, a novel mesh-based P2P VoD system, to address these challenges. Specifically, iPASS adopts a dynamic buffering-progress-based peering strategy to achieve high peer bandwidth utilization with low system maintenance cost. To provide incentives for peer uploading, iPASS employs a differentiated pre-fetching design that enables peers with higher contribution pre-fetch content at higher speed. A distributed adaptive taxation algorithm is developed to balance the system-wide QoE and service differentiations among heterogeneous peers. To assess the performance of iPASS, we built a detailed packet-level P2P VoD simulator and conducted extensive simulations. It was demonstrated that iPASS can completely offload server when the average peer upload bandwidth is more than 1.2 times the streaming rate. Furthermore, we showed that the distributed incentive algorithm motivates peers to contribute and collaboratively achieve a high level of system wide QoE.

P2P-VoD Streaming:

“…Many researches [11,12,[16][17][18][19] discussed some mechanisms through which the scalability problem caused due to pure P2P architecture can be addressed. [11,12] have proposed caching mechanisms that adjust the buffer space in order to improve scalability. In addition to these mechanisms, many have worked on stream reuse techniques such as "batching" [13], "chaining" [14], and "patching" [15].…”

vINCENT: An incentive scheme supporting heterogeneity in Peer-to-Peer content distribution

“…However, the scheme has some flaws regarding the design and security, which are addressed by the authors of [9] with a distributed scheme. In [12], a taxation model for a video on demand streaming scenario is proposed, where taxes are set depending on the playback position of the peers. However, taxation schemes have the general drawback of relying on knowledge about nodes' uplink capacities.…”

A Self-organized Mechanism of Resource Allocation in P2P Systems

“…This benefit is represented by a matrix B, where b ii ≡ 0, and b i j denotes how much the cooperation of j is worth to i; it can be measured as the relative buffering progress of peer j (e.g. in 9 ), its service level (e.g. in 4,7 ), or its quality of service (e.g.…”

“…Hard schemes, which are monetary-based, includes various methods of token-exchange and micropayment, while in soft schemes, fairness of cooperation is the main concern and it is promoted by prioritizing peers according to their cooperation level. Under either of these incentive schemes, many different mechanisms of resource allocation 4,7,8 and policies of server selection 9,10,11 have been proposed, to respectively lead the decisions of rational peers as the provider and the consumer of resources. While they successfully provide incentives by differentiating the peers according to their contributions, the adjustment of their sharing ratio (the ratio between their upload and download resources) in accordance with the inherent dynamics of peer-to-peer systems is not explicitly considered.…”