No 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.

Abstract-As an efficient distribution mechanism, peer-topeer 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 1.2 more times the streaming rate. Furthermore, we showed that the distributed incentive algorithm motivates peers to contribute and collectively achieve a high level of QoE.

No abstract

MOTIVATIONThe evolving global information infrastructure consists of a widearea networking backbone that provides connectivity among service providers and clients requesting multimedia services via different applications. As this infrastructure scales, service providers replicate data and resources on the network to serve more concurrent clients.Adaptive and intelligent scheduling techniques are required to increase the utilization of their resources and handle an increasing number of requests. Scheduling for multimedia applications must guarantee desired Quality-of-Service (QoS) from both the network path and the server. Furthermore, with the increasing amount of mobile clients and highly dynamic network topologies, optimizing resource utilization becomes complicated. In a highly dynamic and ad-hoc environment where clients are mobile, load sensitive muting and scheduling techniques must be able to tolerate some information imprecision. The information collection and scheduling processes must cooperate with each other, they cannot be viewed as independent components in the QoS provisioning framework. This paper deals with a framework in which scheduling decisions are based on path as well as server qualities. Specifically, we address two problems in this paper.1. Scheduling a request from a client with QoS constraints on (a) the path quality and the (b) server quality. This is framed as an optimization problem on the overall network and server loads while scheduling the request.2. Information Collection to capture the current system state. We develop a model and algorithm for the parameter collection process that maximizes accuracy and minimizes traffic overhead.We present an algorithm to combine the two problems into one optimization problem within a unified framework. The framework has two components. The first component implements the optimized scheduling algorithm, while the second component collects the network and server parameters used in the algorithm.