A case for end system multicast (keynote address)
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Design and evaluation of a conit-based continuous consistency model for replicated services
ACM Transactions on Computer Systems (TOCS)
A framework for architecting peer-to-peer receiver-driven overlays
NOSSDAV '04 Proceedings of the 14th international workshop on Network and operating systems support for digital audio and video
Flexible Consistency for Wide Area Peer Replication
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Large-scale live media streaming over peer-to-peer networks through global internet
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
High-bandwidth routing in dynamic peer-to-peer streaming
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
Hi-index | 0.00 |
In decentralized but structured peer-to-peer (P2P) streaming system, when a node is overloading, the new incoming requests will be replicated to its neighboring nodes in the same session, and then the requesting nodes will receive the streams from these neighboring nodes. However, the replication of the requests might result in the service inconsistency due to no-zero replicated time. In general, there is a tradeoff between the system performance and the service consistency. In this paper, we focus on how to provide the service consistency for decentralized but structured P2P streaming system, under the precondition of no obvious degrading at the system performance. We propose a service update algorithm (SUA) which iteratively adjusts the actual read delay at these neighboring nodes, and thus converges to the desired misread probability. The analytic and simulated results show that the algorithm achieves a good tradeoff between the service consistency and the system performance.