Resource allocation problems: algorithmic approaches
Resource allocation problems: algorithmic approaches
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Layer Management in Superpeer Architectures
IEEE Transactions on Parallel and Distributed Systems
Understanding churn in peer-to-peer networks
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
On lifetime-based node failure and stochastic resilience of decentralized peer-to-peer networks
IEEE/ACM Transactions on Networking (TON)
A scalable super-peer approach for public scientific computation
Future Generation Computer Systems
IEEE Transactions on Parallel and Distributed Systems
Optimizing the throughput of data-driven based streaming in heterogeneous overlay network
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
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To model a layered video streaming system in super-peer overlay networks that faces with heterogeneity and volatility of peers, we formulate a layer scheduling problem from understanding some constraints such as layer dependency, transmission rule, and bandwidth heterogeneity. To solve this problem, we propose a new layer scheduling algorithm using a real-coded messy genetic algorithm, providing a feasible solution with low complexity in decision. We also propose a peer-utility-based promotion algorithm that selects the most qualified neighbor to guarantee the sustained quality of streaming despite high intensity of churn. Simulation results show that the proposed layer scheduling scheme can achieve the most near-optimal solutions compared to the four conventional scheduling heuristics in the average streaming ratio. It also highly outperforms those with different peer selection strategies in terms of the average bandwidth (6.9 % higher at least) and the variation of utilization (11.3 % lower at least).