This paper introduces a video application-aware cross-layer framework for joint performance-energy optimization,considering the scenario of multiple users upstreaming real-time Motion JPEG2000 video streams to the acc...This paper introduces a video application-aware cross-layer framework for joint performance-energy optimization,considering the scenario of multiple users upstreaming real-time Motion JPEG2000 video streams to the access point of a WiFi wireless local area network and extends the PHY-MAC run-time cross-layer scheduling strategy that we introduced in (Mangharam et al., 2005; Pollin et al., 2005) to also consider congested network situations where video packets have to be dropped. We show that an optimal solution at PHY-MAC level can be highly suboptimal at application level, and then show that making the cross-layer framework application-aware through a prioritized dropping policy capitalizing on the inherent scalability of Motion JPEG2000 video streams leads to drastic average video quality improvements and inter-user quality variation reductions of as much as 10 dB PSNR, without affecting the overall energy consumption requirements.展开更多
As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster dedupli...As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster deduplication system:the decreasing data deduplication rate with the increasing deduplication server nodes,high communication overhead for data routing,and load balance to improve the throughput of the system.In this paper,we propose a well-performed cluster deduplication system called AR-Dedupe.The experimental results of two real datasets demonstrate that AR-Dedupe can achieve a high data deduplication rate with a low communication overhead and keep the system load balancing well at the same time through a new data routing algorithm.In addition,we utilize application-aware mechanism to speed up the index of handprints in the routing server which has a 30%performance improvement.展开更多
文摘This paper introduces a video application-aware cross-layer framework for joint performance-energy optimization,considering the scenario of multiple users upstreaming real-time Motion JPEG2000 video streams to the access point of a WiFi wireless local area network and extends the PHY-MAC run-time cross-layer scheduling strategy that we introduced in (Mangharam et al., 2005; Pollin et al., 2005) to also consider congested network situations where video packets have to be dropped. We show that an optimal solution at PHY-MAC level can be highly suboptimal at application level, and then show that making the cross-layer framework application-aware through a prioritized dropping policy capitalizing on the inherent scalability of Motion JPEG2000 video streams leads to drastic average video quality improvements and inter-user quality variation reductions of as much as 10 dB PSNR, without affecting the overall energy consumption requirements.
基金the National High Technology Research and Development Program(863)of China(No.2013AA013201)the National Natural Science Foundation of China(Nos.61025009,61232003,61170288 and 61332003)
文摘As data are growing rapidly in data centers,inline cluster deduplication technique has been widely used to improve storage efficiency and data reliability.However,there are some challenges faced by the cluster deduplication system:the decreasing data deduplication rate with the increasing deduplication server nodes,high communication overhead for data routing,and load balance to improve the throughput of the system.In this paper,we propose a well-performed cluster deduplication system called AR-Dedupe.The experimental results of two real datasets demonstrate that AR-Dedupe can achieve a high data deduplication rate with a low communication overhead and keep the system load balancing well at the same time through a new data routing algorithm.In addition,we utilize application-aware mechanism to speed up the index of handprints in the routing server which has a 30%performance improvement.
