A comparison of mechanisms for improving TCP performance over wireless links
IEEE/ACM Transactions on Networking (TON)
MSWIM '01 Proceedings of the 4th ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Discriminating Congestion Losses from Wireless Losses using Inter-Arrival Times at the Receiver
ASSET '99 Proceedings of the 1999 IEEE Symposium on Application - Specific Systems and Software Engineering and Technology
Achieving moderate fairness for UDP flows by path-status classification
LCN '00 Proceedings of the 25th Annual IEEE Conference on Local Computer Networks
Striping Doesn't Scale: How to Achieve Scalability for Continuous Media Servers with Replication
ICDCS '00 Proceedings of the The 20th International Conference on Distributed Computing Systems ( ICDCS 2000)
I-TCP: indirect TCP for mobile hosts
ICDCS '95 Proceedings of the 15th International Conference on Distributed Computing Systems
End-to-end differentiation of congestion and wireless losses
IEEE/ACM Transactions on Networking (TON)
Performance evaluation of packet loss differentiation algorithms for wireless networks
Proceedings of the 2nd ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
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Since interests in multimedia services have been growing with the proliferation of wireless networks, there is a need to provide an efficient loss-differential scheme for the wired-cum-wireless networks. This is important because with the aid of the differential scheme, the congestion control protocol can tell the packet loss due to the error-prone wireless link or the network congestion. Then, the congestion control protocol will avoid reducing the sending rate blindly in the present of the packet loss. In this work, we propose an end-to-end loss-differential approach, called Trend-and-Loss-Density-based (TD) scheme. Since the congestion losses are highly co-related to each other, the TD scheme considers (a) the trend to indicate where the packet loss happens, and (b) the loss density to examine how often the packet loss occurs. Specifically, we use the autocorrelation function to measure the dense degree of a packet loss in a given sequence. Moreover, the threshold of each trend in the TD scheme is decided according to the characteristics of the wireless channel so it is easily adapted to different wireless network situations. We evaluate the TD scheme via extensive simulations in ns2. The results show that compared with other differential schemes, the TD scheme can substantially improve wireless and overall misclassification rates while maintaining a comparable throughput in all experiments.