The Experts below are selected from a list of 18714 Experts worldwide ranked by ideXlab platform
Tutomu Murase - One of the best experts on this subject based on the ideXlab platform.
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statistical estimation of tcp Packet Loss Rate from sampled ack Packets
Global Communications Conference, 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:The appearance of various quality-sensitive applications has greatly changed the requirements for network management. To manage the quality of these applications, monitoring of individual traffic flows, as well as aggregated traffic statistics, has become more important. Since per-flow monitoring involves a high processing cost, especially in emerging high-speed links, Packet sampling techniques have been attracting considerable attention. However, existing sampling techniques, such as NetFlow and sFlow, have mainly targeted traffic volume monitoring and there has been little discussion on the monitoring of quality indexes including Packet Loss Rate. In this paper, we propose a method to estimate the TCP Packet Loss Rate from sampled Packets. The proposed method detects Packet Loss events by monitoring duplicate ACK events induced by a TCP receiver indicating the Loss events. Since only a portion of Packet Loss events can be detected from the sampled Packets, the correct Packet Loss Rate is estimated by means of statistical approximation. Simulation results show that the proposed method accuRately estimates the TCP Packet Loss Rate from 10% of sampled Packets.
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Statistical Evaluation of TCP Packet Loss Rate Estimation
6th Asia-Pacific Symposium on Information and Telecommunication Technologies, 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:Packet sampling techniques have recently attracted much attention as a solution to the traffic measurement in high-speed networks, where large processing cost is incurred when monitoring the behaviors of a large number of sessions. We have proposed a method for estimating TCP Packet Loss Rate from sampled Packets and have evaluated the method through simulations and experiments. Results of those evaluations showed that the proposed method accuRately estimates the TCP Packet Loss Rate from a sampling of 10% of the TCP Packets. The estimation accuracy depends on the input parameters, such as sampling probability and iteration number of the algorithm, for the estimation function. In this paper we clarify the properties of each parameter by statistical evaluation and show that the proposed method is sufficiently accuRate in typical applications under practical conditions
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GLOBECOM - Statistical estimation of TCP Packet Loss Rate from sampled ACK Packets
GLOBECOM '05. IEEE Global Telecommunications Conference 2005., 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:The appearance of various quality-sensitive applications has greatly changed the requirements for network management. To manage the quality of these applications, monitoring of individual traffic flows, as well as aggregated traffic statistics, has become more important. Since per-flow monitoring involves a high processing cost, especially in emerging high-speed links, Packet sampling techniques have been attracting considerable attention. However, existing sampling techniques, such as NetFlow and sFlow, have mainly targeted traffic volume monitoring and there has been little discussion on the monitoring of quality indexes including Packet Loss Rate. In this paper, we propose a method to estimate the TCP Packet Loss Rate from sampled Packets. The proposed method detects Packet Loss events by monitoring duplicate ACK events induced by a TCP receiver indicating the Loss events. Since only a portion of Packet Loss events can be detected from the sampled Packets, the correct Packet Loss Rate is estimated by means of statistical approximation. Simulation results show that the proposed method accuRately estimates the TCP Packet Loss Rate from 10% of sampled Packets.
Hyongsuk Kim - One of the best experts on this subject based on the ideXlab platform.
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Packet Loss Rate Prediction Using the Sparse Basis Prediction Model
IEEE transactions on neural networks, 2007Co-Authors: Amir F. Atiya, Sung Goo Yoo, Kil To Chong, Hyongsuk KimAbstract:The quality of multimedia communicated through the Internet is highly sensitive to Packet Loss. In this letter, we develop a time-series prediction model for the end-to-end Packet Loss Rate (PLR). The estimate of the PLR is needed in several transmission control mechanisms such as the TCP-friendly congestion control mechanism for UDP traffic. In addition, it is needed to estimate the amount of redundancy for the forward error correction (FEC) mechanism. An accuRate prediction would therefore be very valuable. We used a relatively novel prediction model called sparse basis prediction model. It is an adaptive nonlinear prediction approach, whereby a very large dictionary of possible inputs are extracted from the time series (for example, through moving averages, some nonlinear transformations, etc.). Only few of the very best inputs among the dictionary are selected and are combined linearly. An algorithm adaptively updates the input selection (as well as updates the weights) each time a new time sample arrives in a computationally efficient way. Simulation experiments indicate significantly better prediction performance for the sparse basis approach, as compared to other traditional nonlinear approaches
Zhang Yuan-peng - One of the best experts on this subject based on the ideXlab platform.
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Algorithm of Multicast Network Topology Inference Based on Packet Loss Rate
Computer Engineering, 2010Co-Authors: Zhang Yuan-pengAbstract:By analyzing the existing network topology inference algorithms,this paper presents an improved multicast network topology inference algorithm based on Packet Loss Rate.It combines the hop count of receivers,the Hamming distance and the number of received probes and can infer multicast network topology and Loss performance simultaneously.It adapts dynamically the value of threshold according to the estimation of link Packet Loss Rates,it improves the accuracy of the inference.Simulation results show that compared with the existing algorithms,this algorithm has better performance.
Yasuhiro Yamasaki - One of the best experts on this subject based on the ideXlab platform.
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statistical estimation of tcp Packet Loss Rate from sampled ack Packets
Global Communications Conference, 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:The appearance of various quality-sensitive applications has greatly changed the requirements for network management. To manage the quality of these applications, monitoring of individual traffic flows, as well as aggregated traffic statistics, has become more important. Since per-flow monitoring involves a high processing cost, especially in emerging high-speed links, Packet sampling techniques have been attracting considerable attention. However, existing sampling techniques, such as NetFlow and sFlow, have mainly targeted traffic volume monitoring and there has been little discussion on the monitoring of quality indexes including Packet Loss Rate. In this paper, we propose a method to estimate the TCP Packet Loss Rate from sampled Packets. The proposed method detects Packet Loss events by monitoring duplicate ACK events induced by a TCP receiver indicating the Loss events. Since only a portion of Packet Loss events can be detected from the sampled Packets, the correct Packet Loss Rate is estimated by means of statistical approximation. Simulation results show that the proposed method accuRately estimates the TCP Packet Loss Rate from 10% of sampled Packets.
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Statistical Evaluation of TCP Packet Loss Rate Estimation
6th Asia-Pacific Symposium on Information and Telecommunication Technologies, 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:Packet sampling techniques have recently attracted much attention as a solution to the traffic measurement in high-speed networks, where large processing cost is incurred when monitoring the behaviors of a large number of sessions. We have proposed a method for estimating TCP Packet Loss Rate from sampled Packets and have evaluated the method through simulations and experiments. Results of those evaluations showed that the proposed method accuRately estimates the TCP Packet Loss Rate from a sampling of 10% of the TCP Packets. The estimation accuracy depends on the input parameters, such as sampling probability and iteration number of the algorithm, for the estimation function. In this paper we clarify the properties of each parameter by statistical evaluation and show that the proposed method is sufficiently accuRate in typical applications under practical conditions
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GLOBECOM - Statistical estimation of TCP Packet Loss Rate from sampled ACK Packets
GLOBECOM '05. IEEE Global Telecommunications Conference 2005., 2005Co-Authors: Yasuhiro Yamasaki, Hideyuki Shimonishi, Tutomu MuraseAbstract:The appearance of various quality-sensitive applications has greatly changed the requirements for network management. To manage the quality of these applications, monitoring of individual traffic flows, as well as aggregated traffic statistics, has become more important. Since per-flow monitoring involves a high processing cost, especially in emerging high-speed links, Packet sampling techniques have been attracting considerable attention. However, existing sampling techniques, such as NetFlow and sFlow, have mainly targeted traffic volume monitoring and there has been little discussion on the monitoring of quality indexes including Packet Loss Rate. In this paper, we propose a method to estimate the TCP Packet Loss Rate from sampled Packets. The proposed method detects Packet Loss events by monitoring duplicate ACK events induced by a TCP receiver indicating the Loss events. Since only a portion of Packet Loss events can be detected from the sampled Packets, the correct Packet Loss Rate is estimated by means of statistical approximation. Simulation results show that the proposed method accuRately estimates the TCP Packet Loss Rate from 10% of sampled Packets.
Harald Øverby - One of the best experts on this subject based on the ideXlab platform.
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AICT/ICIW - How the Packet length distribution influences the Packet Loss Rate in an optical Packet switch
Advanced Int'l Conference on Telecommunications and Int'l Conference on Internet and Web Applications and Services (AICT-ICIW'06), 2006Co-Authors: Harald ØverbyAbstract:Optical Packet Switching (OPS) has emerged as a promising candidate for the future all-optical core network. A crucial issue in such networks is how the Packet length distribution (PLD) influences the performance under different traffic scenarios. In this paper we investigate how a deterministic, empirical and exponential PLD influences the Packet Loss Rate (PLR) in an optical Packet switch in the case of a Poisson arrival process and a bursty Hyperexponential arrival process. We consider optical Packet switches with and without Fibre Delay Line (FDL) contention buffers. Our results show that in the case of OPS without FDL buffering and with a Hyperexponential arrival process, the empirical PLD yields the lowest PLR. However, in the case of OPS with FDL buffering, the deterministic PLD yields the lowest PLR.
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Packet Loss Rate differentiation in slotted optical Packet switched networks
IEEE Photonics Technology Letters, 2005Co-Authors: Harald ØverbyAbstract:This letter presents a Packet Loss Rate (PLR) differentiation scheme suitable for slotted optical Packet switched networks. An analytical model of the proposed scheme is presented and expressions for the PLRs are derived for a multiclass scenario. We also show that the use of the proposed scheme does not result in any reductions in the average switch throughput.
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Packet Loss Rate and jitter differentiating Quality-of-Service schemes for asynchronous optical Packet switches
Journal of Optical Networking, 2004Co-Authors: Martin Nord, Harald ØverbyAbstract:Feature Issue on Optical Interconnection Networks (OIN). We propose access-restriction-based quality-of-service differentiation schemes, suitable for an asynchronous optical Packet switch with a contention resolution pool that contains both tunable wavelength converters and fiber delay lines. The schemes aim at obtaining a high degree of Packet-Loss-Rate isolation, for a low increase in overall Packet Loss Rate, at the same time respecting the jitter tolerance of each class of service. Numerical simulations quantify how the performance depends significantly on the jitter tolerance of the traffic in general, and of the highest-priority class of service in particular.
