The Experts below are selected from a list of 1197 Experts worldwide ranked by ideXlab platform
Amy R Reibman - One of the best experts on this subject based on the ideXlab platform.
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a versatile model for packet loss visibility and its application to packet prioritization
2010Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, David Poole, Amy R ReibmanAbstract:In this paper, we propose a generalized linear model for video packet loss visibility that is applicable to different group-of-picture structures. We develop the model using three subjective experiment data sets that span various encoding standards (H.264 and MPEG-2), group-of-picture structures, and decoder error concealment choices. We consider factors not only within a packet, but also in its vicinity, to account for possible temporal and spatial masking effects. We discover that the factors of scene cuts, camera motion, and reference distance are highly significant to the packet loss visibility. We apply our visibility model to packet prioritization for a video stream; when the network gets congested at an Intermediate Router, the Router is able to decide which packets to drop such that visual quality of the video is minimally impacted. To show the effectiveness of our visibility model and its corresponding packet prioritization method, experiments are done to compare our perceptual-quality-based packet prioritization approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based prioritization methods. The result shows that our prioritization method produces videos of higher perceptual quality for different network conditions and group-of-picture structures. Our model was developed using data from high encoding-rate videos, and designed for high-quality video transported over a mostly reliable network; however, the experiments show the model is applicable to different encoding rates.
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perceptual quality based packet dropping for generalized video gop structures
2009Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, Amy R ReibmanAbstract:Our work builds a general visibility model of video packets which is applicable to various types of GOP (Group of Pictures). The data used for analysis and building the model come from three subjective experiment sets with different encoding and decoding parameters on H.264 and MPEG-2 videos. We consider factors not only within a packet but also across its vicinity to account for possible temporal and spatial masking effects. This model can be useful for an Intermediate Router in a congested network to drop less visible packets to maintain overall video quality. Experiments are done to compare our perceptual-quality-based packet dropping approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based dropping methods. The result shows that our dropping method produces videos of higher perceptual quality for different network conditions and GOP structures.
Tinglan Lin - One of the best experts on this subject based on the ideXlab platform.
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a versatile model for packet loss visibility and its application to packet prioritization
2010Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, David Poole, Amy R ReibmanAbstract:In this paper, we propose a generalized linear model for video packet loss visibility that is applicable to different group-of-picture structures. We develop the model using three subjective experiment data sets that span various encoding standards (H.264 and MPEG-2), group-of-picture structures, and decoder error concealment choices. We consider factors not only within a packet, but also in its vicinity, to account for possible temporal and spatial masking effects. We discover that the factors of scene cuts, camera motion, and reference distance are highly significant to the packet loss visibility. We apply our visibility model to packet prioritization for a video stream; when the network gets congested at an Intermediate Router, the Router is able to decide which packets to drop such that visual quality of the video is minimally impacted. To show the effectiveness of our visibility model and its corresponding packet prioritization method, experiments are done to compare our perceptual-quality-based packet prioritization approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based prioritization methods. The result shows that our prioritization method produces videos of higher perceptual quality for different network conditions and group-of-picture structures. Our model was developed using data from high encoding-rate videos, and designed for high-quality video transported over a mostly reliable network; however, the experiments show the model is applicable to different encoding rates.
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perceptual quality based packet dropping for generalized video gop structures
2009Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, Amy R ReibmanAbstract:Our work builds a general visibility model of video packets which is applicable to various types of GOP (Group of Pictures). The data used for analysis and building the model come from three subjective experiment sets with different encoding and decoding parameters on H.264 and MPEG-2 videos. We consider factors not only within a packet but also across its vicinity to account for possible temporal and spatial masking effects. This model can be useful for an Intermediate Router in a congested network to drop less visible packets to maintain overall video quality. Experiments are done to compare our perceptual-quality-based packet dropping approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based dropping methods. The result shows that our dropping method produces videos of higher perceptual quality for different network conditions and GOP structures.
Faisal Bashir Hussain - One of the best experts on this subject based on the ideXlab platform.
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Out-of-band Wormhole Attack Detection in MANETs
2011Co-Authors: Faisal Bashir HussainAbstract:Mobile Ad hoc Networks (MANETs) are prone to a variety of attacks due to their unique characteristics such as dynamic topology, open wireless medium, absence of infrastructure, multi hop nature and resource constraints. Any node in mobile ad hoc networks operates not only as end terminal but both as an Intermediate Router and client. In this way, multi-hop communication occurs in MANETs and thus it is a difficult task to establish a secure path between source and destination. The purpose of this work is overcome a special attack called wormhole attack launched by at least two colluding nodes within the network. In this paper we enhance AODV to detect and remove wormhole attack in real-world mobile ad hoc networks. In an out-of-band wormhole attack the communication between two malicious nodes is hidden from the rest of the nodes. This property is exploited by our proposed AODV-DRW protocol for the detection of wormhole attack.
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http://ro.ecu.edu.au/ism/114 OUT-OF-BAND WORMHOLE ATTACK DETECTION IN MANETS
2011Co-Authors: Faisal Bashir Hussain, Sana Ul HaqAbstract:Mobile Ad hoc Networks (MANETs) are prone to a variety of attacks due to their unique characteristics such as dynamic topology, open wireless medium, absence of infrastructure, multi hop nature and resource constraints. Any node in mobile ad hoc networks operates not only as end terminal but both as an Intermediate Router and client. In this way, multi-hop communication occurs in MANETs and thus it is a difficult task to establish a secure path between source and destination. The purpose of this work is overcome a special attack called wormhole attack launched by at least two colluding nodes within the network. In this paper we enhance AODV to detect and remove wormhole attack in real-world mobile ad hoc networks. In an out-of-band wormhole attack the communication between two malicious nodes is hidden from the rest of the nodes. This property is exploited by our proposed AODV-DRW protocol for the detection of wormhole attack
George Varghese - One of the best experts on this subject based on the ideXlab platform.
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Reconsidering fragmentation and reassembly
1998Co-Authors: Girish P. Chandranmenon, George VargheseAbstract:We reconsider several issues related to fragmentation and reassembly in IP. We rst reconsider reassembly. Wedescribe a simple expected case optimization that improves reassembly performance to 38 instructions per fragment if the fragments arrive inFIFOorder (the same assumption made in header prediction) which has been implemented in the NetBSD kernel. Next, we introduce the new idea of Graceful Intermediate Reassembly (GIR), whichisageneralization of the existing IP mechanisms of destination and hop-by-hop reassembly. In GIR, we coalesce the fragments at an Intermediate Router in order to use the largest sized packets on its outgoing interface. We showthat GIR always outperforms hop-by-hop reassembly and can be implemented economically in Routers with small processing and memory costs. We then reconsider fragmentation. Weshowthatavoiding fragmentation has costs of its own in terms of increased packet processing and/or round-trip delays. We describe measurements in which TCP performance improves after turning on fragmentation. For example, on Ethernet under NetBSD using a 536 byte segment size for TCP we get a throughput of only about 5.5Mb/s, whereas we get a throughputaof 8.45Mb/s using a segment size of 146
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Reconsidering Fragmentation and Reassembly
1996Co-Authors: Girish P. Chandranmenon, George VargheseAbstract:We reconsider several issues related to fragmentation and reassembly in IP. We first reconsider reassembly. We describe a simple expected case optimization that improves reassembly performance to 38 instructions per fragment if the fragments arrive in FIFO order (the same assumption made in header prediction) which has been implemented in the NetBSD kernel. Next, we introduce the new idea of Graceful Intermediate Reassembly (GIR), which is a generalization of the existing IP mechanisms of destination and hop-by-hop reassembly. In GIR, we coalesce the fragments at an Intermediate Router in order to use the largest sized packets on its outgoing interface. We show that GIR always outperforms hop-by-hop reassembly and can be implemented economically in Routers with small processing and memory costs. We then reconsider fragmentation. We show that avoiding fragmentation has costs of its own in terms of increased packet processing and/or round-trip delays. We describe measurements in which TC..
Sandeep Kanumuri - One of the best experts on this subject based on the ideXlab platform.
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a versatile model for packet loss visibility and its application to packet prioritization
2010Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, David Poole, Amy R ReibmanAbstract:In this paper, we propose a generalized linear model for video packet loss visibility that is applicable to different group-of-picture structures. We develop the model using three subjective experiment data sets that span various encoding standards (H.264 and MPEG-2), group-of-picture structures, and decoder error concealment choices. We consider factors not only within a packet, but also in its vicinity, to account for possible temporal and spatial masking effects. We discover that the factors of scene cuts, camera motion, and reference distance are highly significant to the packet loss visibility. We apply our visibility model to packet prioritization for a video stream; when the network gets congested at an Intermediate Router, the Router is able to decide which packets to drop such that visual quality of the video is minimally impacted. To show the effectiveness of our visibility model and its corresponding packet prioritization method, experiments are done to compare our perceptual-quality-based packet prioritization approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based prioritization methods. The result shows that our prioritization method produces videos of higher perceptual quality for different network conditions and group-of-picture structures. Our model was developed using data from high encoding-rate videos, and designed for high-quality video transported over a mostly reliable network; however, the experiments show the model is applicable to different encoding rates.
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perceptual quality based packet dropping for generalized video gop structures
2009Co-Authors: Tinglan Lin, Yuan Zhi, Sandeep Kanumuri, Pamela C Cosman, Amy R ReibmanAbstract:Our work builds a general visibility model of video packets which is applicable to various types of GOP (Group of Pictures). The data used for analysis and building the model come from three subjective experiment sets with different encoding and decoding parameters on H.264 and MPEG-2 videos. We consider factors not only within a packet but also across its vicinity to account for possible temporal and spatial masking effects. This model can be useful for an Intermediate Router in a congested network to drop less visible packets to maintain overall video quality. Experiments are done to compare our perceptual-quality-based packet dropping approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based dropping methods. The result shows that our dropping method produces videos of higher perceptual quality for different network conditions and GOP structures.