The Experts below are selected from a list of 2409 Experts worldwide ranked by ideXlab platform
Toshihiko Kato - One of the best experts on this subject based on the ideXlab platform.
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an enhanced reinforcement routing protocol for inter vehicular Unicast Application
Internet Multimedia Systems and Applications, 2008Co-Authors: Toshihiko KatoAbstract:In Vehicular Ad-Hoc Network (VANET), as a result of frequent changes of network topology caused by vehicle's movement, the general purpose ad hoc routing protocols such as AODV and DSR cannot work efficiently. This paper proposed a VANET routing protocol QLAODV which fits for Unicast Application in high mobility scenario. QLAODV is a distributed reinforcement learning routing protocol, which uses Q-Learning algorithm to infer network state information and uses Unicast control packets checking the availability of paths in a real time manner in order to allow Q-Learning to work efficiently in highly dynamic network environment. In this paper, we show the performance analysis of QLAODV by simulation with NS2 in different mobility models, and give the simulation results confirming that QLAODV outperforms original AODV significantly in highly dynamic networks.
Haixiang Wang - One of the best experts on this subject based on the ideXlab platform.
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benefits of network coding for Unicast Application in disruption tolerant networks
IEEE ACM Transactions on Networking, 2013Co-Authors: Xiaolan Zhang, Giovanni Neglia, Jim Kurose, Don Towsley, Haixiang WangAbstract:In this paper, we investigate the benefits of applying a form of network coding known as random linear coding (RLC) to Unicast Applications in disruption-tolerant networks (DTNs). Under RLC, nodes store and forward random linear combinations of packets as they encounter each other. For the case of a single group of packets originating from the same source and destined for the same destination, we prove a lower bound on the probability that the RLC scheme achieves the minimum time to deliver the group of packets. Although RLC significantly reduces group delivery delays, it fares worse in terms of average packet delivery delay and network transmissions. When replication control is employed, RLC schemes reduce group delivery delays without increasing the number of transmissions. In general, the benefits achieved by RLC are more significant under stringent resource (bandwidth and buffer) constraints, limited signaling, highly dynamic networks, and when applied to packets in the same flow. For more practical settings with multiple continuous flows in the network, we show the importance of deploying RLC schemes with a carefully tuned replication control in order to achieve reduction in average delay, which is observed to be as large as 20% when buffer space is constrained.
Xiaolan Zhang - One of the best experts on this subject based on the ideXlab platform.
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benefits of network coding for Unicast Application in disruption tolerant networks
IEEE ACM Transactions on Networking, 2013Co-Authors: Xiaolan Zhang, Giovanni Neglia, Jim Kurose, Don Towsley, Haixiang WangAbstract:In this paper, we investigate the benefits of applying a form of network coding known as random linear coding (RLC) to Unicast Applications in disruption-tolerant networks (DTNs). Under RLC, nodes store and forward random linear combinations of packets as they encounter each other. For the case of a single group of packets originating from the same source and destined for the same destination, we prove a lower bound on the probability that the RLC scheme achieves the minimum time to deliver the group of packets. Although RLC significantly reduces group delivery delays, it fares worse in terms of average packet delivery delay and network transmissions. When replication control is employed, RLC schemes reduce group delivery delays without increasing the number of transmissions. In general, the benefits achieved by RLC are more significant under stringent resource (bandwidth and buffer) constraints, limited signaling, highly dynamic networks, and when applied to packets in the same flow. For more practical settings with multiple continuous flows in the network, we show the importance of deploying RLC schemes with a carefully tuned replication control in order to achieve reduction in average delay, which is observed to be as large as 20% when buffer space is constrained.
Giovanni Neglia - One of the best experts on this subject based on the ideXlab platform.
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benefits of network coding for Unicast Application in disruption tolerant networks
IEEE ACM Transactions on Networking, 2013Co-Authors: Xiaolan Zhang, Giovanni Neglia, Jim Kurose, Don Towsley, Haixiang WangAbstract:In this paper, we investigate the benefits of applying a form of network coding known as random linear coding (RLC) to Unicast Applications in disruption-tolerant networks (DTNs). Under RLC, nodes store and forward random linear combinations of packets as they encounter each other. For the case of a single group of packets originating from the same source and destined for the same destination, we prove a lower bound on the probability that the RLC scheme achieves the minimum time to deliver the group of packets. Although RLC significantly reduces group delivery delays, it fares worse in terms of average packet delivery delay and network transmissions. When replication control is employed, RLC schemes reduce group delivery delays without increasing the number of transmissions. In general, the benefits achieved by RLC are more significant under stringent resource (bandwidth and buffer) constraints, limited signaling, highly dynamic networks, and when applied to packets in the same flow. For more practical settings with multiple continuous flows in the network, we show the importance of deploying RLC schemes with a carefully tuned replication control in order to achieve reduction in average delay, which is observed to be as large as 20% when buffer space is constrained.
Jim Kurose - One of the best experts on this subject based on the ideXlab platform.
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benefits of network coding for Unicast Application in disruption tolerant networks
IEEE ACM Transactions on Networking, 2013Co-Authors: Xiaolan Zhang, Giovanni Neglia, Jim Kurose, Don Towsley, Haixiang WangAbstract:In this paper, we investigate the benefits of applying a form of network coding known as random linear coding (RLC) to Unicast Applications in disruption-tolerant networks (DTNs). Under RLC, nodes store and forward random linear combinations of packets as they encounter each other. For the case of a single group of packets originating from the same source and destined for the same destination, we prove a lower bound on the probability that the RLC scheme achieves the minimum time to deliver the group of packets. Although RLC significantly reduces group delivery delays, it fares worse in terms of average packet delivery delay and network transmissions. When replication control is employed, RLC schemes reduce group delivery delays without increasing the number of transmissions. In general, the benefits achieved by RLC are more significant under stringent resource (bandwidth and buffer) constraints, limited signaling, highly dynamic networks, and when applied to packets in the same flow. For more practical settings with multiple continuous flows in the network, we show the importance of deploying RLC schemes with a carefully tuned replication control in order to achieve reduction in average delay, which is observed to be as large as 20% when buffer space is constrained.
