The Experts below are selected from a list of 51867 Experts worldwide ranked by ideXlab platform
Curt Schurgers - One of the best experts on this subject based on the ideXlab platform.
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converss a hybrid mac Routing Solution for small scale convergecast wireless networks
IEEE Transactions on Mobile Computing, 2011Co-Authors: Clement Kam, Curt SchurgersAbstract:In applications involving networks of sensor-equipped autonomous vehicles, it is crucial to have an energy-efficient communication protocol due to the limited on-board batteries. Unlike traditional sensor networks, vehicle sensor networks typically consist of only a small number of nodes. We exploit this fact in our protocol design by optimizing specifically for these mobile small-scale networks. Our proposed Solution, ConverSS, is a hybrid MAC/Routing protocol that is energy-efficient for vehicle sensor networks. We have evaluated the protocol through simulation in ns-2 and verified its operation in a testbed network deployment. The results show that ConverSS is robust to real-world link impairments and that it outperforms common layered Solutions by as much as a factor of 10.
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ConverSS: A Hybrid MAC/Routing Solution for Small-Scale, Convergecast Wireless Networks
IEEE Transactions on Mobile Computing, 2011Co-Authors: Clement Kam, Curt SchurgersAbstract:In applications involving networks of sensor-equipped autonomous vehicles, it is crucial to have an energy-efficient communication protocol due to the limited on-board batteries. Unlike traditional sensor networks, vehicle sensor networks typically consist of only a small number of nodes. We exploit this fact in our protocol design by optimizing specifically for these mobile small-scale networks. Our proposed Solution, ConverSS, is a hybrid MAC/Routing protocol that is energy-efficient for vehicle sensor networks. We have evaluated the protocol through simulation in ns-2 and verified its operation in a testbed network deployment. The results show that ConverSS is robust to real-world link impairments and that it outperforms common layered Solutions by as much as a factor of 10.
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converss a hybrid mac Routing Solution for small scale convergecast wireless networks
International Conference on Signal Processing and Communication Systems, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:In many applications of sensor-equipped mobile vehicle networks, an energy-efficient communication Solution is required due to the limited battery on the vehicle. There are certain characteristics of vehicle-based networks that set them apart from typical sensor networks, namely that they are mobile and consist of only a few nodes. We adopt a design philosophy that optimizes the networking approach for these types of systems. We introduce ConverSS, a combined MAC/Routing Solution that provides reliable, efficient data delivery. Through simulation, we show that for these small-scale networks, the energy consumption of ConverSS performs almost as well as an omniscient Routing protocol, and it is superior to a traditional layered protocol. We also show that it is tolerant to non-ideal link behavior, such as packet errors and asymmetric links.
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ConverSS: A hybrid MAC/Routing Solution for small-scale, convergecast wireless networks
2009 3rd International Conference on Signal Processing and Communication Systems, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:In many applications of sensor-equipped mobile vehicle networks, an energy-efficient communication Solution is required due to the limited battery on the vehicle. There are certain characteristics of vehicle-based networks that set them apart from typical sensor networks, namely that they are mobile and consist of only a few nodes. We adopt a design philosophy that optimizes the networking approach for these types of systems. We introduce ConverSS, a combined MAC/Routing Solution that provides reliable, efficient data delivery. Through simulation, we show that for these small-scale networks, the energy consumption of ConverSS performs almost as well as an omniscient Routing protocol, and it is superior to a traditional layered protocol. We also show that it is tolerant to non-ideal link behavior, such as packet errors and asymmetric links.
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MobiQuitous - TreeDMA: a hybrid MAC/Routing Solution for small-scale wireless networks
Proceedings of the 6th Annual International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:Vehicle-based networks need energy-efficient communication to extend the battery lifetime, which subsequently extends the mission time of the node. We observe that these kinds of networks operate under different assumptions than traditional static sensor networks. The main difference is that these are small-scale networks. This motivates the need for a protocol that is optimized for such scenarios. To handle the communication, we introduce a combined MAC and Routing protocol, TreeDMA, that uses a contention-free MAC in conjunction with beaconing and overhearing. We show through simulation that for these kinds of networks, the energy consumption and latency is comparable to an “ideal” omniscient protocol and superior to traditional layered protocols.
Clement Kam - One of the best experts on this subject based on the ideXlab platform.
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converss a hybrid mac Routing Solution for small scale convergecast wireless networks
IEEE Transactions on Mobile Computing, 2011Co-Authors: Clement Kam, Curt SchurgersAbstract:In applications involving networks of sensor-equipped autonomous vehicles, it is crucial to have an energy-efficient communication protocol due to the limited on-board batteries. Unlike traditional sensor networks, vehicle sensor networks typically consist of only a small number of nodes. We exploit this fact in our protocol design by optimizing specifically for these mobile small-scale networks. Our proposed Solution, ConverSS, is a hybrid MAC/Routing protocol that is energy-efficient for vehicle sensor networks. We have evaluated the protocol through simulation in ns-2 and verified its operation in a testbed network deployment. The results show that ConverSS is robust to real-world link impairments and that it outperforms common layered Solutions by as much as a factor of 10.
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ConverSS: A Hybrid MAC/Routing Solution for Small-Scale, Convergecast Wireless Networks
IEEE Transactions on Mobile Computing, 2011Co-Authors: Clement Kam, Curt SchurgersAbstract:In applications involving networks of sensor-equipped autonomous vehicles, it is crucial to have an energy-efficient communication protocol due to the limited on-board batteries. Unlike traditional sensor networks, vehicle sensor networks typically consist of only a small number of nodes. We exploit this fact in our protocol design by optimizing specifically for these mobile small-scale networks. Our proposed Solution, ConverSS, is a hybrid MAC/Routing protocol that is energy-efficient for vehicle sensor networks. We have evaluated the protocol through simulation in ns-2 and verified its operation in a testbed network deployment. The results show that ConverSS is robust to real-world link impairments and that it outperforms common layered Solutions by as much as a factor of 10.
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converss a hybrid mac Routing Solution for small scale convergecast wireless networks
International Conference on Signal Processing and Communication Systems, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:In many applications of sensor-equipped mobile vehicle networks, an energy-efficient communication Solution is required due to the limited battery on the vehicle. There are certain characteristics of vehicle-based networks that set them apart from typical sensor networks, namely that they are mobile and consist of only a few nodes. We adopt a design philosophy that optimizes the networking approach for these types of systems. We introduce ConverSS, a combined MAC/Routing Solution that provides reliable, efficient data delivery. Through simulation, we show that for these small-scale networks, the energy consumption of ConverSS performs almost as well as an omniscient Routing protocol, and it is superior to a traditional layered protocol. We also show that it is tolerant to non-ideal link behavior, such as packet errors and asymmetric links.
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ConverSS: A hybrid MAC/Routing Solution for small-scale, convergecast wireless networks
2009 3rd International Conference on Signal Processing and Communication Systems, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:In many applications of sensor-equipped mobile vehicle networks, an energy-efficient communication Solution is required due to the limited battery on the vehicle. There are certain characteristics of vehicle-based networks that set them apart from typical sensor networks, namely that they are mobile and consist of only a few nodes. We adopt a design philosophy that optimizes the networking approach for these types of systems. We introduce ConverSS, a combined MAC/Routing Solution that provides reliable, efficient data delivery. Through simulation, we show that for these small-scale networks, the energy consumption of ConverSS performs almost as well as an omniscient Routing protocol, and it is superior to a traditional layered protocol. We also show that it is tolerant to non-ideal link behavior, such as packet errors and asymmetric links.
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MobiQuitous - TreeDMA: a hybrid MAC/Routing Solution for small-scale wireless networks
Proceedings of the 6th Annual International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services, 2009Co-Authors: Clement Kam, Curt SchurgersAbstract:Vehicle-based networks need energy-efficient communication to extend the battery lifetime, which subsequently extends the mission time of the node. We observe that these kinds of networks operate under different assumptions than traditional static sensor networks. The main difference is that these are small-scale networks. This motivates the need for a protocol that is optimized for such scenarios. To handle the communication, we introduce a combined MAC and Routing protocol, TreeDMA, that uses a contention-free MAC in conjunction with beaconing and overhearing. We show through simulation that for these kinds of networks, the energy consumption and latency is comparable to an “ideal” omniscient protocol and superior to traditional layered protocols.
Christian S Jensen - One of the best experts on this subject based on the ideXlab platform.
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learning to route with sparse trajectory sets
International Conference on Data Engineering, 2018Co-Authors: Bin Yang, Jilin Hu, Christian S JensenAbstract:Motivated by the increasing availability of vehicle trajectory data, we propose learn-to-route, a comprehensive trajectory-based Routing Solution. Specifically, we first construct a graph-like structure from trajectories as the Routing infrastructure. Second, we enable trajectory-based Routing given an arbitrary (source, destination) pair. In the first step, given a road network and a collection of trajectories, we propose a trajectory-based clustering method that identifies regions in a road network. If a pair of regions are connected by trajectories, we maintain the paths used by these trajectories and learn a Routing preference for travel between the regions. As trajectories are skewed and sparse, %and although the introduction of regions serves to consolidate the sparse data, many region pairs are not connected by trajectories. We thus transfer Routing preferences from region pairs with sufficient trajectories to such region pairs and then use the transferred preferences to identify paths between the regions. In the second step, we exploit the above graph-like structure to achieve a comprehensive trajectory-based Routing Solution. Empirical studies with two substantial trajectory data sets offer insight into the proposed Solution, indicating that it is practical. A comparison with a leading Routing service offers evidence that the paper's proposal is able to enhance Routing quality.
Bin Yang - One of the best experts on this subject based on the ideXlab platform.
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learning to route with sparse trajectory sets
International Conference on Data Engineering, 2018Co-Authors: Bin Yang, Jilin Hu, Christian S JensenAbstract:Motivated by the increasing availability of vehicle trajectory data, we propose learn-to-route, a comprehensive trajectory-based Routing Solution. Specifically, we first construct a graph-like structure from trajectories as the Routing infrastructure. Second, we enable trajectory-based Routing given an arbitrary (source, destination) pair. In the first step, given a road network and a collection of trajectories, we propose a trajectory-based clustering method that identifies regions in a road network. If a pair of regions are connected by trajectories, we maintain the paths used by these trajectories and learn a Routing preference for travel between the regions. As trajectories are skewed and sparse, %and although the introduction of regions serves to consolidate the sparse data, many region pairs are not connected by trajectories. We thus transfer Routing preferences from region pairs with sufficient trajectories to such region pairs and then use the transferred preferences to identify paths between the regions. In the second step, we exploit the above graph-like structure to achieve a comprehensive trajectory-based Routing Solution. Empirical studies with two substantial trajectory data sets offer insight into the proposed Solution, indicating that it is practical. A comparison with a leading Routing service offers evidence that the paper's proposal is able to enhance Routing quality.
Jilin Hu - One of the best experts on this subject based on the ideXlab platform.
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learning to route with sparse trajectory sets
International Conference on Data Engineering, 2018Co-Authors: Bin Yang, Jilin Hu, Christian S JensenAbstract:Motivated by the increasing availability of vehicle trajectory data, we propose learn-to-route, a comprehensive trajectory-based Routing Solution. Specifically, we first construct a graph-like structure from trajectories as the Routing infrastructure. Second, we enable trajectory-based Routing given an arbitrary (source, destination) pair. In the first step, given a road network and a collection of trajectories, we propose a trajectory-based clustering method that identifies regions in a road network. If a pair of regions are connected by trajectories, we maintain the paths used by these trajectories and learn a Routing preference for travel between the regions. As trajectories are skewed and sparse, %and although the introduction of regions serves to consolidate the sparse data, many region pairs are not connected by trajectories. We thus transfer Routing preferences from region pairs with sufficient trajectories to such region pairs and then use the transferred preferences to identify paths between the regions. In the second step, we exploit the above graph-like structure to achieve a comprehensive trajectory-based Routing Solution. Empirical studies with two substantial trajectory data sets offer insight into the proposed Solution, indicating that it is practical. A comparison with a leading Routing service offers evidence that the paper's proposal is able to enhance Routing quality.
