The Experts below are selected from a list of 49506 Experts worldwide ranked by ideXlab platform
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.
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MDM (1) - Vehicle Routing with User-Generated Trajectory Data
2015 16th IEEE International Conference on Mobile Data Management, 2015Co-Authors: Vaida Ceikute, Christian S JensenAbstract:Rapidly increasing volumes of GPS data collected from vehicles provide new and increasingly comprehensive insight into the routes that drivers prefer. While Routing Services generally compute shortest or fastest routes, recent studies suggest that local drivers often prefer routes that are neither shortest nor fastest, indicating that drivers value route properties that are diverse and hard to quantify or even identify. We propose a Routing Service that uses an existing Routing Service while exploiting the availability of historical route usage data from local drivers. Given a source and destination, the Service recommends a corresponding route that is most preferred by local drivers. It uses a route preference function that takes into account the number of distinct drivers and the number of trips associated with a route, as well as temporal aspects of the trips. The paper provides empirical studies with real route usage data and an existing online Routing Service.
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MDM (1) - Routing Service Quality -- Local Driver Behavior Versus Routing Services
2013 IEEE 14th International Conference on Mobile Data Management, 2013Co-Authors: Vaida Ceikute, Christian S JensenAbstract:Mobile location-based Services is a very successful class of Services that are being used frequently by users with GPS-enabled mobile devices such as smartphones. This paper presents a study of how to exploit GPS trajectory data, which is available in increasing volumes, for the assessment of the quality of one kind of location-based Service, namely Routing Services. Specifically, the paper presents a framework that enables the comparison of the routes provided by Routing Services with the actual driving behaviors of local drivers. Comparisons include route length, travel time, and also route popularity, which are enabled by common driving behaviors found in available trajectory data. The ability to evaluate the quality of Routing Services enables Service providers to improve the quality of their Services and enables users to identify the Services that best serve their needs. The paper covers experiments with real vehicle trajectory data and an existing online navigation Service. It is found that the availability of information about previous trips enables better prediction of route travel time and makes it possible to provide the users with more popular routes than does a conventional navigation Service.
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.
Michele Nogueira - One of the best experts on this subject based on the ideXlab platform.
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Routing management for performance and security tradeoff in wireless mesh networks
International Journal of Information Security, 2015Co-Authors: Helber Silva, Aldri Santos, Michele NogueiraAbstract:Wireless mesh networks (WMNs) support multimedia applications that claim for high level of security and performance simultaneously. However, wireless medium and multihop communication allow the action of attackers that can violate data packets or compromise the Routing Service, reducing performance and quality of Service (QoS) of applications. Even in normal conditions of the network, without the presence of attackers, interferences in the shared wireless medium reduce the overall performance of paths. Such aspects require the development of new Routing management approaches to address security and performance together. In this work, we integrate a path selection scheme, called CRoss-layer and Adaptive path selection scheme for Balancing performance and security on WMN data Routing (CRAB), in the Routing Service to improve performance and security of multimedia applications, even in face of attacks. Novel results from scenarios under different data traffic patterns representative from multimedia applications show that the CRAB scheme yields a better tradeoff between network performance and security, even when the network is under Routing attacks.
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A Security Management Architecture for Supporting Routing Services on WANETs
IEEE Transactions on Network and Service Management, 2012Co-Authors: Michele Nogueira, Helber Silva, Aldri Santos, Guy PujolleAbstract:Due to the raising dependence of people on critical applications and wireless networks, high level of reliability, security and availability is claimed to assure secure and reliable Service operation. Wireless ad hoc networks (WANETs) experience serious security issues even when solutions employ preventive or reactive security mechanisms. In order to support both network operations and security requirements of critical applications, we present SAMNAR, a Survivable Ad hoc and Mesh Network ARchitecture. Its goal lies in managing adaptively preventive, reactive and tolerant security mechanisms to provide essential Services even under attacks, intrusions or failures. We use SAMNAR to design a path selection scheme for WANET Routing. The evaluation of this path selection scheme considers scenarios using urban mesh network mobility with urban propagation models, and also random way point mobility with two-ray ground propagation models. Results show the survivability achieved on Routing Service under different conditions and attacks.
Cauligi S. Raghavendra - One of the best experts on this subject based on the ideXlab platform.
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An autonomic Routing framework for sensor networks
Cluster Computing, 2006Co-Authors: Cauligi S. Raghavendra, S. Berson, R. BradenAbstract:Current Routing Services for sensor networks are often designed for specific applications and network conditions, thus have difficulty in adapting to application and network dynamics. This paper proposes an autonomic framework to promote the adaptivity of Routing Services in sensor networks. The key idea of this framework is to maintain some feature functions that are decoupled from originally-integrated Routing Services. This separation enables significant Service changes to be done by only tuning these functions. Measures including parameterization are taken to save the energy for changing these functions. Further, this framework includes a monitoring module to support a policy-based collaborative adaptation. This paper shows an example autonomic Routing Service conforming to this framework.
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Adaptive Routing Services in ad-hoc and sensor networks
2005Co-Authors: Cauligi S. RaghavendraAbstract:In this dissertation, two different approaches are proposed to improve adaptability of Routing Services for mobile ad-hoc and sensor networks. For mobile ad-hoc networks, we propose a general approach called active ad-hoc network Routing that uses a helper module to improve existing Routing algorithms without changing their inner mechanisms. This helper module issues probing packets that roam around an ad-hoc network to collect information which then is used to update Routing state. By collecting different state information, adaptability of existing ad-hoc network Routing algorithms can be improved in multiple aspects. As a case study, we apply this general approach to the Dynamic Source Routing algorithm in ad-hoc networks. The resulting algorithm, called Active DSR, collects topology and queue-length information to update route cache in DSR. Discussions and extensive simulations show that Routing cache miss rates are reduced by using the topology information, and network congestion is improved by using the queue-length information. We also show energy consumption and TCP performance improvement under ADSR. For sensor networks, we propose a new Routing paradigm called X Visiting-pattern Routing (XVR) to promote Routing flexibility. Visiting-patterns indicate where to forward packets as next hops in a network and are essential to any Routing Service. Unlike any existing Routing Service in which each packet handler is integrated with its visiting-pattern, XVR deliberately decouples visiting-patterns of packets from their corresponding packet handlers. The separated packet handlers consist of a Routing core that calls the visiting-pattern module when issuing or forwarding packets. This separation has several important implications for building flexible Routing Services in sensor networks. First, a Routing Service can be changed by simply using different visiting-patterns with low energy cost. Second, extensive simulations show that existing and new Routing Services can be brought together for comprehensive experiments in a unified environment. Third, automatic and concurrent Routing Services can be built on top of XVR without changing the Routing core. As a case study, we show how to conduct automatic Routing changes between two known Routing Services, push and pull, with XVR, and evaluate performance gains.
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Building programmable Routing Service for sensor networks
Computer Communications, 2005Co-Authors: Cauligi S. RaghavendraAbstract:Current Routing Services for sensor networks are application-specific. They are pre-configured into nodes, and thus have difficulty in adapting to different applications and network conditions. This paper describes a framework to build programmable Routing Services for sensor networks. This framework includes a parameter space that identifies both common and different properties among Routing Services. With this parameter space, different Routing Services can be obtained with small programming effort. A programmable Routing architecture is proposed to maintain this parameter space and support energy-efficient Service deployment. This paper presents implementation details of this programmable framework and shows simulation results.
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A programmable Routing framework for autonomic sensor networks
2003 Autonomic Computing Workshop, 1Co-Authors: Cauligi S. Raghavendra, S. Berson, B. BradenAbstract:This paper proposes a programmable Routing framework that promotes the adaptivity in Routing Services for sensor networks. This framework includes a universal Routing Service and an automatic deployment Service. The universal Routing Service allows the introduction of different Services through its tunable parameters and programmable components. The deployment Service completes the configuration of the universal Routing Service throughout a sensor network in an automatic and energy-efficient way. With this deployment Service, a self-configuring ability is realized for sensor Routing Services. With the changeable parameters and programmable components of the universal Routing Service, the self-optimizing as well as other autonomic abilities can be explored in an experimental sensor network conforming to the proposed framework.
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INFOCOM - XVR: X visiting-pattern Routing for sensor networks
Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 1Co-Authors: Cauligi S. RaghavendraAbstract:This paper proposes a new Routing paradigm for sensor networks called X visiting-pattern Routing (XVR) that decouples visiting-patterns of packets from the Routing core. Visiting-patterns indicate where to forward packets as next hops in a network and are essential to any Routing Service. With XVR, the visiting-patterns are defined in a separate module from the Routing core, thus enabling them to be changed independently. The overhead of changing Routing behavior is further reduced significantly by parameterizing usual visiting-patterns; different Routing Services can be obtained by simply changing the visiting-pattern parameters. In addition, with the extensive Routing behavior space and the separate visiting-pattern module, XVR furnishes a desirable base to realize automatic and concurrent Routing Services that adapt to application and network dynamics. Discussions and extensive simulations show that by systematically testing different visiting-patterns XVR provides a unique environment and a comprehensive approach to study both existing and new Routing algorithms.
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.
