The Experts below are selected from a list of 22833 Experts worldwide ranked by ideXlab platform
Bhaskar Krishnamachari - One of the best experts on this subject based on the ideXlab platform.
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the effect of mobility induced Location errors on geographic routing in mobile ad hoc sensor networks analysis and improvement using mobility prediction
IEEE Transactions on Mobile Computing, 2004Co-Authors: Dongjin Son, Ahmed Helmy, Bhaskar KrishnamachariAbstract:Geographic routing has been introduced in mobile ad hoc networks and sensor networks. Under ideal settings, it has been proven to provide drastic performance improvement over strictly address centric routing schemes. While geographic routing has been shown to be correct and efficient when Location information is accurate, its performance in the face of Location errors is not well understood. We study the effect of inaccurate Location information caused by node mobility under a rich set of scenarios and mobility models. We identify two main problems, named LLNK and LOOP, that are caused by mobility-induced Location errors. Based on analysis via ns-2 simulations, we propose two mobility prediction schemes - neighbor Location prediction (NLP) and Destination Location prediction (DLP) to mitigate these problems. Simulation results show noticeable improvement under all mobility models used in our study. Under the settings we examine, our schemes achieve up to 27 percent improvement in packet delivery and 37 percent reduction in network resource wastage, on average without incurring any additional communication or intense computation.
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the effect of mobility induced Location errors on geographic routing in ad hoc networks analysis and improvement using mobility prediction
Wireless Communications and Networking Conference, 2004Co-Authors: Dongjin Son, Ahmed Helmy, Bhaskar KrishnamachariAbstract:Geographic routing in mobile ad hoc networks has proved to provide drastic performance improvement over strictly address-centric routing schemes. While geographic routing has been shown to be correct and efficient when Location information is accurate, its performance in the face of Location errors is not well understood. In this paper, we study the effect of inaccurate Location information caused by node mobility under a rich set of scenarios and mobility models. We identify two main problems, named LINK and LOOP, that are caused by mobility-induced Location errors. Based on the analysis via ns-2 simulations, we propose two mobility prediction schemes - neighbor Location prediction (NLP) and Destination Location prediction (DLP) to mitigate these problems. Simulation results have shown noticeable improvement under all mobility models used in our study. Our schemes achieve up to 27% improvement in packet delivery and 37% reduction in network resource wastage on average without incurring any additional communication or intense computation.
Jian Ren - One of the best experts on this subject based on the ideXlab platform.
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r star Destination Location privacy schemes in wireless sensor networks
International Conference on Communications, 2015Co-Authors: Leron Lightfoot, Jian RenAbstract:Wireless sensor networks (WSNs) can provide the world with a technology for real-time event monitoring for both military and civilian applications. One of the primary concerns that hinder the successful deployment of wireless sensor networks is providing adequate Location privacy. Many protocols have been proposed to provide Location privacy but most are based on public-key cryptosystems, while others are either energy inefficient or have certain security flaws. In this paper, after analyzing security weakness of the existing schemes, we propose an architecture that addresses the security flaw for Destination Location privacy in WSNs based on energy-aware two phase routing protocol. We call this scheme the R-STaR routing protocol. In the first routing phase of R-STaR routing, the source node transmits the the message to a randomly selected intermediate node located in a pre-determined region surrounding the source node, which we call the R-STaR area. In the second routing phase, the message is routed to the Destination node using shortest path mix with fake message injections. We show that R-STaR routing provides a exceptional balance between security and energy consumption in comparison to existing well-known proposed schemes.
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ICC - R-STaR Destination-Location privacy schemes in wireless sensor networks
2015 IEEE International Conference on Communications (ICC), 2015Co-Authors: Leron Lightfoot, Jian RenAbstract:Wireless sensor networks (WSNs) can provide the world with a technology for real-time event monitoring for both military and civilian applications. One of the primary concerns that hinder the successful deployment of wireless sensor networks is providing adequate Location privacy. Many protocols have been proposed to provide Location privacy but most are based on public-key cryptosystems, while others are either energy inefficient or have certain security flaws. In this paper, after analyzing security weakness of the existing schemes, we propose an architecture that addresses the security flaw for Destination Location privacy in WSNs based on energy-aware two phase routing protocol. We call this scheme the R-STaR routing protocol. In the first routing phase of R-STaR routing, the source node transmits the the message to a randomly selected intermediate node located in a pre-determined region surrounding the source node, which we call the R-STaR area. In the second routing phase, the message is routed to the Destination node using shortest path mix with fake message injections. We show that R-STaR routing provides a exceptional balance between security and energy consumption in comparison to existing well-known proposed schemes.
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Providing Destination-Location Privacy in Wireless Sensor Network Using Bubble Routing
Lecture Notes in Electrical Engineering, 2012Co-Authors: Leron Lightfoot, Jian RenAbstract:One of the most challenging problems for wireless sensor networks (WSNs) is in how to provide adequate Location privacy. In this paper, we will address the concern to adequately provide routing-based Destination-Location privacy (DLP). The privacy of the Location of the Destination sensor node is critical and highly vulnerable by the usage of wireless communications. While message content privacy can be accomplished through message encryption, it is much more difficult to adequately address the Location privacy. For WSNs, Destination-Location privacy service is further complex by the fact that sensors consist of low-cost and energy efficient radio devices. Therefore, using computationally intensive cryptographic algorithms (such as public-key cryptosystems) and large scale broadcasting-based protocols are not suitable for WSNs. We propose a unique routing technique that can provide strong Destination-Location privacy with low tradeoff in the energy overhead. In our proposed scheme, the source node randomly selects an intermediate node from pre-determined region located around the Destination node, which we refer to as the bubble region. The bubble region would be large enough to make it infeasible for an adversary to monitor the entire area. Also, in this scheme, we will mix real messages with fake messages to add to the security strength in providing Destination-Location privacy. We compare our proposed scheme to other well known schemes.
Rahman Ashfaqur - One of the best experts on this subject based on the ideXlab platform.
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ADC - An Effective Spatio-Temporal Approach for Predicting Future Semantic Locations
Lecture Notes in Computer Science, 2016Co-Authors: Hamidu Abdel-fatao, Jixue Liu, Rahman AshfaqurAbstract:Human mobility prediction in ubiquitous computing is the ability of a system to forecast the anticipated movement of an individual or a group of persons. This interdisciplinary problem has gained traction in fields of academic and industrial research mainly because it is fundamental to achieving system efficiency and marketing efficacy in many applications. This study seeks to develop a novel heuristic technique that predicts the actual geo-spatial Locations associated with the most probable semantic tags of Locations (e.g. restaurant) that individuals are likely to visit. The intuition of this work lies in the fact that, for any given probable future semantic tag there exists multiple geo-spatial Locations associated with it, hence the need to disambiguate the actual Destination Location. We develop an algorithm \( STS \_ predict \), that exploits the spatio-temporal relationships between the current Location of a target individual and candidate geo-spatial Locations associated with future semantic tags to predict the actual Destination Location. We evaluate our approach on a real world GPS trajectory dataset.
Samiha Samrose - One of the best experts on this subject based on the ideXlab platform.
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Trip planning queries with Location privacy in spatial databases
World Wide Web, 2017Co-Authors: Subarna Chowdhury Soma, Tanzima Hashem, Muhammad Aamir Cheema, Samiha SamroseAbstract:Privacy has become a major concern for the users of Location-based services (LBSs) and researchers have focused on protecting user privacy for different Location-based queries. In this paper, we propose techniques to protect Location privacy of users for trip planning (TP) queries, a novel type of query in spatial databases. A TP query enables a user to plan a trip with the minimum travel distance, where the trip starts from a source Location, goes through a sequence of points of interest (POIs) (e.g., restaurant, shopping center), and ends at a Destination Location. Due to privacy concerns, users may not wish to disclose their exact Locations to the Location-based service provider (LSP). In this paper, we present the first comprehensive solution for processing TP queries without disclosing a user’s actual source and Destination Locations to the LSP. Our system protects the user’s privacy by sending either a false Location or a cloaked Location of the user to the LSP but provides exact results of the TP queries. We develop a novel technique to refine the search space as an elliptical region using geometric properties, which is the key idea behind the efficiency of our algorithms. To further reduce the processing overhead while computing a trip from a large POI database, we present an approximation algorithm for privacy preserving TP queries. Extensive experiments show that the proposed algorithms evaluate TP queries in real time with the desired level of Location privacy.
Dongjin Son - One of the best experts on this subject based on the ideXlab platform.
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the effect of mobility induced Location errors on geographic routing in mobile ad hoc sensor networks analysis and improvement using mobility prediction
IEEE Transactions on Mobile Computing, 2004Co-Authors: Dongjin Son, Ahmed Helmy, Bhaskar KrishnamachariAbstract:Geographic routing has been introduced in mobile ad hoc networks and sensor networks. Under ideal settings, it has been proven to provide drastic performance improvement over strictly address centric routing schemes. While geographic routing has been shown to be correct and efficient when Location information is accurate, its performance in the face of Location errors is not well understood. We study the effect of inaccurate Location information caused by node mobility under a rich set of scenarios and mobility models. We identify two main problems, named LLNK and LOOP, that are caused by mobility-induced Location errors. Based on analysis via ns-2 simulations, we propose two mobility prediction schemes - neighbor Location prediction (NLP) and Destination Location prediction (DLP) to mitigate these problems. Simulation results show noticeable improvement under all mobility models used in our study. Under the settings we examine, our schemes achieve up to 27 percent improvement in packet delivery and 37 percent reduction in network resource wastage, on average without incurring any additional communication or intense computation.
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the effect of mobility induced Location errors on geographic routing in ad hoc networks analysis and improvement using mobility prediction
Wireless Communications and Networking Conference, 2004Co-Authors: Dongjin Son, Ahmed Helmy, Bhaskar KrishnamachariAbstract:Geographic routing in mobile ad hoc networks has proved to provide drastic performance improvement over strictly address-centric routing schemes. While geographic routing has been shown to be correct and efficient when Location information is accurate, its performance in the face of Location errors is not well understood. In this paper, we study the effect of inaccurate Location information caused by node mobility under a rich set of scenarios and mobility models. We identify two main problems, named LINK and LOOP, that are caused by mobility-induced Location errors. Based on the analysis via ns-2 simulations, we propose two mobility prediction schemes - neighbor Location prediction (NLP) and Destination Location prediction (DLP) to mitigate these problems. Simulation results have shown noticeable improvement under all mobility models used in our study. Our schemes achieve up to 27% improvement in packet delivery and 37% reduction in network resource wastage on average without incurring any additional communication or intense computation.