The Experts below are selected from a list of 120123 Experts worldwide ranked by ideXlab platform
Xuejie Zhu - One of the best experts on this subject based on the ideXlab platform.
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Social Feature enabled communications among devices toward the smart iot community
IEEE Communications Magazine, 2019Co-Authors: Houbing Song, Xuejie ZhuAbstract:Future IoT is expected to achieve ubiquitous access and information exchange on a global scale. Facing the massive IoT access and spectrum shortage problems, centralized control becomes prohibitively complicated. But with the increasing capability of IoT devices in communications and computing, IoT will gradually evolve to be highly autonomous, yield Social Features in IoT networking, and eventually form the smart IoT community. Motivated by the tendency of Socialization over IoT, this article first presents an overview and discussions on Social Features affecting connections among IoT devices. Then, we propose studies to characterize the highly-varying Social Features by using the queuing model and asymptotic analysis framework. With emphases on Social Features including credit and reputation, we show how to fit transmissions between IoT devices to the framework for Socially-aware optimization. Finally, this article shares opinions about open problems and future topics on Socially-aware design toward the smart IoT community.
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Social Feature enabled communications among devices towards smart iot community
arXiv: Networking and Internet Architecture, 2018Co-Authors: Houbing Song, Xuejie ZhuAbstract:Future IoT is expected to get ubiquitous connection and access in a global scale. In the meantime, with the empowered communications capability for IoT devices, IoT will evolve to be highly autonomous, even under the help from infrastructure, and thus will gradually establish the smart IoT community. One of the major challenges imposed on the smart IoT communities is the Socialization of IoT communications, because massive IoT accesses make centralized control very hard and also face the shortage of spectrum resources. Towards these issues, we in this article first present the overview and discussions on Social Features affecting connections among devices. Then, we motivate studies on the statistical characteristics of Social Features for connections among devices towards smart IoT. We further propose the queuing model under unified asymptotic analyses framework to characterize the statistical Social Features, with emphases on typical Social metrics such as credit, reputation, centrality, etc. How to apply these Features for network optimization is further suggested. Finally, we share our opinion on the open problems of Social-aware design towards future smart IoT.
Yunsheng Wang - One of the best experts on this subject based on the ideXlab platform.
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hypercube based multipath Social Feature routing in human contact networks
IEEE Transactions on Computers, 2014Co-Authors: Yunsheng WangAbstract:Most routing protocols for delay tolerant networks resort to the sufficient state information, including trajectory and contact information, to ensure routing efficiency. However, state information tends to be dynamic and hard to obtain without a global and/or long-term collection process. In this paper, we use the internal Social Features of each node in the network to perform the routing process. In this way, Feature-based routing converts a routing problem in a highly mobile and unstructured contact space to a static and structured Feature space. This approach is motivated from several human contact networks, such as the Infocom 2006 trace and MIT reality mining data, where people contact each other more frequently if they have more Social Features in common. Our approach includes two unique processes: Social Feature extraction and multipath routing. In Social Feature extraction, we use entropy to extract the m most informative Social Features to create a Feature space (F-space): (F1, F2,..., Fm), where Fi corresponds to a Feature. The routing method then becomes a hypercube-based Feature matching process, where the routing process is a step-by-step Feature difference resolving process. We offer two special multipath routing schemes: node-disjoint-based routing and delegation-based routing. Extensive simulations on both real and synthetic traces are conducted in comparison with several existing approaches, including spray-and-wait routing, spray-and-focus routing, and Social-aware routing based on betweenness centrality and similarity. In addition, the effectiveness of multipath routing is evaluated and compared to that of single-path routing.
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analysis of a hypercube based Social Feature multipath routing in delay tolerant networks
IEEE Transactions on Parallel and Distributed Systems, 2013Co-Authors: Yunsheng Wang, Weishih YangAbstract:Social behavior plays a more and more important role in delay tolerant networks (DTNs). In this paper, we present an analytical model for a hypercube-based Social Feature multipath routing protocol in DTNs. In this routing protocol, we use the internal Social Features of each node (individual) in the network for routing guidance. This approach is motivated from several real Social contact networks, which show that people contact each other more when they have more Social Features in common. This routing scheme converts a routing problem in a highly mobile and unstructured contact space (M-space) to a static and structured Feature space (F-space). The multipath routing process is a hypercube-based Feature matching process where the Social Feature differences are resolved step-by-step. A Feature matching shortcut algorithm for fast searching is presented where more than one Feature difference is resolved at one time. The multiple paths for the routing process are node-disjoint. We formally analyze the delivery rate and latency by using hypercube-based routing. The solutions for the expected values of latency and delivery rate are given under different path conditions: single-/multipath and Feature difference resolutions with/without shortcuts. Extensive simulations on both real and synthetic traces are conducted in comparison to several existing state-of-the-art DTN routing protocols.
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Social Feature based multi path routing in delay tolerant networks
International Conference on Computer Communications, 2012Co-Authors: Yunsheng WangAbstract:Most routing protocols for delay tolerant networks resort to the sufficient state information, including trajectory and contact information, to ensure routing efficiency. However, state information tends to be dynamic and hard to obtain without a global and/or long-term collection process. In this paper, we use the internal Social Features of each node in the network to perform the routing process. This approach is motivated from several Social contact networks, such as the Infocom 2006 trace, where people contact each other more frequently if they have more Social Features in common. Our approach includes two unique processes: Social Feature extraction and multi-path routing. In Social Feature extraction, we use entropy to extract the m most informative Social Features to create a Feature space (F-space): (F 1 , F 2 , …, F m ), where F i corresponds to a Feature. The routing method then becomes a hypercube-based Feature matching process where the routing process is a step-by-step Feature difference resolving process. We offer two special multi-path routing schemes: node-disjoint-based routing and delegation-based routing. Extensive simulations on both real and synthetic traces are conducted in comparison with several existing approaches, including spray-and-wait routing and spray-and-focus routing.
Weishih Yang - One of the best experts on this subject based on the ideXlab platform.
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analysis of a hypercube based Social Feature multipath routing in delay tolerant networks
IEEE Transactions on Parallel and Distributed Systems, 2013Co-Authors: Yunsheng Wang, Weishih YangAbstract:Social behavior plays a more and more important role in delay tolerant networks (DTNs). In this paper, we present an analytical model for a hypercube-based Social Feature multipath routing protocol in DTNs. In this routing protocol, we use the internal Social Features of each node (individual) in the network for routing guidance. This approach is motivated from several real Social contact networks, which show that people contact each other more when they have more Social Features in common. This routing scheme converts a routing problem in a highly mobile and unstructured contact space (M-space) to a static and structured Feature space (F-space). The multipath routing process is a hypercube-based Feature matching process where the Social Feature differences are resolved step-by-step. A Feature matching shortcut algorithm for fast searching is presented where more than one Feature difference is resolved at one time. The multiple paths for the routing process are node-disjoint. We formally analyze the delivery rate and latency by using hypercube-based routing. The solutions for the expected values of latency and delivery rate are given under different path conditions: single-/multipath and Feature difference resolutions with/without shortcuts. Extensive simulations on both real and synthetic traces are conducted in comparison to several existing state-of-the-art DTN routing protocols.
Houbing Song - One of the best experts on this subject based on the ideXlab platform.
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Social Feature enabled communications among devices toward the smart iot community
IEEE Communications Magazine, 2019Co-Authors: Houbing Song, Xuejie ZhuAbstract:Future IoT is expected to achieve ubiquitous access and information exchange on a global scale. Facing the massive IoT access and spectrum shortage problems, centralized control becomes prohibitively complicated. But with the increasing capability of IoT devices in communications and computing, IoT will gradually evolve to be highly autonomous, yield Social Features in IoT networking, and eventually form the smart IoT community. Motivated by the tendency of Socialization over IoT, this article first presents an overview and discussions on Social Features affecting connections among IoT devices. Then, we propose studies to characterize the highly-varying Social Features by using the queuing model and asymptotic analysis framework. With emphases on Social Features including credit and reputation, we show how to fit transmissions between IoT devices to the framework for Socially-aware optimization. Finally, this article shares opinions about open problems and future topics on Socially-aware design toward the smart IoT community.
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Social Feature enabled communications among devices towards smart iot community
arXiv: Networking and Internet Architecture, 2018Co-Authors: Houbing Song, Xuejie ZhuAbstract:Future IoT is expected to get ubiquitous connection and access in a global scale. In the meantime, with the empowered communications capability for IoT devices, IoT will evolve to be highly autonomous, even under the help from infrastructure, and thus will gradually establish the smart IoT community. One of the major challenges imposed on the smart IoT communities is the Socialization of IoT communications, because massive IoT accesses make centralized control very hard and also face the shortage of spectrum resources. Towards these issues, we in this article first present the overview and discussions on Social Features affecting connections among devices. Then, we motivate studies on the statistical characteristics of Social Features for connections among devices towards smart IoT. We further propose the queuing model under unified asymptotic analyses framework to characterize the statistical Social Features, with emphases on typical Social metrics such as credit, reputation, centrality, etc. How to apply these Features for network optimization is further suggested. Finally, we share our opinion on the open problems of Social-aware design towards future smart IoT.
Brian J. Hall - One of the best experts on this subject based on the ideXlab platform.
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Non-Social Features of smartphone use are most related to depression, anxiety and problematic smartphone use
Computers in Human Behavior, 2017Co-Authors: Jon D. Elhai, Jason C. Levine, Robert D. Dvorak, Brian J. HallAbstract:Little is known about the mechanisms of smartphone Features that are used in sealing relationships between psychopathology and problematic smartphone use. Our purpose was to investigate two specific smartphone usage types process use and Social use for associations with depression and anxiety; and in accounting for relationships between anxiety/depression and problematic smartphone use. Social smartphone usage involves Social Feature engagement (e.g., Social networking, messaging), while process usage involves non-Social Feature engagement (e.g., news consumption, entertainment, relaxation). 308 participants from Amazon's Mechanical Turk internet labor market answered questionnaires about their depression and anxiety symptoms, and problematic smartphone use along with process and Social smartphone use dimensions. Statistically adjusting for age and sex, we discovered the association between anxiety symptoms was stronger with process versus Social smartphone use. Depression symptom severity was negatively associated with greater Social smartphone use. Process smartphone use was more strongly associated with problematic smartphone use. Finally, process smartphone use accounted for relationships between anxiety severity and problematic smartphone use. Anxiety was more related to process (or consumption-based) smartphone use than Social smartphone use.Depression was inversely associated with problematic smartphone use.Process smartphone use was most associated with problematic smartphone use.Process smartphone use mediated relations between anxiety and problematic smartphone use.Clinical patients with depressive/anxious symptoms should schedule Social-related activity, facilitated by smartphones.
