Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the distributed multi-sensor tracking problem in a WSN as an inferenc...
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Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the distributed multi-sensor tracking problem in a WSN as an inference problem on a factor graph. Using particle filtering methods, we propose a nonparametric variant of sum-product algorithm (SPA), called sequential particle-based SPA (SPSPA), for factor graphs to infer the multi-sensor target states over time. In the proposed algorithm, importance sampling methods are used to sample from message products, and the computational complexity of SPSPA is thus linear in the number of particles. We apply the SPSPA to a distributed multi-sensor tracking problem, and evaluate its performance in terms of the measurement noise and the number of particles.
In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of...
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In this paper, we explore network architecture anal key technologies for content-centric networking （CCN）, an emerging networking technology in the big-data era. We descrihe the structure anti operation mechanism of tl CCN node. Then we discuss mobility management, routing strategy, and caching policy in CCN. For better network performance, we propose a probability cache replacement policy that is based on cotent popularity. We also propose and evaluate a probability cache with evicted copy-up decision policy.
It is necessary for a server oriented to the Internet of Things(IOT) applications to provide countless connections with efficient andreliable *** the communication layer should try to lower the *** a highly efficient ...
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ISBN:
(纸本)9781467356985
It is necessary for a server oriented to the Internet of Things(IOT) applications to provide countless connections with efficient andreliable *** the communication layer should try to lower the *** a highly efficient design for a socket server with buffer pool and a thread pool for concurrent request on the IOT platform is *** reduces the system overhead and buffer usage to the largest extent while faced with a large number of connections and digital *** simulation shows that a socket server with a thread pool and buffer pool could lower the overhead on the context switch of threads as well as the I/O *** creates and destroys threads so as to energize the system.
Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the sensor self-localization problem in a WSN as an inference problem...
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Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the sensor self-localization problem in a WSN as an inference problem on a factor graph. Using a sequential schedule of message updates, a sequential uniformly reweighted sum-product algorithm (SURW-SPA) is developed for self-localization problems. The proposed algorithm combines the distributed nature of belief propagation (BP) with the improved performance of sequential tree-reweighted message passing (TRW-S) algorithm. We apply the SURW-SPA to sensor self-localization in large-scale static networks, and evaluate its performance in terms of localization accuracy and convergence speed.
P-homomorphic signature is a general framework for computing on authenticated data, which is recently proposed by Ahn et al. With P-homomorphic signature, any third party can derive a signature on the object message m...
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Stream data is a very common data type in big data and in many data streams applications,users tend to pay more attention to the mode information of the data *** mining frequent patterns in data streams is a significa...
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ISBN:
(纸本)9781479900763
Stream data is a very common data type in big data and in many data streams applications,users tend to pay more attention to the mode information of the data *** mining frequent patterns in data streams is a significative ***,finding frequent itemests in a data set with predefined fixed support threshold could be seen as an optimization *** this paper,the problem of frequent itemsets mining is derived as a non-linear optimization problem,then genetic algorithm is adopted to solve *** the formal and bitmap representation of frequent itemsets,the non-linear optimization problem is transformed to 0-1 programming.A set of experimental results show that unlike typical Apriori algorithm,the complexity of time and memory space grows exponentially as the support decrease,our proposed algorithm has a high time and space efficiency even with a very low support.
According to the significant impact on the accuracy rate of detection of current immune algorithms brought by incorrect classification of signal, it proposes network malicious code dendritic cell immune algorithm base...
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In this paper, we propose a robust object tracking algorithm based on SURF. First, we adopt a two-stage matching method to improve the accuracy of SURF matching points. Then a template update method is used to deal wi...
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In this paper, we propose a robust object tracking algorithm based on SURF. First, we adopt a two-stage matching method to improve the accuracy of SURF matching points. Then a template update method is used to deal with the problem of object appearance change. Next we use matching points between new template and candidate region to locate the initial position of object. As template update and object occlusion will cause the accumulation of tracking errors, therefore, at last fixed template is used to correct object's position. For those frames which have little matching points, we use Meanshift instead of SURF to track object. The experiments demonstrate that our work is robust and can track object accurately in complex environments.
Proxy re-signature is proposed by Blaze, Blemmer and Strauss (BBS), in which a semi-trusted proxy acts as a translator converts a signature from Alice into a signature from Bob on the same message. Proxy re-signature ...
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Proxy re-signature is proposed by Blaze, Blemmer and Strauss (BBS), in which a semi-trusted proxy acts as a translator converts a signature from Alice into a signature from Bob on the same message. Proxy re-signature is a very useful tool for the interoperable DRM architecture and the proof of passed path in cloud computing. However, cloud users usually are mobile devices which are constrained with processing and power limitations. When a mobile user obtain the converted signature from the proxy (cloud server), it still can not verify it due to the heavy computation cost. We propose a new definition of server-aided verification proxy re-signature which consist of a proxy re-signature scheme and a server-aided verification protocol. With the server-aided verification protocol, some computational tasks for a proxy re-signature verification are carried out by the proxy (cloud server), which is generally untrusted, therefore, it is very useful for mobile devices. We present, on the basis of Ateniese and Hohenberger's unidirectional proxy re-signature scheme, two novel existential unforgeability server-aided verification proxy re-signature schemes.
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