Shenzhen Key Laboratory of Data Vitalization Smart City

Shenzhen, China

Shenzhen Key Laboratory of Data Vitalization Smart City

Shenzhen, China
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Pu J.,Beihang University | Pu J.,Shenzhen Key Laboratory of Data Vitalization Smart City | Liu X.,CAS Institute of Computing Technology | Torabkhani N.,Georgia Institute of Technology | And 3 more authors.
Wireless Communications and Mobile Computing | Year: 2015

In this paper, we study the block delivery delay of random linear network coding in two-hop single-unicast delay-tolerant networks with grid-based mobility. By block delivery delay, we mean how long it takes the destination to receive all the K information packets of a single block. Our work includes two parts. First, we give a general analysis of the dependency between packet spaces spanned by different nodes in a stochastic way. Then we simplify the result by means of the approximation. By the dependency analysis, we can accurately update nodes' innovativeness rank. Second, via tracking the innovativeness ranks of all nodes, we develop an analytic framework to iteratively compute the cumulative distribution function of the block delivery delay. Our simulation results verify that both parts of our analysis are sufficiently accurate. Copyright © 2013 John Wiley & Sons, Ltd.


Pu J.,Beihang University | Pu J.,Shenzhen Key Laboratory of Data Vitalization Smart City | Chen J.,Beihang University | Chen J.,Shenzhen Key Laboratory of Data Vitalization Smart City | And 4 more authors.
IEICE Transactions on Communications | Year: 2012

This paper presents an efficient algorithm, NEAR, that allows sensor nodes to acquire their off-duty eligibility. Any node only needs to calculate the coverage degrees of the intersections on its sensing boundary, and cooperates with its neighbors to know if it is redundant or not. The computing complexity of NEAR is only O(nlogn). Copyright © 2012 The Institute of Electronics, Information and Communication Engineers.


Wei Q.,Beihang University | Wei Q.,Shenzhen Key Laboratory of Data Vitalization Smart City | Xiong Z.,Beihang University | Xiong Z.,Shenzhen Key Laboratory of Data Vitalization Smart City | And 6 more authors.
AEU - International Journal of Electronics and Communications | Year: 2011

Multiple vehicle targets tracking is one of the most challenging problems in Intelligent Transportation Systems. It is used for recognizing and understanding vehicle behaviors, especially suffering from illumination, scale, pose variations and occlusions. In this paper, we explore a robust tracking algorithm, combining deterministic and probabilistic methods, to solve this problem. We build a fusion observation model with color and local integral orientation descriptor, and give multiple vehicle targets model. In order to overcome the disadvantage of particle impoverishment, we propose a layered particle filter architecture embedding continuous adaptive mean shift, which considers both concentration and diversity of particles, and the particle set can better represent the posterior probability density. This paper also presents experiments using real video sequences to verify the proposed method. © 2011 Elsevier GmbH. All rights reserved.


Zeng J.-B.,Beihang University | Zeng J.-B.,Shenzhen Key Laboratory of Data Vitalization Smart City | Leng B.,Beihang University | Leng B.,Shenzhen Key Laboratory of Data Vitalization Smart City | And 3 more authors.
International Journal of Modern Physics C | Year: 2011

In this paper, an extended FF model (floor field model) to simulate pedestrian dynamics in complex scenarios is proposed. Considering that pedestrians are unaware of the global view of traffic path, we introduce pedestrians' local views and propose a framework to change a pedestrian's static floor field each time they enter a new convex area. A pedestrian's view is limited to a convex polygon. When they travel from one convex area to another, they make decisions about the next goal according to the distances between them and the candidate goals, as well as densities of capacity and herding behaviors. Meanwhile, after making an initial decision about the next goal, a pedestrian can estimate the travel time to reach each visible goal and change their path adaptively within the convex area. Simulations in two scenarios are conducted and the results show that pedestrians under local views behave more practically than those under global views in complex scenarios. Parameter settings are also discussed along with suggestions that can be given to designers for improving traffic management. © 2011 World Scientific Publishing Company.

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