Real-World Spatio–Temporal Behavior Aware D2D Multicast Networks

2020 ◽  
Vol 7 (3) ◽  
pp. 1675-1686
Author(s):  
Mansi Peer ◽  
Vivek Ashok Bohara ◽  
Anand Srivastava
2012 ◽  
Vol 204-208 ◽  
pp. 2721-2725
Author(s):  
Hua Ji Zhu ◽  
Hua Rui Wu

Village land continually changes in the real world. In order to keep the data up-to-date, data producers need update the data frequently. When the village land data are updated, the update information must be dispensed to the end-users to keep their client-databases current. In the real world, village land changes in many forms. Identifying the change type of village land (i.e. captures the semantics of change) and representing them in the data world can help end-users understand the change commonly and be convenient for end-users to integrate these change information into their databases. This work focuses on the model of the spatio-temporal change. A three-tuple model CAR for representing the spatio-temporal change is proposed based on the village land feature set before change and the village land feature set after change, change type and rules. In this model, the C denotes the change type. A denotes the attribute set; R denotes the judging rules of change type. The rule is described by the IF-THEN expressions. By the operations between R and A, the C is distinguished. This model overcomes the limitations of current methods. And more, the rules in this model can be easy realized in computer program.


Author(s):  
Ahmed Abusnaina ◽  
Mohammed Abuhamad ◽  
DaeHun Nyang ◽  
Songqing Chen ◽  
An Wang ◽  
...  

Cyber Crime ◽  
2013 ◽  
pp. 395-415 ◽  
Author(s):  
Can Brochmann Yildizli ◽  
Thomas Pedersen ◽  
Yucel Saygin ◽  
Erkay Savas ◽  
Albert Levi

Recent concerns about privacy issues have motivated data mining researchers to develop methods for performing data mining while preserving the privacy of individuals. One approach to develop privacy preserving data mining algorithms is secure multiparty computation, which allows for privacy preserving data mining algorithms that do not trade accuracy for privacy. However, earlier methods suffer from very high communication and computational costs, making them infeasible to use in any real world scenario. Moreover, these algorithms have strict assumptions on the involved parties, assuming involved parties will not collude with each other. In this paper, the authors propose a new secure multiparty computation based k-means clustering algorithm that is both secure and efficient enough to be used in a real world scenario. Experiments based on realistic scenarios reveal that this protocol has lower communication costs and significantly lower computational costs.


2020 ◽  
Vol 25 (9) ◽  
pp. 931-947
Author(s):  
Ding Xu ◽  
Li Cong ◽  
Geoffrey Wall

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e19397 ◽  
Author(s):  
Denis B. Rosemberg ◽  
Eduardo P. Rico ◽  
Ben Hur M. Mussulini ◽  
Ângelo L. Piato ◽  
Maria E. Calcagnotto ◽  
...  

1989 ◽  
Vol 44 (11) ◽  
pp. 1046-1050 ◽  
Author(s):  
J. Parisi ◽  
J. Peinke ◽  
R. P. Huebener

We study the cooperative spatio-temporal behavior of semiconductor breakdown via both probabilistic and dynamical characterization methods (fractal dimensions, entropies, Lyapunov exponents, and the corresponding scaling functions). Agreement between the results obtained from the different numerical concepts (e.g., verification of the Kaplan-Yorke conjecture and the Newhouse- Ruelle-Takens theorem) gives a self-consistent picture of the physical situation investigated. As a consequence, the affirmed chaotic hierarchy of generalized horseshoe-type strange attractors may be ascribed to weak nonlinear coupling between competing localized oscillation centers intrinsic to the present semiconductor system


2016 ◽  
Vol 3 (6) ◽  
pp. 160196 ◽  
Author(s):  
Matthew J. Williams ◽  
Mirco Musolesi

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.


2017 ◽  
Vol 6 (5) ◽  
pp. 151 ◽  
Author(s):  
Luliang Tang ◽  
Qianqian Zou ◽  
Xia Zhang ◽  
Chang Ren ◽  
Qingquan Li

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