Titlebook: Distributed Computing and Internet Technology; 10th International C Raja Natarajan Conference proceedings 2014 Springer International Publi

讨人喜欢

Reinforcement Learning for Matrix Computations: PageRank as an Exampleg model-free, i.e., not dependent on any specific assumptions about the transition probabilities in the random web-surfer model. We analyze its convergence and finite time behavior and present some supporting numerical experiments.

APNEA

思考

Value Added Services on Stationary Vehicular Cloud a communication mechanism for providing value added services on an opportunistically formed Stationary Vehicular Cloud by exploiting the idle vehicular resources that, now has become a thing of commonality in cities.

切碎

Proclaim

Software Transactional Memory Friendly Slot Schedulersthms follow the reverse trend. We thus propose a class of algorithms using software transactional memory (STM) that are in the middle of the spectrum. They equitably balance fairness and throughput, and are much simpler to design and verify.

hermitage

0302-9743 l papers presented together with 6 invited talks in this volume were carefully reviewed and selected from 197 submissions. The papers cover topics such as distributed computing, sensor networks, Internet technologies and applications, security and multimedia..978-3-319-04482-8978-3-319-04483-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

遗产

Jaume Barceló,Xavier Ros-Roca,Lidia Monterot are known to be key components for the modular design of complex reactive behaviors. HipHop departs from Esterel by its ability to handle the dynamicity of Web applications, thanks to the reflexivity of Hop. Using a music player example, we show how to modularly build a non-trivial Hop application using HipHop orchestration code.

淘气

遭受

Negotiating a European Defence Frameworkapplied on noisy sensor logs. Representative methods from supervised and unsupervised discretization, like binning, clustering and entropy minimization are evaluated with context extraction. Interestingly, unlike common perception, for discretization of sensor data, supervised algorithms do not have a clear edge over unsupervised.

FATAL