In the emerging digital age, massive production of data is occurred actively or passively by collecting data from users and environment via applications, sensor devices and so on. that makes it important and crucial t...
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ISBN:
(纸本)9781538659304
In the emerging digital age, massive production of data is occurred actively or passively by collecting data from users and environment via applications, sensor devices and so on. that makes it important and crucial to have the ability to process big data efficiently and effectively utilize it. the challenge to process big data is that it has high volume, velocity, variety, as well as veracity and value. In this paper, we present a survey of related work and prescribe our recommendations towards building Bayesian classification for big data environments. It is based on MapReduce and is distributed, parallel, single pass and incremental which makes it feasible to be deployed and executed on cloud computing platform We also carry out scalability analysis of the proposed solution that it can train Bayesian classifier to perform predictive analytics by processing big data with large volume, velocity and variety.
Execution times of dynamic distributed real-time systems are affected by variables that originate in external environments, and this leads to a new class of task allocation problems. A taxonomy was introduced to accom...
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Execution times of dynamic distributed real-time systems are affected by variables that originate in external environments, and this leads to a new class of task allocation problems. A taxonomy was introduced to accommodate these external variables and help systematically understand and characterize the set of problems. Existing work can be classified withthe taxonomy, and the classification also reveals many open problems.
the experimental researches of efficiency of coarse-grain parallel method of artificial neural networks training with static mapping onto processors of parallel computer are presented in this paper. the features of pa...
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the experimental researches of efficiency of coarse-grain parallel method of artificial neural networks training with static mapping onto processors of parallel computer are presented in this paper. the features of parallel algorithm implementation using C language and MPI library are described. the research of parallel method is carried out using analysis of its speed-up and efficiency.
While distributed multi-agent systems are especially suitable for taking advantage of the capacity for evolution and adaptation in ubiquitous computing, writing such programs is a difficult and complicated task if not...
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ISBN:
(纸本)9780889867741
While distributed multi-agent systems are especially suitable for taking advantage of the capacity for evolution and adaptation in ubiquitous computing, writing such programs is a difficult and complicated task if not supported by an agent programming framework. this paper presents a real-time agent service layer (RT-ASL) that is built on an existing de facto standard for interconnecting distributed objects, CORBA middleware. RT-ASL enables programmers to write distributed cooperative application programs for ubiquitous computing using a high-level abstraction of software agents. As criteria for designing RT-ASL on CORBA, we have made four important decisions regarding the message passing communication mechanism for agent communications, agent service discovery mechanism, real-time agent communication language, and real-time generic scheduling interfaces. this paper justifies the importance of such design decisions and how they can effectively deal withthe complicated difficulties.
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