Big data analysis requires adequate infrastructure and programming paradigms capable of processing large amount of data. Hadoop, the most known open-source implementation of the MapReduce paradigm, is widely employed ...
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ISBN:
(纸本)9781450346177
Big data analysis requires adequate infrastructure and programming paradigms capable of processing large amount of data. Hadoop, the most known open-source implementation of the MapReduce paradigm, is widely employed in big data analysis frameworks. However, in many recent application scenarios data are natively distributed over different geographic regions in data centers which are interconnected through network links with very lower bandwidth than those of the computing environments where traditionally Hadoop deployments are supposed to work. In such a context, Hadoop applications perform very poorly. To cope with these issues, we developed a Hierarchical Hadoop Framework (H2F) specifically designed to work on geodistributed data. In this work, we compare the performance of H2F with that of a plain Hadoop implementation. First results show that for very large amount of data the H2F solution performs better than the Hadoop.
Data mining algorithms tacitly quite access to the data either at centralized or distributed form. distributed data becomes a big challenge and cannot handle by a classical analytic tool. Cloud computing can solve the...
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ISBN:
(纸本)9781509036967
Data mining algorithms tacitly quite access to the data either at centralized or distributed form. distributed data becomes a big challenge and cannot handle by a classical analytic tool. Cloud computing can solve the issues of processing, storing, and analyzing the data at distributing locations within the cloud. However, a significant problem that is preventing free sharing of data is privacy and security issues, therefore obstructing data mining schemes. Lately, there is increasingly hard to find a solution to these problems. Due to the existing knowledge in a more distributed data and better for data mining issues. An important task of data mining and machine learning is classification, a widely used in classification is support vector machine (SVM) algorithms applicable in many various domains. In this paper, we proposes a privacy-preserving solution for SVM classification. Our workaround constructing a global SVM classification model from vertically partitioned distributed data at multi-parties based on Gram matrix, without revealing a party's data. We proposed an efficient and preserve privacy protocol for SVM classification on vertical partitioned data. Our experimental results, the accuracy of distributed SVM using Gram matrix up to 90% and the privacy not compromised.
At present, with continuously expanding of Chinese credit market, thus large amounts of P2P (person-to-person borrow or lend money in internet Finance) platform were born and have been in development. Most of P2P plat...
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ISBN:
(数字)9783319633121
ISBN:
(纸本)9783319633121;9783319633114
At present, with continuously expanding of Chinese credit market, thus large amounts of P2P (person-to-person borrow or lend money in internet Finance) platform were born and have been in development. Most of P2P platform in China carries out the credit risk evaluation of loan applicant by data mining method. As an emerging data mining tool, the artificial neural network has better classification capability. The improvement of risk assessment capabilities of applicant can effectively reduce the overdue rate of analysis, thus in this paper, a kind of credit risk evaluation model based on the Long Short-Term Memory (LSTM) model is presented. The sample data of overdue and non-overdue credits are provided by Hengxin Investment Consulting Co., Ltd. in Jinan, by which the model is established. After the trial, this model is applied to the aspect of overdue classification of credit evaluation with higher accuracy.
Blockchain is the latest buzzword in the FinTech scene and all companies big and small are vying to launch blockchain enabled products. At the basic technology level Blockchain is a distributedtechnology application....
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ISBN:
(纸本)9781538669129;9781538669112
Blockchain is the latest buzzword in the FinTech scene and all companies big and small are vying to launch blockchain enabled products. At the basic technology level Blockchain is a distributedtechnology application. The challenges of operating such an application are known [1]. But the techniques of developing distributed applications by large enterprise teams, in a typical SDLC lifecycle (Develop, Test, Deploy and Upgrade) is not well known. Without proper methodologies / Formal Tools as is the case with most blockchain systems, bugs slip in easily. Studies on failures point to developers missing low handing bugs as most of the errors are simulated with 3 nodes or less [2]. The developer ecosystem is fast changing with technologies like containers and the emerging Micro Services architectures and Cloud Native computing. The decisions on setup, build, CI/CD, Automated Testing are not taken at the beginning and as pointed out by [3] affect the entire project. The good news is that there are lot of tools available in the Open source domain that addresses the needs. The bad news is that picking the right combination to work in team sizes of 5 or more is not straight forward. This paper details our journey and lessons learnt on setting up Application Development Teams for Rapid Development in Blockchain using multiple blockchain tools like Ethereum and the HyperLedger Fabric. It details both our application architecture and the modifications needed to enable a Cloud Native architecture and the build/ deploy/ testing frameworks that we used.
6Complex Event Processing (CEP) has become the key part of internet of Things (IoT). Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligen...
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6Complex Event Processing (CEP) has become the key part of internet of Things (IoT). Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.
The proceedings contain 26 papers. The special focus in this conference is on Stabilization, Safety, and Security of distributed Systems. The topics include: Marginal games and characterizations of the shapley value i...
ISBN:
(纸本)9789811067525
The proceedings contain 26 papers. The special focus in this conference is on Stabilization, Safety, and Security of distributed Systems. The topics include: Marginal games and characterizations of the shapley value in TU games;computing the shapley value of threshold cardinality matching games;matrix analysis for the shapley value and its inverse problem;the general nucleolus of n-person cooperative games;a cooperative game approach to author ranking in coauthorship networks;a reduced harsanyi power solution for cooperative games with a weight vector;an allocation method of provincial college enrollment plan based on bankruptcy model;edgeworth equilibria of economies and cores in multi-choice NTU games;a game theory approach for deploying medical resources in emergency department;two-phase nonlinear programming models and method for interval-valued multiobjective cooperative games;models and algorithms for least square interval-valued nucleoli of cooperative games with interval-valued payoffs;interval-valued least square prenucleolus of interval-valued cooperative games with fuzzy coalitions;quadratic programming models and method for interval-valued cooperative games with fuzzy coalitions;cooperative games with the intuitionistic fuzzy coalitions and intuitionistic fuzzy characteristic functions;a profit allocation model of employee coalitions based on triangular fuzzy numbers in tacit knowledge sharing;non-cooperative monomino games;bargaining model of mutual deterrence among three players with incomplete information;stakeholders’ behavior analysis and enterprise management strategy selection in Chinese ancient village tourism development;two bargain game models of the second-hand housing commence;some relaxed solutions of minimax inequality for discontinuous game;dynamic games of firm social media disclosure.
Efficient resource allocation is one of the most challenging facet in small cell deployment. With continuous research, many algorithms have been developed in this regard. The proposed algorithm is for small cell downl...
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ISBN:
(纸本)9781467392068
Efficient resource allocation is one of the most challenging facet in small cell deployment. With continuous research, many algorithms have been developed in this regard. The proposed algorithm is for small cell downlink on a large scale with the context of orthogonal frequency division multiple access. The proposed algorithm has 4 stages, one of which also incorporates device-to-device (D2D) communication inside a small cell. The algorithm uses distributed resource allocation for downlink model based on user demand. A simulation environment is developed to study the quantitative effects of proposed algorithm. Poisson random distribution is used to model the user and access point locations. The interference analysis to determine maximum distance of D2D connection within a small cell is also provided. Performance comparisons between fixed resource allocation, partially distributed allocation and the proposed, proportional resource allocation algorithm with and without D2D are also shown. The simulations are carried out in MATLAB 2013.
internet of Things (IoT) is a concept that connects real world physical objects to the internet. Each object is given a unique identity to digitally identify it all across the internet. Each object has sensing and com...
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ISBN:
(纸本)9789380544199
internet of Things (IoT) is a concept that connects real world physical objects to the internet. Each object is given a unique identity to digitally identify it all across the internet. Each object has sensing and communication capabilities by which it collects information and forwards the collected information to the internet. Objects also communicate among themselves to perform a common goal by means of internet protocols. In this paper, an application of IoT that helps in monitoring and maintaining the ambience light of a classroom is discussed.
The proceedings contain 76 papers. The topics discussed include: research on the safety accidents prediction for smart laboratory based on statistical analysis;analyzing elements of letters in a letter management syst...
ISBN:
(纸本)9781509048717
The proceedings contain 76 papers. The topics discussed include: research on the safety accidents prediction for smart laboratory based on statistical analysis;analyzing elements of letters in a letter management system;an XML representation of the octgrid for the rectangular dissections;implementation and comparison of M2M protocols for internet of things;template-based code generation framework for data-driven software development;an intelligent approach to review filtering and review quality improvement;the development of the magnetic measurement system of the movement method using the posture information;development of dragonfly-like flapping robot;and estimation of rates arriving at the winning hands in multi-player games with imperfect information.
Under the rapid development of information technology in todays society, kiosk system has become an indispensable part in many fields. Especially in retail business, retailers use the kiosk system to meet customer dem...
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