Artificial intelligence has become the core driving force of a new round of industrial innovation around the world and a strategic technology that leads future development. The application of artificial intelligence t...
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There has been increasing need for secure data sharing. In practice a group of data owners often adopt a heterogeneous security scheme under which each pair of parties decide their own protocol to share data with dive...
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ISBN:
(纸本)9781450367356
There has been increasing need for secure data sharing. In practice a group of data owners often adopt a heterogeneous security scheme under which each pair of parties decide their own protocol to share data with diverse levels of trust. The scheme also keeps track of how the data is used. This paper studies distributed SQL query answering in the heterogeneous security setting. We define query plans by incorporating toll functions determined by data sharing agreements and reflected in the use of various security facilities. We formalize query answering as a bi-criteria optimization problem, to minimize both data sharing toll and parallel query evaluation cost. We show that this problem is PSPACE-hard for SQL and Sigma(p)(3)-hard for SPC, and it is in NEXPTIME. Despite the hardness, we develop a set of approximate algorithms to generate distributed query plans that minimize data sharing toll and reduce parallel evaluation cost. Using real-life and synthetic data, we empirically verify the effectiveness, scalability and efficiency of our algorithms.
Smart grids facilitate the use of distributed and renewable resources on the supply side and providing consumers with a range of tailored services on the consumption side. The introduction of energy smart grid in Mala...
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The industry and academia have proposed many distributed graph processing systems. However, the existing systems are not friendly enough for users like data analysts and algorithm engineers. On the one hand, the progr...
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ISBN:
(纸本)9781665408790
The industry and academia have proposed many distributed graph processing systems. However, the existing systems are not friendly enough for users like data analysts and algorithm engineers. On the one hand, the programming models and interfaces differ a lot in the existing systems, leading to high learning costs and program migration costs. On the other hand, these graph processing systems are tightly bound to the underlying distributedcomputing platforms, requiring users to be familiar with distributedcomputing. To improve the usability of distributed graph processing, we propose a unified distributed graph programming framework UniGPS. Firstly, we propose a unified cross-platform graph programming model VCProg for UniGPS. VCProg hides details of distributedcomputing from users. It is compatible with the popular graph programming models Pregel, GAS, and Push-Pull. VCProg-based programs can be executed by compatible distributed graph processing systems without modification, reducing the learning overheads of users. Secondly, UniGPS supports Python as the programming language. We propose an interprocess-communication-based execution environment isolation mechanism to enable Java/C++-based graph processing systems to call user-defined methods written in Python. The experimental results show that UniGPS enables users to process big graphs beyond the memory capacity of a single machine without sacrificing usability. UniGPS shows near-linear data scalability and machine scalability.
Recently, interest in the spread of the culture of sharing has been increasing at a social level due to the deepening income polarization, poverty, and the rapid growth of civil society and the importance of public in...
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ISBN:
(纸本)9781665418430;9781665448260
Recently, interest in the spread of the culture of sharing has been increasing at a social level due to the deepening income polarization, poverty, and the rapid growth of civil society and the importance of public interest activities of private organizations. In 2016, the National Statistical Office conducted a survey on changes in donation attitudes and recognition of donations, items that took up a large part in the area for the spread of the overall donation culture were the convenience of donation methods and the enhancement of transparency of donation organizations. The existing donation system is a way for donors to donate directly to several donor organizations. However, this method has its disadvantage: it is difficult for donors to see how their donations are spent. To address the convenience of such donation methods, based on the platform that is the core of the fourth industrial era, it enables unrestricted interaction in the network environment such as mobile or PC, inducing open participation in talent donation to the general public. Blockchain is a data forgery/modulation prevention technology based on distributedcomputing technology. Because the block chain records continuously changing data on all participating nodes, it is impossible to arbitrarily manipulate the data by the operators of distributed nodes. Blockchain technology is in the spotlight because it can secure transparency in transactions. In this paper, to solve these problems, we try to introduce the block chain technology into the donation system.
Some graph analyses, such as social network and biological network, need large-scale graph construction and maintenance over distributed memory space. distributed data-streaming tools, including MapReduce and Spark, r...
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ISBN:
(纸本)9781728162515
Some graph analyses, such as social network and biological network, need large-scale graph construction and maintenance over distributed memory space. distributed data-streaming tools, including MapReduce and Spark, restrict some computational freedom of incremental graph modification and run-time graph visualization. Instead, we take an agent-based approach. We construct a graph from a scientific dataset in CSV, tab, and XML formats;dispatch many reactive agents on it;and analyze the graph in the form of their collective group behavior: propagation, flocking, and collision. The key to success is how to automate the run-time construction and visualization of agent-navigable graphs mapped over distributed memory. We implemented this distributed graph-computing support in the multi-agent spatial simulation (MASS) library, coupled with the Cytoscape graph visualization software. This paper presents the MASS implementation techniques and demonstrates its execution performance in comparison to MapReduce and Spark, using two benchmark programs: (1) an incremental construction of a complete graph and (2) a KD tree construction.
Size databases have constantly increased from advances in technology and the Internet, so processing this vast amount of information has been a great challenge. The neural network Extreme Learning Machine (ELM) have b...
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ISBN:
(纸本)9781665456753
Size databases have constantly increased from advances in technology and the Internet, so processing this vast amount of information has been a great challenge. The neural network Extreme Learning Machine (ELM) have been widely accepted in the scientific community due to their simplicity and good generalization capacity. This model consists of randomly assigning the weights of the hidden layer, and analytically calculating the weights of the output layer through the Moore- Penrose generalized inverse. High-Performance computing has emerged as an excellent alternative for tackling problems involving large-scale databases and reducing processing times. The use of parallelcomputing tools in Extreme Learning Machines and their variants, especially the Online Sequential Extreme Learning Machine (OS-ELM), has proven to be a good alternative to tackle regression and classification problems with largescale databases. In this paper, we present a parallel training methodology consisting of several Online Sequential Extreme Learning Machines running on different cores of the Central Processing Unit, with a balanced fingerprint database having 2,000,000 samples distributed in five classes. The results show that training and validation times decrease as the number of processes increases since the number of samples to train in each process decreases. In addition, by having several Online Sequential Extreme Learning Machines trained, new samples can beclassified on any of them.
Internet of Things (IoT) has attracted the attention of researchers from both industry and academia. Smart city, as one of the IoT applications, includes several sub-applications, such as intelligent transportation sy...
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ISBN:
(纸本)9783030389611;9783030389604
Internet of Things (IoT) has attracted the attention of researchers from both industry and academia. Smart city, as one of the IoT applications, includes several sub-applications, such as intelligent transportation system (ITS), smart car parking and smart grid. Focusing on traffic flow management and car parking systems because of their correlation, this paper aims to provide a framework solution to both systems using online detection and prediction based on fog computing. Online event detection plays a vital role in traffic flow management, as circumstances, such as social events and congestion resulting from accidents and roadworks, affect traffic flow and parking availability. We developed an online prediction model using an incremental decision tree and distributed the prediction process on fog nodes at each intersection traffic light responsible for a connecting road. It effectively reduces the load on the communication network, as the data is processed, and the decision is made locally, with low storage requirements. The spatially correlated fog nodes can communicate if necessary to take action for an emergency. The experiments were conducted using the Melbourne city open data.
Graph Analytics is important in different domains: social networks, computer networks, and computational biology to name a few. This paper describes the challenges involved in programming the underlying graph algorith...
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ISBN:
(纸本)9783030369873;9783030369866
Graph Analytics is important in different domains: social networks, computer networks, and computational biology to name a few. This paper describes the challenges involved in programming the underlying graph algorithms for graph analytics for distributed systems with CPU, GPU, and multi-GPU machines and how to deal with them. It emphasizes how language abstractions and good compilation can ease programming graph analytics on such platforms without sacrificing implementation efficiency.
Energy theft is an old and multifaceted phenomenon affecting our society on a global scale from both an operational as well as from a monetary perspective. The relatively recent decentralisation of the grid infrastruc...
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