Using internet of things (IoT), we can connect and enable every object to send or receive data through the internet. When it comes to real life applications we can make use of this technology for easy communication th...
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In distributed database systems, replication is the most widely used approach to offering high data availability, increased fault tolerance, and improved scalability of the overall system. However, the primary concern...
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In distributed database systems, replication is the most widely used approach to offering high data availability, increased fault tolerance, and improved scalability of the overall system. However, the primary concern with this technique is not only to provide high availability and reliability but also to boost the performance of data replication, i.e. to minimize response time and maximize throughput. We propose an analytical model for asynchronous replication technique ( ART) by copying the data and replicating it to remote sites on a continuous basis. A remote copy of the data is created at a subsequent time after the primary copy is updated. The model is based on the M/G/1 queuing system by taking into account intersite communication between sites in the systems.
This article presents a new methodology using distributed algorithms to identify and prevent errors in production and service. A sequential production/service line is selected to challenge the analysis, and reveal if ...
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This article presents a new methodology using distributed algorithms to identify and prevent errors in production and service. A sequential production/service line is selected to challenge the analysis, and reveal if the distributed algorithms can outperform centralized algorithms in automating error prevention. Agent-based error prevention algorithms (AEPAs) are developed for distributed agents to identify and prevent errors with decision rules. Analytical studies and simulation experiments are conducted to compare AEPAs with traditional centralized error prediction and detection algorithms. The results show that the AEPAs employing nominal and optimistic rules perform better than the centralized algorithms in terms of preventability and reliability. Collaboration among agents improves AEPAs' performance. It is recommended to prevent errors by two agents simultaneously executing the AEPA employing the integrated nominal rule. (C) 2011 Elsevier Ltd. All rights reserved.
With the rapid development of E-business systems, the technology of distributed services and security becomes research focus in the field of Internet based applications. The distributed E-business application platform...
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With the development of flash memory, its storage density has gradually increased, but its reliability has been greatly reduced. Now, flash memory relies on LDPC to solve this problem. Although LDPC (Low Density Parit...
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The success of machine learning and deep learning depends on the large amount of for training. Data acquisition is an indispensable event for data science. In this paper, we study a scenario where a data broker wantes...
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ISBN:
(纸本)9781728143286
The success of machine learning and deep learning depends on the large amount of for training. Data acquisition is an indispensable event for data science. In this paper, we study a scenario where a data broker wantes to buy private data from a population to estimate some statistics and resell the results to the data users in order to obtain profits. It's necessary to compensate owners of private data for their loss of privacy. In our setting, we assume that sellers are selfish agents who would like to maximize his or her utilities, thus we need to design truthful mechanisms. In our work, we will study a more generalized optimization goal for budget free crowdsoucer, profit maximization. The utility of the buyer is a function of the accuracy of the expected statistic. We will use a Profit-Extract algorithm for the auction, and a Laplace mechanism will be used for privacy protection. Our proposed designed mechanism has properties of individual rationality, truthfulness, computational efficiency and also has a performance lowerbound. Furthermore, we will design an online auction for our setting.
Non-dedicated loosely coupled systems are popular platforms for cluster- and grid-based parallel processing, fundamentally because they have good cost-performance ratios and are scalable. However, these platforms repr...
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Non-dedicated loosely coupled systems are popular platforms for cluster- and grid-based parallel processing, fundamentally because they have good cost-performance ratios and are scalable. However, these platforms represent highly dynamic environments in which performance and efficiency can be seriously impacted by changes in environmental conditions. This is especially significant where the runtime configuration has been determined statically, either at compilation time or at the start of execution. This paper introduces the concept of agile parallel processing in which the application manages several aspects of its own run-time behaviour, including deployment granularity. This approach reduces the emphasis on the preconfiguration of components, and relies instead on inbuilt learning and discovery capabilities. To facilitate investigation into the extent to which a self-managing approach can be beneficial to parallel processing, an experimental framework has been developed. The framework provides a range of services such as dynamic worker discovery and performance calibration, and policy-controlled facilities such as resource management and adaptation to suit environmental conditions. The framework integrates these services with the parallel application code. The operation and performance of policy-based dynamic deployment scheduling in dynamic environments is analysed in detail.
With technological advancements in computing and communications, huge amounts of big data are generated and collected at a very rapid rate from a wide variety of rich data sources. Embedded in these big data are usefu...
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ISBN:
(纸本)9781665414852
With technological advancements in computing and communications, huge amounts of big data are generated and collected at a very rapid rate from a wide variety of rich data sources. Embedded in these big data are useful information and valuable knowledge. An example is healthcare and epidemiological data such as data related to patients who suffered from viral diseases like the coronavirus disease 2019 (COVID-19). Knowledge discovered from these epidemiological data via data science helps researchers, epidemiologists and policy makers to get a better understanding of the disease, which may inspire them to come up ways to detect, control and combat the disease. In this paper, we present a temporal data science algorithm for analyzing big COVID-19 epidemiological data, with focus on the temporal data analytics with ubiquitous computing. The algorithm helps users to get a better understanding of information about the confirmed cases of COVID-19. Evaluation results show the benefits of our system in temporal data analytics of big COVID-19 data with ubiquitous computing. Although the algorithm is designed for temporal data analytics of big epidemiological data, it would be applicable to other temporal data analytics of big data in many real-life applications and services.
In mobile ad hoc networks (MANETs), a single certificate authority (CA) node could be a security bottleneck. Multiple replica of CA is fault tolerant, but the network is as vulnerable as single CA or even worse since ...
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ISBN:
(纸本)9780769534947
In mobile ad hoc networks (MANETs), a single certificate authority (CA) node could be a security bottleneck. Multiple replica of CA is fault tolerant, but the network is as vulnerable as single CA or even worse since breaking one of the CAs means breaking all of them. Many distributed CA models based on the secret sharing scheme are proposed. In this paper, the suitable construction of the distributed CA is discussed based on the optimization theory. By the analyzing of the characters of the distributed CA in MANETS and the processes of the secure services provided, the optimization model is built. The mean response time of the applications is the optimization goal and the service success probability, system security probability and the loss probability of applications are the constraints in the optimization model. A classic resolving process of the optimization model is given, which is instructional for designing the construction of distributed CA applied in MANETs.
Orienting to the competitive exploration of marine resources and the ship intelligent navigation, the broadband and stable maritime communications has regarded as a matter of concern. Due to the particularity of the o...
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ISBN:
(纸本)9781665414852
Orienting to the competitive exploration of marine resources and the ship intelligent navigation, the broadband and stable maritime communications has regarded as a matter of concern. Due to the particularity of the ocean environment, the maritime communication network is severely restricted compared to the terrestrial one. By understanding the requirement of maritime business, this article deepens the research on maritime communications at offshore areas and ocean and makes a summary of the urgent problems and mainstream communication technologies. Besides, an experimental type of maritime network paradigm based on the coast-5G network involving virtual MIMO technology is present, with a view to providing open issues for the offshore maritime broadband communications.
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