With the constant improvement of Chinese economic development level, there have been constantly increasing researches on artificial intelligence and database field and the application of data mining in each field has ...
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With the constant improvement of Chinese economic development level, there have been constantly increasing researches on artificial intelligence and database field and the application of data mining in each field has been increasingly wide. However, with the increase of information quantity and data size, such information makes it more difficult to discover effective knowledge while helping the work and production of people. A lot of information is arranged in the specified equipment. However, mode and isomerism are more complicated and network noise increases. To process such data more effectively, cloud computing method can be used to handle problems that cannot be solved by traditional distributed computation method.
The study provides insights into the perceived risk in the course of farmers39; agriculture information adoption in China. The information perceived risk model is gotten with the approach of the factor analysis and ...
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ISBN:
(纸本)9783319483542;9783319483535
The study provides insights into the perceived risk in the course of farmers' agriculture information adoption in China. The information perceived risk model is gotten with the approach of the factor analysis and six aspects constitute the model. The regression equation of farmers' information perceived risk is obtained with the multiple regression analysis in this research. The results show that there are many aspects that farmers consider about when they are applied with new agricultural information and technologies, and information service departments may pay more attention to those especially.
In this paper, we present an approach to building cloud bursting architecture based on the peer-to-peer infrastructure for managing services. Proposed approach is designed to address various issues of interconnecting ...
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ISBN:
(纸本)9781467381031
In this paper, we present an approach to building cloud bursting architecture based on the peer-to-peer infrastructure for managing services. Proposed approach is designed to address various issues of interconnecting several clouds, problems of resource provisioning, service deployment and provisioning in the hybrid cloud. To ensure robustness of our system we use peer-to-peer overlay, which was proposed by us in previous papers. Scalability of the approach is attained due to flexibility of service discovery mechanism, decentralized architecture and modular approach, which allows to leverage existing components. We argue that our approach present viable solution for managing abrupt peaks in the load and keeping service provider's QoS and SLA requirements on the desired level.
The problem of efficient querying large amount of linked data using Map-Reduce is investigated in this paper. The proposed approach is based on the following assumptions: a) Data graphs are arbitrarily partitioned in ...
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ISBN:
(纸本)9781467381031
The problem of efficient querying large amount of linked data using Map-Reduce is investigated in this paper. The proposed approach is based on the following assumptions: a) Data graphs are arbitrarily partitioned in the distributed file system is such a way that replication of data triples between the data segments is allowed. b) Data triples are replicated is such a way that answers to a special form of queries, called subject-object star queries, can be obtained from a single data segment. c) Each query posed by the user, can be transformed into a set of subject-object star subqueries. We propose a one and a half phase, scalable, Map-Reduce algorithm that efficiently computes the answers of the initial query by computing and appropriately combining the subquery answers. We prove that, under certain conditions, query can be answered in a single map-reduce phase.
Computational Grids are high performance computing systems used to solve large scale computational demands. Because scheduling workflow applications in a distributed environment is a NP-Complete problem, meta heuristi...
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ISBN:
(纸本)9781467381031
Computational Grids are high performance computing systems used to solve large scale computational demands. Because scheduling workflow applications in a distributed environment is a NP-Complete problem, meta heuristics are introduced to solve this issue. In this paper, we propose an Energy-Aware algorithm based on Discrete Particle Swarm Optimization (DPSO) called EA-DPSO. Our aim is to minimize the makespan (i.e., overall completion time) of all the tasks within the workflow while optimizing energy consumption. The experimental results show that energy consumption is optimized, while the scheduling in terms of completion time is maintained.
Cloud technology is moving towards more distribution across multi-clouds and the inclusion of various devices, as evident through IoT and network integration in the context of edge cloud and fog computing. Generally, ...
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ISBN:
(纸本)9781467381031
Cloud technology is moving towards more distribution across multi-clouds and the inclusion of various devices, as evident through IoT and network integration in the context of edge cloud and fog computing. Generally, lightweight virtualisation solutions are beneficial for this architectural setting with smaller, but still virtualised devices to host application and platform services, and the logistics required to manage this. Containerisation is currently discussed as a lightweight virtualisation solution. In addition to having benefits over traditional virtual machines in the cloud in terms of size and flexibility, containers are specifically relevant for platform concerns typically dealt with Platform-as-a-Service (PaaS) clouds such as application packaging and orchestration. For the edge cloud environment, application and service orchestration can help to manage and orchestrate applications through containers as an application packaging mechanism. We review edge cloud requirements and discuss the suitability container and cluster technology of that arise from having to facilitate applications through distributed multi-cloud platforms build from a range of networked nodes ranging from data centres to small devices, which we refer to here as edge cloud.
internet of Things (IoT) devices used in mining, agriculture, and environmental sensing often require Disruption Tolerant Networking (DTN) support, since end-to-end network connectivity may not always available in dis...
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internet of Things (IoT) devices used in mining, agriculture, and environmental sensing often require Disruption Tolerant Networking (DTN) support, since end-to-end network connectivity may not always available in distributed and sparsely populated locations. Data mules such as workers or vehicles, which pass through the monitored area periodically, bridge the gap between disconnected networks. Since data dissemination often involves multiple users, and configuration updates from the Monitoring and Control Center needs to be delivered reliably to all participating IoT devices, the combination of efficient Reliable Multicast algorithms with DTN should address this problem effectively. This paper examines the current status of DTN support for multicast from different design aspect of routing protocols and summarizes some of the open issues related to the design of Reliable Multicast DTN (RMDTN) protocols for IoT.
To help people make choices and take decisions is an important function of recommender system. Reviews and comments that are written online by users after watching movies, reading books, listening to music or purchasi...
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ISBN:
(纸本)9781467394178
To help people make choices and take decisions is an important function of recommender system. Reviews and comments that are written online by users after watching movies, reading books, listening to music or purchasing a specific item, are important sources of user generated data, which can be utilized for decision making using recommendations given to user by the recommender system. When the available data in one domain is sparse, data (content and ratings) from other domains can be used to make cross domain recommendations. In this paper we have used this content information as well as ratings of both domains where there is no user-item overlap between the given domains for cross domain recommendations. User generated content (reviews and comments) crawled from web requires topic modeling to discover the latent thematic structure in the corpora of both domains. Since the topics in both domains are dissimilar, we have compared various approaches based on semantic space of corpus and knowledge based methods for finding cross domain recommendations. Experimental results show improvement in precision in recommendations over existing approach based on semantic clustering.
Edgecomputing and Fog computing are new paradigms where data processing is executed in or on the edge of networks to mitigate cloud server load. However, Edgecomputing and Fog computing still need powerful servers on ...
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Edgecomputing and Fog computing are new paradigms where data processing is executed in or on the edge of networks to mitigate cloud server load. However, Edgecomputing and Fog computing still need powerful servers on the edge of networks which impose additional costs for deployments. We proposed a platform called IFoT (Information Flow of Things) that efficiently performs distributed processing as well as distribution and analysis of data streams near their sources based on "Process On Our Own (PO3)" concept. In IFoT, processing of tasks for cloud servers is delegated to an ad-hoc distributed system consisting of proximity IoT devices for distributed real-time stream processing. In this demonstration, we show a face recognition system for person tracking developed on top of IFoT middleware which locally processes video streams in real-time and in a distributed manner by using computational resources of IoT devices.
Opportunistic Mobile Networks (OMN) interpret the social characteristics of human beings for message routing in hostile environment or rural areas. The concept of cyber foraging provides mobile nodes the ability to of...
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ISBN:
(纸本)9781479985807
Opportunistic Mobile Networks (OMN) interpret the social characteristics of human beings for message routing in hostile environment or rural areas. The concept of cyber foraging provides mobile nodes the ability to offload the computationally intensive tasks to the nearest data center or cloudlets instead of offloading the requests to Wide Area Networks (WAN). The cloudlets are the major components of the cyber foraging environment. The cloudlets have mobile as well as fixed states. Most opportunistic mobile networks rely on the participating nodes for the purpose of providing security. This makes the security model heterogeneous and computationally more intensive for the nodes. The goal is to have a greater level of security while decreasing the power consumption of the nodes at the same time. This work proposes a Secured Opportunistic Mobile Network (SecOMN) which uses cloudlets to address the issues of intensive computation and security. We assume the scenario in which the cloudlets are in hostile environments and as such have very limited internet connectivity. The goal of increased level of security is met by the introduction of a hybrid encryption algorithm that combines both symmetric and asymmetric key encryption systems in an intuitive manner. The system also takes care of the integrity and authenticity of the transmitted packets. It is found that the proposed model is successfully able to reduce the computations performed at the nodes by a large extent. Further, the concept of cyber foraging enables the implementation of a more complex security model which has been analyzed to be significantly secure against all known attacks.
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