The proceedings contain 99 papers. The topics discussed include: energy-conscious cloudcomputing adopting DVFS and state-switching for workflow applications;smart intermediate data transfer for MapReduce on cloud com...
ISBN:
(纸本)9781479928293
The proceedings contain 99 papers. The topics discussed include: energy-conscious cloudcomputing adopting DVFS and state-switching for workflow applications;smart intermediate data transfer for MapReduce on cloudcomputing;a generic, scalable and fine-grained data access system for sharing digital objects in honest but curious cloud environments;failover pattern with a self-healing mechanism for high availability cloud solutions;a novel parallel architecture with fault-tolerance for joining bi-directional data streams in cloud;modeling energy savings in volunteers clouds;a novel architecture for self-propagating malicious software within cloud infrastructures;migrating existing applications to the cloud;and latency-aware dynamic voltage and frequency scaling on many-core architectures for data-intensive applications.
The proceedings contain 29 papers. The special focus in this conference is on cloud Architecture, Applications, bigdata and Social Network. The topics include: An effective approach to isolating performance bottlenec...
ISBN:
(纸本)9783319284293
The proceedings contain 29 papers. The special focus in this conference is on cloud Architecture, Applications, bigdata and Social Network. The topics include: An effective approach to isolating performance bottleneck during slow data delivery;schedule compaction and deadline constrained dag scheduling for IAAS cloud;synthesizing realistic cloud workload traces for studying dynamic resource system management;energy-efficient VM placement algorithms for clouddata center;a new analytics model for large scale multidimensional data visualization;an architecture-based autonomous engine for services configuration and deployment in hybrid clouds;dynamic load sharing to maximize resource utilization within cloud federation;real-time task scheduling algorithm for cloudcomputing based on particle swarm optimization;making GPU warp scheduler and memory scheduler synchronization-aware;a novel grid based k-means cluster method for traffic zone division;color image fusion researching based on S-PCNN and laplacian pyramid;rationalizing the parameters of k-nearest neighbor classification algorithm;analyzing and predicting failure in hadoop clusters using distributed hidden Markov model;emerging pragmatic patterns in large-scale RDF data;cross-correlation as tool to determine the similarity of series of measurements for big-data analysis tasks;the key technologies of real-time processing large scale microblog data stream;an efficient index method for multi-dimensional query in cloud environment;keyword search over encrypted data in cloudcomputing from lattices in the standard model and research of terminal transparent encryption storage mechanism for multi-cloud disks.
This paper firstly sums up the main security threats to data confidentiality in cloudcomputing environment, then classifies and introduces the existing access control models according to the core strategy they have a...
详细信息
ISBN:
(纸本)9781479928293
This paper firstly sums up the main security threats to data confidentiality in cloudcomputing environment, then classifies and introduces the existing access control models according to the core strategy they have adopted. Lastly this paper points out the main challenges facing access control in cloudcomputing environment and the subsequent research directions.
cloudcomputing can provide Virtual Machine (VM) computing resources to meet the growing computational demands. Efficient and flexible resource management is a critical issue in cloudcomputing context. We present a s...
详细信息
ISBN:
(纸本)9781479928293
cloudcomputing can provide Virtual Machine (VM) computing resources to meet the growing computational demands. Efficient and flexible resource management is a critical issue in cloudcomputing context. We present a scheduling study on OpenStack VMs scheduler using cloudSim. We focus it on from a more practical viewpoint, the simulation experiments indicate that each of the different scheduling policies suited to different applications in cloudcomputing.
A production tracking and scheduling system was developed based on a cloudcomputing-based system architecture. cloud and radio frequency identification technologies were integrated to implement remote production data...
详细信息
ISBN:
(纸本)9781479928293
A production tracking and scheduling system was developed based on a cloudcomputing-based system architecture. cloud and radio frequency identification technologies were integrated to implement remote production data capture and tracking, and intelligent optimization techniques are adopted to provide effective production scheduling solutions. A prototype system was developed to implement the remote production tracking and scheduling functions in a distributed manufacturing environment. The effectiveness of the system was validated by improved production efficiency and reduced production waste and costs.
Tasks scheduling problem in cloudcomputing is NP-hard, and it is difficult to attain an optimal solution, so we can use intelligent optimization algorithms to approximate the optimal solution, such as ant colony opti...
详细信息
ISBN:
(纸本)9781479928293
Tasks scheduling problem in cloudcomputing is NP-hard, and it is difficult to attain an optimal solution, so we can use intelligent optimization algorithms to approximate the optimal solution, such as ant colony optimization algorithm. In order to solve the task scheduling problem in cloudcomputing, a period ACO_based scheduling algorithm (PACO) has been proposed in this paper. PACO uses ant colony optimization algorithm in cloudcomputing, with the first proposed scheduling period strategy and the improvement of pheromone intensity update strategy. The experiments results show that, PACO has a good performance both in makespan and load balance of the whole cloud cluster.
MapReduce is a programming model proposed by Google to process large datasets in clusters. However, MapReduce often needs to transfer much intermediate data among nodes, which is harmful to performances of an applicat...
详细信息
ISBN:
(纸本)9781479928293
MapReduce is a programming model proposed by Google to process large datasets in clusters. However, MapReduce often needs to transfer much intermediate data among nodes, which is harmful to performances of an application. MapReduce can be enhanced by using the proposed Smart Intermediate data Transfer (SIDT) in the runtime system to smartly arrange intermediate data. Although SIDT does not reduce intermediate data to the minimal size in comparison with other intermediate data arrangement procedures such as Huffman coding, bzip2, and gzip, MapReduce is proved to get a better performance from SIDT than from others in the experiments of this paper.
Reducing energy consumption without scarifying service quality is important for cloudcomputing. Efficient scheduling algorithms HEFT-D and HEFT-DS based on frequency-scaling and state-switching techniques are propose...
详细信息
ISBN:
(纸本)9781479928293
Reducing energy consumption without scarifying service quality is important for cloudcomputing. Efficient scheduling algorithms HEFT-D and HEFT-DS based on frequency-scaling and state-switching techniques are proposed. Our scheduling algorithms use the fact that the hosts employing a lower frequency or entering a sleeping state may consume less energy without leading to a longer makespan. Experimental results have shown that our algorithms maintain the performance as good as that of HEFT while the energy consumption is reduced.
A new cloud-based Trust Awareness and Interaction Model (CTAIM) is proposed for trust evaluation based content filtering in social interactive data. The research is based on diversified information from social interac...
详细信息
ISBN:
(纸本)9781479928293
A new cloud-based Trust Awareness and Interaction Model (CTAIM) is proposed for trust evaluation based content filtering in social interactive data. The research is based on diversified information from social interactive data to analyse people's intention and evaluate people's trust. The proposed model is composed of Bayesian content filtering algorithm and Bayesian inference algorithm in Dirichlet distribution, and it's capable to provide 3rd party trustworthiness evaluation according to node behavior and interaction history with high-efficiency, security, and neutrality. Additionally, MapReduce-based computing and HBase storage framework are implemented for parallel computing among mass interactive data.
暂无评论