2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing最新文献_第10页

Publish/Subscribe Middleware for Resource Discovery in MANET MANET中用于资源发现的发布/订阅中间件

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.39

Malihe Saghian, R. Ravanmehr

引用次数: 7

General Functional Regenerating Codes with Uncoded Repair for Distributed Storage System 分布式存储系统通用无编码修复功能再生码

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.38

Qing Liu, D. Feng, Zhan Shi, Min Fu

引用次数: 3

A QoS Assured Network Service Chaining Algorithm in Network Function Virtualization Architecture 网络功能虚拟化体系结构中一种保证QoS的网络服务链算法

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.135

Taekhee Kim, S. Kim, Kwonyong Lee, Sungyong Park

引用次数: 23

A Multi-objective Biogeography-Based Optimization for Virtual Machine Placement 基于生物地理的多目标虚拟机布局优化

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.25

Q. Zheng, R. Li, Xiuqi Li, Jie Wu

引用次数: 37

Improving Energy Efficiency of Web Servers by Using a Load Distribution Algorithm and Shutting Down Idle Nodes 利用负载分配算法和关闭空闲节点来提高Web服务器的能源效率

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.75

Kai Chen, Jörg Lenhardt, W. Schiffmann

引用次数: 7

An Auto-Scaling Framework for Controlling Enterprise Resources on Clouds 用于控制云上企业资源的自动扩展框架

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.120

Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki

引用次数: 15

PCAH: A PCA-Based Hierarchical Clustering Method for Visual Words Construction PCAH:一种基于pca的视觉词结构分层聚类方法

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.33

Ying He, Jian Wang, Xue-xia Zhong, Lin Mei, Zhi-zong Wu

{"title":"PCAH: A PCA-Based Hierarchical Clustering Method for Visual Words Construction","authors":"Ying He, Jian Wang, Xue-xia Zhong, Lin Mei, Zhi-zong Wu","doi":"10.1109/CCGrid.2015.33","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.33","url":null,"abstract":"Most of the existing methods for generating a visual dictionary SIFT based on local characteristics, and adopt the common K-means clustering method to get the visual dictionary. But when the image vector dimension of the local feature is growing higher, the vector distribution of the local characteristics becomes sparse, resulting in the high correlation distance between the image vectors and reducing the comparability and universality of the visual patterns. According to the above problem, based on the local SIFT features, this paper introduced a Principal Component Analysis Hierarchical clustering method (PCAH) for generating the visual dictionary. This method can effectively ease the feature dimension disaster and obtain better stability. In addition, this method can solve the problem because of high dimension and structure complexity in the feature space of the images efficiently, and can get better performance in generating the visual dictionary. The experiment is executed on the pedestrians dataset Test_dataset1(our own dataset), pos, the scene classification dataset Upright vs Inverted, and the behavior classification dataset Stanford40_JPEGImages. And the datasets are divided into two groups based on the number of the SIFT features (one is less than 300 and the other is more than 5000). We adopt the Silhouette index and the computation time as the evaluation index. The experiment results indicate that comparing with the K-means clustering algorithm, the proposed PCA-based Hierarchical clustering method (PCAH) can reach higher quality visual words. At the same time, the computation speed of the PCAH clustering method is faster.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"102 1","pages":"1009-1018"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75766305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Joint Scheduling of Data and Computation in Geo-Distributed Cloud Systems 地理分布式云系统中数据与计算的联合调度

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.83

Lingyan Yin, Ji-zhou Sun, Laiping Zhao, Chenzhou Cui, Jian Xiao, Ce Yu

{"title":"Joint Scheduling of Data and Computation in Geo-Distributed Cloud Systems","authors":"Lingyan Yin, Ji-zhou Sun, Laiping Zhao, Chenzhou Cui, Jian Xiao, Ce Yu","doi":"10.1109/CCGrid.2015.83","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.83","url":null,"abstract":"Recent trends show that cloud computing is growing to span more and more globally distributed data centers. For geo-distributed data centers, there is an increasing need for scheduling algorithms to place tasks across data centers, by jointly considering data and computation. This scheduling must deal with situations such as wide-area distributed data, data sharing, WAN bandwidth costs and data center capacity limits, while also minimizing completion time. However, this kind of scheduling problems is known to be NP-Hard. In this paper, inspired by real applications in astronomy field, we propose a two-phase scheduling algorithm that addresses these challenges. The mapping phase groups tasks considering the data-sharing relations, and dispatches groups to data centers by way of one-to-one correspondence. The reassigning phase balances the completion time across data centers according to relations between tasks and groups. We utilize the real China-Astronomy-Cloud model and typical applications to evaluate our proposal. Simulations show that our algorithm obtains up to 22% better completion time and effectively reduces the amount of data transfers compared with other similar scheduling algorithms.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"67 1","pages":"657-666"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75833125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Cloud Service Recommendation: State of the Art and Research Challenges 云服务推荐:技术现状和研究挑战

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.144

Lantian Guo, Xianrong Zheng, Chen Ding, Dejun Mu, Zhe Li

引用次数: 11

Assessing Safe Task Parallelism in SPEC 2006 INT 在spec2006 INT中评估安全任务并行性

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.159

Tongxin Bai, C. Ding, Pengcheng Li

引用次数: 1