2014 IEEE 7th International Conference on Cloud Computing最新文献_第6页

Enabling Performance as a Service for a Cloud Storage System 开启云存储性能即服务

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.80

Yang Li, Li Guo, A. Supratak, Yike Guo

引用次数: 7

Keeping Your API Keys in a Safe 将您的API密钥保存在保险箱中

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.143

Hongqian Karen Lu

{"title":"Keeping Your API Keys in a Safe","authors":"Hongqian Karen Lu","doi":"10.1109/CLOUD.2014.143","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.143","url":null,"abstract":"Cloud API (Application Programming Interface) enables client applications to access services and manage resources hosted in the Cloud. To protect themselves and their customers, Cloud service providers (CSP) often require client authentication for each API call. The authentication usually depends on some kind of secret (or called API key), for example, secret access key, password, or access token. As such, the API key unlocks the door to the treasure inside the Cloud. Hence, protecting these keys is critical. It is a difficult task especially on the client side, such as users' computers or mobile devices. How do CSPs authenticate client applications? What are security risks of managing API keys in common practices? How can we mitigate these risks? This paper focuses on finding answers to these questions. By reviewing popular client authentication methods that CSPs use and using Cloud APIs as software developers, we identified various security risks associated with API keys. To mitigate these risks, we use hardware secure elements for secure key provisioning, storage, and usage. The solution replaces the manual key handling with end-to-end security between CSP and its customers' secure elements. This removes the root causes of the identified risks and enhances API security. It also enhances the usability by eliminating manual key operations and alleviating software developers' worries of working with cryptography.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133710301","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: 7

Palantir: Reseizing Network Proximity in Large-Scale Distributed Computing Frameworks Using SDN Palantir:在使用SDN的大规模分布式计算框架中重新获取网络邻近性

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.66

Ze Yu, Min Li, Xin Yang, Xiaolin Li

引用次数: 10

Speculative Execution for a Single Job in a MapReduce-Like System 类mapreduce系统中单个作业的推测执行

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.84

Huanle Xu, W. Lau

{"title":"Speculative Execution for a Single Job in a MapReduce-Like System","authors":"Huanle Xu, W. Lau","doi":"10.1109/CLOUD.2014.84","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.84","url":null,"abstract":"Parallel processing plays an important role for large-scale data analytics. It breaks a job into many small tasks which run parallel on multiple machines such as MapReduce framework. One fundamental challenge faced to such parallel processing is the straggling tasks as they can delay the completion of a job seriously. In this paper, we focus on the speculative execution issue which is used to deal with the straggling problem in the literature. We present a theoretical framework for the optimization of a single job which differs a lot from the previous heuristics-based work. More precisely, we propose two schemes when the number of parallel tasks the job consists of is smaller than cluster size. In the first scheme, no monitoring is needed and we can provide the job deadline guarantee with a high probability while achieve the optimal resource consumption level. The second scheme needs to monitor the task progress and makes the optimal number of duplicates when the straggling problem happens. On the other hand, when the number of tasks in a job is larger than the cluster size, we propose an Enhanced Speculative Execution (ESE) algorithm to make the optimal decision whenever a machine is available for a new scheduling. The simulation results show the ESE algorithm can reduce the job flow time by 50% while consume fewer resources comparing to the strategy without backup.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"412 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132343429","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: 17

Bridging the Virtualization Performance Gap for HPC Using SR-IOV for InfiniBand 利用SR-IOV为ib搭建高性能计算的虚拟化性能鸿沟

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.89

Malek Musleh, Vijay S. Pai, J. Walters, A. Younge, S. Crago

引用次数: 22

A Software Product Line Approach for Configuring Cloud Robotics Applications 配置云机器人应用的软件产品线方法

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.104

Luca Gherardi, D. Hunziker, Mohanarajah Gajamohan

引用次数: 21

Core-Selecting Auctions for Dynamically Allocating Heterogeneous VMs in Cloud Computing 云计算中动态分配异构虚拟机的选核拍卖

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.30

Haoming Fu, Zongpeng Li, Chuan Wu, Xiaowen Chu

引用次数: 34

Data Farming on Heterogeneous Clouds 异构云上的数据耕种

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.120

Dariusz Król, R. Słota, J. Kitowski, L. Dutka, Jakub Liput

引用次数: 9

PowerCass: Energy Efficient, Consistent Hashing Based Storage for Micro Clouds Based Infrastructure PowerCass:基于微云基础设施的节能、一致的哈希存储

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.17

Frezewd Lemma Tena, Thomas Knauth, C. Fetzer

引用次数: 8

Time-Constrained Live VM Migration in Share-Nothing IaaS-Clouds 无共享iaas - cloud中的限时热迁移

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.18

Konstantinos Tsakalozos, Vasilis Verroios, M. Roussopoulos, A. Delis

引用次数: 16