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نتیجه جستجو - چند ابری

تعداد مقالات یافته شده: 4
ردیف عنوان نوع
1 Optimized Big Data Management across Multi-Cloud Data Centers: Software-Defined Network-Based Analysis
مدیریت داده های بزرگ بهینه شده در سراسر مراکز داده چند ابری: تحلیل مبتنی بر شبکه نرم افزار تعریف شده-2018
With an exponential increase in smart device users, there is an increase in the bulk amount of data generation from various smart devices, which varies with respect to all the essential Vs used to categorize it as big data. Generally, most service providers, including Google, Amazon, Microsoft and so on, have deployed a large number of geographically distributed data centers to process this huge amount of data generated from various smart devices so that users can get quick response time. For this purpose, Hadoop, and SPARK are widely used by these service providers for processing large datasets. However, less emphasis has been given on the underlying infrastructure (the network through which data flows), which is one of the most important components for successful implementation of any designed solution in this environment. In the worst case, due to heavy network traffic with respect to data migrations across different data centers, the underlying network infrastructure may not be able to transfer data packets from source to destination, resulting in performance degradation. Focusing on all these issues, in this article, we propose a novel SDN-based big data management approach with respect to the optimized network resource consumption such as network bandwidth and data storage units. We analyze various components at both the data and control planes that can enhance the optimized big data analytics across multiple cloud data centers. For example, we analyze the performance of the proposed solution using Bloom-filter-based insertion and deletion of an element in the flow table maintained at the OpenFlow controller, which makes most of the decisions for network traffic classification using the rule-and-action-based mechanism. Using the proposed solution, developers can deploy and analyze real-time traffic behavior for the future big data applications in MCE.
Keywords: Big Data,cloud computing, computer centres, software defined networking, telecommunication traffic
مقاله انگلیسی
2 SHAMC: A Secure and highly available database system in multi-cloud environment
SHAMC: سیستم پایگاه داده امن و قابل دسترس در محیط چند ابری-2017
Data owners outsource their databases into the cloud to enjoy the quality services provided by the cloud service providers. However, using cloud database makes the private data vulnerable and exposed to the attackers including malicious insiders. Many researchers try to find the way to encrypt the cloud database and execute queries securely on the ciphertext. In this paper, we propose a secure and highly available cloud database system in the multi-cloud named SHAMC. Specifically, we use the idea of secure multiparty computation and homomorphic encryption to store data and execute queries direct on the ciphertext. Besides, the entire database is stored in multiple clouds to avoid service interruption as well as solve the problems of permanent failure and vendor lock-in. We implement the prototype of SHAMC which supports all queries in TPC BenchmarkTM H (TPC-H) on the top of the commercial cloud. SHAMC is proved to be highly available and cost-efficient. The evaluation shows it has an acceptable query overhead which is superior to other encrypted cloud databases.
Keywords: Database security | Cloud availability | Homomorphic encryption | Multi-party computation | Implementation
مقاله انگلیسی
3 Secure Model Based on Multi-cloud for Big Data Storage and Query
مدل مبتنی بر امنیت چند ابری برای ذخیره سازی داده های بزرگ و پرس و جو-2016
Database-as-a-Service provides a scalable cloud database for data owners. However, existing cloud database has its limitations. Intermittent unavailability of cloud service increases the response time for the database. In addition, vendor lock-in makes it difficult for data owners to change the service provider when necessary. In this paper, we propose a secure model based on multi-cloud, adopting secret sharing algorithm to upload the encrypted data to clouds and supporting SQL queries on encrypted data. In our model, most computations are performed in the clouds in order to increase query efficiency. We implemented this model as a client application which is proven to be practical. We observed that our model can improve the availability of cloud database and ensure the data security in multi-cloud. Moreover, this model reduces the query processing time compared to other encrypted cloud database without increasing the cost of cloud service.
Keywords: database security| multi-cloud | secret sharing | ven dor lock-in | cloud availability
مقاله انگلیسی
4 A Pretreatment Workflow Scheduling Approach for Big Data Applications in Multicloud Environments
یک رویکرد برنامه ریزی گردش کار پیش پردازش برای برنامه های داده بزرگ در محیط های چند ابری-2016
The rapid development of the latest distributed computing paradigm, i.e., cloud computing, generates a highly fragmented cloud market composed of numerous cloud providers and offers tremendous parallel computing ability to handle big data problems. One of the biggest challenges in multiclouds is efficient workflow scheduling. Although the workflow scheduling problem has been studied extensively, there are still very few primal works tailored for multicloud environments. Moreover, the existing research works either fail to satisfy the quality of service (QoS) requirements, or do not consider some fundamental features of cloud computing such as heterogeneity and elasticity of computing resources. In this paper, a scheduling algorithm, which is called multiclouds partial critical paths with pretreatment (MCPCPP), for big data workflows in multiclouds is presented. This algorithm incorporates the concept of partial critical paths, and aims to minimize the execution cost of workflow while satisfying the defined deadline constraint. Our approach takes into consideration the essential characteristics of multiclouds such as the charge per time interval, various instance types from different cloud providers, as well as homogeneous intrabandwidth vs. heterogeneous interbandwidth. Various types of workflows are used for evaluation purpose and our experimental results show that the MCPCPP is promising.
Index Terms: Big data| cloud computing | multiclouds | scheduling | scientific workflow
مقاله انگلیسی
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بازدید امروز: 1878 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 1878 :::::::: افراد آنلاین: 66