Dynamic Service Provisioning and Selection for Satisfying Cloud Applications and Cloud Providers in Hybrid Cloud

2017 ◽  
Vol 26 (04) ◽  
pp. 1750005 ◽  
Author(s):  
Xu Lijun ◽  
Li Chunlin

The paper presents a hybrid cloud service provisioning and selection optimization scheme, and proposes a hybrid cloud model which consists of hybrid cloud users, private cloud and public cloud. This scheme aims to effectively provide cloud service and allocate cloud resources, such that the system utility can be maximized subject to public cloud resource constraints and hybrid cloud users constraints. The paper makes use of a utility-driven approach to solve interaction among private cloud user, hybrid cloud service provider and public cloud provider in hybrid cloud environment. The paper presents hybrid cloud service provisioning and selection algorithm in hybrid cloud. The hybrid cloud market consists of hybrid cloud user agent, hybrid cloud service agent and hybrid cloud agent, which represent the interests of different roles. The experiments are designed to compare the performance of proposed algorithm with the other related work.

2015 ◽  
Vol 24 (08) ◽  
pp. 1550111 ◽  
Author(s):  
Chunlin Li ◽  
LaYuan Li

The paper proposes hierarchical scheduling optimization scheme in hybrid cloud. Our proposed hierarchical scheduling takes advantage of the interaction of cloud users, private cloud and public cloud. For high level optimization in hybrid cloud, the objective of public cloud provider optimization is to maximize the revenue of providing virtual machines (VMs) and minimize the energy cost. The private cloud users' applications give the unique optimal payment to public cloud providers under deadline and cost constraint to maximize the satisfaction of private cloud user applications. The objective of low-level scheduling optimization is to minimize the cost and execution time of private cloud application. From the simulation results, the revenue, execution success ratio and resource utilization of our proposed hierarchical scheduling algorithm are better than other related works.


Techno Com ◽  
2018 ◽  
Vol 17 (4) ◽  
pp. 404-414
Author(s):  
Toga Aldila Cinderatama ◽  
Yoppy Yunhasnawa ◽  
Rinanza Zulmy Alhamri

Dalam implementasi big data biasanya membutuhkan sumber daya yang cukup besar untuk dapat melakukan analisis terhadap data-data yang jumlahnya sangat besar tersebut, hal ini biasanya menjadi kendala dikarenakan keterbatasan sumber daya yang dimiliki. Komputasi awan (cloud computing) yang salah satunya mempunyai sifat elasticity di dalamnya, menawarkan solusi keterbatasan sumber daya ini. Sumber daya yang terbatas misalkan dalam hal processor, RAM atau storage, dapat digabungkan dengan sumber daya yang dimiliki public cloud provider yang tersedia di market. Sehingga penggabungan 2 sumber daya ini, private cloud dan public cloud, diharapkan menjadi solusi untuk dapat mengimplementasikan analisis big data yang dapat diterapkan untuk analisis berbagai macam bidang. Secara umum penelitian ini bertujuan untuk mengimplementasikan hybrid cloud yang menggabungkan sumber daya dari private cloud dengan sumber daya dari public cloud sebagai infrastruktur untuk analisis big data. Secara khusus tujuan penelitian ini adalah merumuskan sebuah metode minimalisasi cost dalam pemilihan public cloud dengan pendekatan sistem pendukung keputusan menggunakan Fuzzy AHP pada pemilihan public cloud. Langkah pertama yang dilakukan dalam penelitian ini adalah pengumpulan data cost penggunaan resource dari public cloud. Selanjutnya dilakukan analisis kebutuhan sumber daya yang diperlukan untuk melalukan analisis big data dengan studi kasus topik tertentu. Selanjutnya tahap analisis terhadap pemilihan public cloud yang tepat untuk digunakan sumber dayanya dengan pertimbangan minimalisasi cost. Langkah terakhir adalah implementasi hybrid cloud dan melakukan analisis dan evaluasi terhadap metode yang diusulkan.


2015 ◽  
pp. 1721-1731
Author(s):  
S. Srinivasan

Cloud computing is facilitated often through the open Internet, which is not designed for secure communications. From the cloud user perspective, access to the cloud through a Virtual Private Network (VPN) is a possibility, but this is not the default access method for all cloud users. Given this reality, the cloud service users must be prepared for risk management because they do not control the cloud hardware or the communication channels. Added to this uncertainty is the potential for cloud service outage for risk management planning. In this chapter, the authors discuss the various aspects of risk management from the cloud user perspective. In addition, they analyze some of the major cloud outages over the past five years that have resulted in loss of trust. This list includes the outages in Amazon Web Services, Google, Windows, and Rackspace.


Author(s):  
Junfeng Tian ◽  
He Zhang

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.


2020 ◽  
Vol 8 (5) ◽  
pp. 1627-1631

Confidentiality, Privacy and Protection of data (CPPD) are the major challenges in the cloud environment for cloud users such as industrials and organizations. Hence major companies are loath to migrate to cloud and also still using the private cloud because of lock in CPPD of cloud. Cloud Service Providers (CSP) are unable to elucidate strength of the storage and services due to lack of data security. To solve the above issue, we trust, algorithms are not the only solution for data security. In this regards, we suggest to change the architecture and develop a new mechanisms. In this paper, we are proposed two thinks. First is move to single cloud architecture to multiple cloud architecture and second is develop an innovative algorithm. And one more think also considered and proposed an inimitable mechanism to use an innovative algorithm in the multi cloud architecture for improving CPPD.


2019 ◽  
pp. 903-922
Author(s):  
Junfeng Tian ◽  
He Zhang

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.


The Cloud substitutes a computing criterion where shared configurable resources are afforded as an on-demand service over the Internet. Moreover, the cloud environment provides resources to the users on the basis of services like SaaS, PaaS and IaaS. Generally, a cloud can be referred as private cloud or public cloud. When a Cloud Service Provider (CSP) imposes upon public cloud resources to compile their private cloud, the result is demonstrated as a virtual private cloud. Private or public, the imperious intent of cloud computing is to provide simplistic, reliable usage of various computing resources. One of the significant features of cloud is that the outsourced data are accessed through any anonymous machines over the Internet. On the other hand, it creates an issue that user’s fear of unknown access of data, which can become a major difficulty to the wide implementation of cloud. In this paper, a decentralized accountability framework is developed to monitor the actual usage and access of the data that is shared on cloud. For that, a logging mechanism that includes authentication for each user to access the data has also been provided. Moreover, some procedures for providing the data under the control of data owner includes Integrity Checking Mechanism (ICM) have also been developed. The overall process strengthens the security constraints over cloud. And the experimental results reveal that the approach affords secure and scalable data sharing with reduced memory utilization and processing time


Cloud computing allows on-demand access and fast network connection to a shared resource pool. Most companies are switching to Cloud due to the popularity and benefits of using Cloud Services. So finding a suitable and best cloud provider is a challenge for all users. Several ranking methods, such as AHP, TOPSIS, had been suggested to solve this problem by multicriteria decision making techniques. But, many of the works focused on a subset of the main QoS attributes for ranking. Cloud Services Measurement Initiatives Consortium (CSMIC) has released Service Measurement Index attributes for effectively comparing the Cloud services. The comparison of services provided by cloud based on SMI attributes which are qualitative as well as quantitative in nature is studied in this paper by one of the non-parametric methods called Data Envelopment Analysis (DEA) and ranked the cloud services based on the efficiency scores obtained by DEA. The cloud users can select the best suitable Cloud service using the proposed approach that best suit their QoS requirements.


Author(s):  
Rajkamal Kaur Grewal ◽  
Pushpendra Kumar Pateriya

Resource provisioning is important issue in cloud computing and in the environment of heterogeneous clouds. The private cloud with confidentiality data configure according to users need. But the scalability of the private cloud limited. If the resources private clouds are busy in fulfilling other requests then new request cannot be fulfilled. The new requests are kept in waiting queue to process later. It take lot of delay to fulfill these requests and costly. In this paper Rule Based Resource Manager proposed for the Hybrid environment, which increase the scalability of private cloud on-demand and reduce the cost. Also set the time for public cloud and private cloud to fulfill the request and provide the services in time. The Evaluated the performance of Resource Manager on the basis of resource utilization and cost in hybrid cloud environment.


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