scholarly journals Cloud hosting services and resources utilizing efficient proxy server based speculative algorithm

2018 ◽  
Vol 7 (4) ◽  
pp. 2687
Author(s):  
Ravi Mahadevan ◽  
Neelamegam Anbazhagan
Keyword(s):  
Energy Consumption ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Data Consistency ◽  
Current Status ◽  
Maintenance Cost ◽  
Proxy Server ◽  
Service Policies ◽  
Qos Performance

Cloud computing is an envisioned technique for service providing paradigm. Currently, many enterprises and organizations are hosting data into cloud service provider to minimize the maintenance cost, energy consumption and improve the data consistency. However, the several cloud servers facing the various hosting service policies, clients may be confused with which cloud server providers are appropriate for storing data and which hosting methodology is inexpensive. The current status quo is clients frequently put data into the single cloud and simply trust to luck. In the paper, proposes a new data hosting redundancy methodology called as Efficient Proxy Server Based Speculative (EPSBS) algorithm that provides accessibility guarantee, reducing hosting service, energy consumption and enhances Quality of Services (QoS) performance concurrently and it requires integrating two key functions. The first function is choosing numerous appropriate cloud service providers and a suitable EPSBS redundancy methodology to store data with guaranteed accessibility. The second key function is triggering a transmission process to reallocate data along with the deviations of data access prototype of clouds.  Based on Experimental evaluations, proposed methodology reduces 0.11 ET (Execution Time), and 0.02 EC (Energy Consumption) and improves 29% HS (Hosting Service size), 2.8 T (Throughput) compared than existing methodologies.

scholarly journals An Adaptive Data Placement Architecture in Multicloud Environments

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Pengwei Wang ◽  
Caihui Zhao ◽  
Yi Wei ◽  
Dong Wang ◽  
Zhaohui Zhang
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Data Retrieval ◽  
Data Placement ◽  
Data Availability ◽  
Maintenance Cost ◽  
Time Varying ◽  
Access Pattern ◽  
Data Lifetime

Cloud service providers (CSPs) can offer infinite storage space with cheaper maintenance cost compared to the traditional storage mode. Users tend to store their data in geographical and diverse CSPs so as to avoid vendor lock-in. Static data placement has been widely studied in recent works. However, the data access pattern is often time-varying and users may pay more cost if static placement is adopted during the data lifetime. Therefore, it is a pending problem and challenge of how to dynamically store users’ data under time-varying data access pattern. To this end, we propose ADPA, an adaptive data placement architecture that can adjust the data placement scheme based on the time-varying data access pattern and subject for minimizing the total cost and maximizing the data availability. The proposed architecture includes two main components: data retrieval frequency prediction module based on LSTM and data placement optimization module based on Q-learning. The performance of ADPA is evaluated through several experimental scenarios using NASA-HTTP workload and cloud providers information.

scholarly journals Energy-Aware Autonomic Resource Scheduling Framework for Cloud

2019 ◽  
Vol 4 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Bhupesh Kumar Dewangan ◽  
Amit Agarwal ◽  
Venkatadri M. ◽  
Ashutosh Pasricha
Keyword(s):  
Energy Consumption ◽  
Resource Utilization ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Providers ◽  
Optimal Solution ◽  
Cloud Service ◽  
Cloud Services ◽  
Energy Aware ◽  
Increasing Demand

Cloud computing is a platform where services are provided through the internet either free of cost or rent basis. Many cloud service providers (CSP) offer cloud services on the rental basis. Due to increasing demand for cloud services, the existing infrastructure needs to be scale. However, the scaling comes at the cost of heavy energy consumption due to the inclusion of a number of data centers, and servers. The extraneous power consumption affects the operating costs, which in turn, affects its users. In addition, CO2 emissions affect the environment as well. Moreover, inadequate allocation of resources like servers, data centers, and virtual machines increases operational costs. This may ultimately lead to customer distraction from the cloud service. In all, an optimal usage of the resources is required. This paper proposes to calculate different multi-objective functions to find the optimal solution for resource utilization and their allocation through an improved Antlion (ALO) algorithm. The proposed method simulated in cloudsim environments, and compute energy consumption for different workloads quantity and it increases the performance of different multi-objectives functions to maximize the resource utilization. It compared with existing frameworks and experiment results shows that the proposed framework performs utmost.

scholarly journals Data Storage, Security And Techniques In Cloud Computing

2020 ◽  
Author(s):  
Dinesh Arpitha R ◽  
Sai Shobha R
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Cloud Services ◽  
Security Risk ◽  
Storage Security ◽  
The Cost ◽  
User Knowledge

Cloud computing is the computing technology which provides resources like software, hardware, services over the internet. Cloud computing provides computation, software, data access, and storage services that do not require end- user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing enables the user and organizations to store their data remotely and enjoy good quality applications on the demand without having any burden associated with local hardware resources and software managements but it possesses a new security risk towards correctness of data stored at cloud. The data storage in the cloud has been a promising issue in these days. This is due to the fact that the users are storing their valuable data and information in the cloud. The users should trust the cloud service providers to provide security for their data. Cloud storage services avoid the cost storage services avoids the cost expensive on software, personnel maintains and provides better performance less storage cost and scalability, cloud services through internet which increase their exposure to storage security vulnerabilities however security is one of the major drawbacks that preventing large organizations to enter into cloud computing environment. This work surveyed on several storage techniques and this advantage and its drawbacks.

Migration of Data between Cloud and Non-Cloud Datastores

2012 ◽  
pp. 206-225
Author(s):  
Shreyansh Bhatt ◽  
Sanjay Chaudhary ◽  
Minal Bhise
Keyword(s):  
Relational Databases ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Data Migration ◽  
Cloud Service Providers ◽  
Application Data ◽  
And Migration ◽  
Legacy Applications ◽  
Recent Attention

The on demand services and scalability features of cloud computing have attracted many customers to move their applications into the cloud. Therefore, application, data access, storage, and migration to and from cloud have garnered much recent attention, especially with well-established legacy applications. Cloud service providers are following different standards to host applications and data. In the present chapter, the authors focus on data migration from various datastores to cloud and vice versa. They have discussed various challenges associated with this reciprocal migration and proposed a simple yet powerful model whereby data can be migrated between various datastores, especially cloud datastores. The results show an efficient way to move data from conventional relational databases to Google App Engines and how data residing in the Google App Engines can be stored on relational databases and vice versa. They provide a generalized architecture to store data in any cloud datastore. The authors use RDF/RDFS as an intermediate model in the migration process.

Authentication and Identity Management for Secure Cloud Businesses and Services

2014 ◽  
pp. 180-201 ◽  
Author(s):  
Bing He ◽  
Tuan T. Tran ◽  
Bin Xie
Keyword(s):  
Access Control ◽  
Identity Management ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Fine Grained ◽  
Industry Standards ◽  
Cloud Service Providers ◽  
Potential Benefits ◽  
Identity Management System

Today, cloud-based services and applications are ubiquitous in many systems. The cloud provides undeniable potential benefits to the users by offering lower costs and simpler deployment. The users significantly reduce their system management responsibilities by outsourcing services to the cloud service providers. However, the management shift has posed significant security challenges to the cloud service providers. Security concerns are the main reasons that delay organizations from moving to the cloud. The security and efficiency of user identity management and access control in the cloud needs to be well addressed to realize the power of the cloud. In this chapter, the authors identify the key challenges and provide solutions to the authentication and identity management for secure cloud business and services. The authors first identify and discuss the challenges and requirements of the authentication and identity management system in the cloud. Several prevailing industry standards and protocols for authentication and access control in cloud environments are provided and discussed. The authors then present and discuss the latest advances in authentication and identity management in cloud, especially for mobile cloud computing and identity as a service. They further discuss how proximity-based access control can be applied for an effective and fine-grained data access control in the cloud.

scholarly journals A Privacy-Preserving Attribute-Based Encryption System for Data Sharing in Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xieyang Shen ◽  
Chuanhe Huang ◽  
Danxin Wang ◽  
Jiaoli Shi
Keyword(s):  
Data Sharing ◽  
Service Providers ◽  
Smart Cities ◽  
Information Leakage ◽  
Cloud Service ◽  
Data Access ◽  
Smart Devices ◽  
Fine Grained ◽  
Data Access Control ◽  
High Level

Information leakage and efficiency are the two main concerns of data sharing in cloud-aided IoT. The main problem is that smart devices cannot afford both energy and computation costs and tend to outsource data to a cloud server. Furthermore, most schemes focus on preserving the data stored in the cloud but omitting the access policy is typically stored in unencrypted form. In this paper, we proposed a fine-grained data access control scheme based on CP-ABE to implement access policies with a greater degree of expressiveness as well as hidden policies from curious cloud service providers. Moreover, to mitigate the extra computation cost generated by complex policies, an outsourcing service for decryption can be used by data users. Further experiments and extensive analysis show that we significantly decrease the communication and computation overhead while providing a high-level security scheme compared with the existing schemes.

Authentication and Identity Management for Secure Cloud Businesses and Services

2016 ◽  
pp. 1629-1651
Author(s):  
Bing He ◽  
Tuan T. Tran ◽  
Bin Xie
Keyword(s):  
Access Control ◽  
Identity Management ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Fine Grained ◽  
Industry Standards ◽  
Cloud Service Providers ◽  
Potential Benefits ◽  
Identity Management System

Today, cloud-based services and applications are ubiquitous in many systems. The cloud provides undeniable potential benefits to the users by offering lower costs and simpler deployment. The users significantly reduce their system management responsibilities by outsourcing services to the cloud service providers. However, the management shift has posed significant security challenges to the cloud service providers. Security concerns are the main reasons that delay organizations from moving to the cloud. The security and efficiency of user identity management and access control in the cloud needs to be well addressed to realize the power of the cloud. In this chapter, the authors identify the key challenges and provide solutions to the authentication and identity management for secure cloud business and services. The authors first identify and discuss the challenges and requirements of the authentication and identity management system in the cloud. Several prevailing industry standards and protocols for authentication and access control in cloud environments are provided and discussed. The authors then present and discuss the latest advances in authentication and identity management in cloud, especially for mobile cloud computing and identity as a service. They further discuss how proximity-based access control can be applied for an effective and fine-grained data access control in the cloud.

scholarly journals HNSciCloud, a Hybrid Cloud for Science

2019 ◽  
Vol 214 ◽  
pp. 09006
Author(s):  
João Fernandes ◽  
Bob Jones ◽  
Sergey Yakubov ◽  
Andrea Chierici
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Cloud Services ◽  
Use Cases ◽  
Hybrid Cloud ◽  
Network Bandwidth ◽  
It Resources ◽  
Cloud Service Providers ◽  
Research Organisations

Helix Nebula Science Cloud (HNSciCloud) has developed a hybrid cloud platform that links together commercial cloud service providers and research organizations’ in-house IT resources via the GEANT network. The platform offers data management capabilities with transparent data access where applications can be deployed with no modifications on both sides of the hybrid cloud and with compute services accessible via eduGAIN [1] and ELIXIR [2] federated identity and access management systems. In addition, it provides support services, account management facilities, full documentation and training. The cloud services are being tested by a group of 10 research organisations from across Europe [3], against the needs of use-cases from seven ESFRI infrastructures [4]. The capacity procured by ten research organisations from the commercial cloud service providers to support these use-cases during 2018 exceeds twenty thousand cores and two petabytes of storage with a network bandwidth of 40Gbps. All the services are based on open source implementations that do not require licenses in order to be deployed on the in-house IT resources of research organisations connected to the hybrid platform. An early adopter scheme has been put in place so that more research organisations can connect to the platform and procure additional capacity to support their research programmes.

scholarly journals Virtual Machine Customization Using Resource Using Prediction for Efficient Utilization of Resources in IaaS Public Clouds

2021 ◽  
Vol 6 (2) ◽  
pp. 170-182
Author(s):  
Derdus Kenga ◽  
Vincent Omwenga ◽  
Patrick Ogao
Keyword(s):  
Energy Consumption ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Data ◽  
Efficient Resource ◽  
Server Utilization ◽  
Auto Scaling ◽  
Cloud Users

The main cause of energy wastage in cloud data centres is the low level of server utilization. Low server utilization is a consequence of allocating more resources than required for running applications. For instance, in Infrastructure as a Service (IaaS) public clouds, cloud service providers (CSPs) deliver computing resources in the form of virtual machines (VMs) templates, which the cloud users have to choose from. More often, inexperienced cloud users tend to choose bigger VMs than their application requirements. To address the problem of inefficient resources utilization, the existing approaches focus on VM allocation and migration, which only leads to physical machine (PM) level optimization. Other approaches use horizontal auto-scaling, which is not a visible solution in the case of IaaS public cloud. In this paper, we propose an approach of customizing user VM’s size to match the resources requirements of their application workloads based on an analysis of real backend traces collected from a VM in a production data centre. In this approach, a VM is given fixed size resources that match applications workload demands and any demand that exceeds the fixed resource allocation is predicted and handled through vertical VM auto-scaling. In this approach, energy consumption by PMs is reduced through efficient resource utilization. Experimental results obtained from a simulation on CloudSim Plus using GWA-T-13 Materna real backend traces shows that data center energy consumption can be reduced via efficient resource utilization

scholarly journals Energy-Efficient Cloud Service Selection and Recommendation Based on QoS for Sustainable Smart Cities

2021 ◽  
Vol 11 (20) ◽  
pp. 9394
Author(s):  
Preeti Sirohi ◽  
Fahd N. Al-Wesabi ◽  
Haya Mesfer Alshahrani ◽  
Piyush Maheshwari ◽  
Amit Agarwal ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Recommendation System ◽  
Service Providers ◽  
Smart Cities ◽  
Service Selection ◽  
Cloud Service ◽  
Heat Emission ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Cloud Servers

The growing demand for cloud technology brings several cloud service providers and their diverse list of services in the market, putting a challenge for the user to select the best service from the inventory of available services. Therefore, a system that understands the user requirements and finds a suitable service according to user-customized requirements is a challenge. In this paper, we propose a new cloud service selection and recommendation system (CS-SR) for finding the optimal service by considering the user’s customized requirements. In addition, the service selection and recommendation system will consider both quantitative and qualitative quality of service (QoS) attributes in service selection. The comparison is made between proposed CS-SR with three existing approaches analytical hierarchy process (A.H.P.), efficient non-dominated sorting-sequential search (ENS-SS), and best-worst method (B.W.M.) shows that CR-SR outperforms the above approaches in two ways (i) reduce the total execution time and (ii) energy consumption to find the best service for the user. The proposed cloud service selection mechanism facilitates reduced energy consumption at cloud servers, thereby reducing the overall heat emission from a cloud data center.

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