scholarly journals A Semi-Markov decision model-based brokering mechanism for mobile cloud market

2021 ◽  
Author(s):  
Elena Degtiareve
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Iteration Algorithm ◽  
Value Iteration ◽  
Security Risk ◽  
System Cost ◽  
Cloud Broker ◽  
Markov Decision ◽  
Markov Decision Model

As the multitude and complexity of cloud market increases the evaluation and selection of cloud services becomes a burdensome task for the users. With the increased rise of available services from various Cloud Service Providers (CSP), the role of cloud brokers becomes more and more important. In this thesis, the challenge of optimally allocating multiple cloud system resources to multiple mobile user’s requests with different requirements is investigated and an optimal Cloud Broker model is proposed. The cloud brokering mechanism is formulated as a Semi-Markov Decision Process (SMDP) model under the average system cost criteria, taking into consideration the cost of the occupying computing resources, the communication costs, the request traffic, and some security risk degrees and resource requirements from the multiple mobile users. Through minimizing the overall system cost, the optimal resource allocation policy is derived by using the Value Iteration Algorithm. Simulation results are provided, demonstrating the efficiency of the proposed Cloud Broker design.

scholarly journals A Semi-Markov decision model-based brokering mechanism for mobile cloud market

2021 ◽  
Author(s):  
Elena Degtiareve
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Iteration Algorithm ◽  
Value Iteration ◽  
Security Risk ◽  
System Cost ◽  
Cloud Broker ◽  
Markov Decision ◽  
Markov Decision Model

As the multitude and complexity of cloud market increases the evaluation and selection of cloud services becomes a burdensome task for the users. With the increased rise of available services from various Cloud Service Providers (CSP), the role of cloud brokers becomes more and more important. In this thesis, the challenge of optimally allocating multiple cloud system resources to multiple mobile user’s requests with different requirements is investigated and an optimal Cloud Broker model is proposed. The cloud brokering mechanism is formulated as a Semi-Markov Decision Process (SMDP) model under the average system cost criteria, taking into consideration the cost of the occupying computing resources, the communication costs, the request traffic, and some security risk degrees and resource requirements from the multiple mobile users. Through minimizing the overall system cost, the optimal resource allocation policy is derived by using the Value Iteration Algorithm. Simulation results are provided, demonstrating the efficiency of the proposed Cloud Broker design.

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.

scholarly journals An optimal broker design for inter-cloud systems

2021 ◽  
Author(s):  
Shraddha R Peesary
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
End Users ◽  
Service Request ◽  
Cloud Systems ◽  
Cloud Broker ◽  
Cost Criterion ◽  
Long Run ◽  
Markov Decision ◽  
The One

In the next generation of Cloud computing systems, it is expected that multiple Cloud Service Providers (CSPs) will cooperate together to advertise their services and prices to their end users, which may choose the one that best meets their budgetary and technical needs. Despite this benefit of having multiple CSPs to select from, several issues may arise. For instance, how does an IT entrepreneur select a CSP to offload his/her service request? How does the underlying Inter-Cloud system handle this service request? To address these questions, this thesis proposes a novel Optimal Cloud Broker design for Inter-Cloud Systems in the form of a Semi-Markov Decision Process (SMDP) based model. Under the long-run expected average cost criterion, the optimal policy is derived, which aim at maximizing the overall virtual machine utilization while giving the end users the best possible prices. The effectiveness of the proposed Broker design is validated by numerical results.

scholarly journals An optimal broker design for inter-cloud systems

2021 ◽  
Author(s):  
Shraddha R Peesary
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
End Users ◽  
Service Request ◽  
Cloud Systems ◽  
Cloud Broker ◽  
Cost Criterion ◽  
Long Run ◽  
Markov Decision ◽  
The One

In the next generation of Cloud computing systems, it is expected that multiple Cloud Service Providers (CSPs) will cooperate together to advertise their services and prices to their end users, which may choose the one that best meets their budgetary and technical needs. Despite this benefit of having multiple CSPs to select from, several issues may arise. For instance, how does an IT entrepreneur select a CSP to offload his/her service request? How does the underlying Inter-Cloud system handle this service request? To address these questions, this thesis proposes a novel Optimal Cloud Broker design for Inter-Cloud Systems in the form of a Semi-Markov Decision Process (SMDP) based model. Under the long-run expected average cost criterion, the optimal policy is derived, which aim at maximizing the overall virtual machine utilization while giving the end users the best possible prices. The effectiveness of the proposed Broker design is validated by numerical results.

scholarly journals Profit Maximization for Cloud Broker in Cloud Computing

2021 ◽  
Vol 9 (VII) ◽  
pp. 354-359
Author(s):  
Prof. M. S. Namose
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Providers ◽  
Current System ◽  
Profit Maximization ◽  
Cloud Service ◽  
Cloud Services ◽  
Market Demand ◽  
Cloud Broker ◽  
The Cost

As cloud computing evolves, more and more applications are moving to the cloud. Cloud brokers are are like Middlemen between cloud service providers and cloud users. Thus, cloud brokers can significantly reduce the cost of consumers. In addition to reducing the cost per user, the cloud broker can also accommodate the price difference between on-demand virtual machines and dedicated virtual machines. The problem with the current system is that if many customers request a large amount of cloud services at once, the cloud service broker cannot purchase enough cloud services from CSP to meet the needs of all customers. Then there is a peak demand problem where the customer cannot complete the job. As a result, dynamic conditions not only lead to financial problems, but can also negatively impact the customer experience. To solve this problem, the system focuses on guaranteed quality of service for all requests, reduces waste of resources, increases security and maximizes revenue. All jobs are scheduled by the job scheduler and assigned to different VMs in a centralized way. Many factors such as market demand, application volume, SLA, service rental cost, etc. are taken into account to formulate an optimal configuration problem of profit maximization.

A Practical Conflicting Role-based Cloud Security Risk Evaluation Method

2019 ◽  
Vol 13 ◽  
Author(s):  
Jin Han ◽  
Jing Zhan ◽  
Xiaoqing Xia ◽  
Xue Fan
Keyword(s):  
Risk Evaluation ◽  
Evaluation Method ◽  
Service Providers ◽  
Risk Preferences ◽  
Cloud Service ◽  
Cloud Security ◽  
Third Party ◽  
Security Evaluation ◽  
Security Risk ◽  
Cloud Users

Background: Currently, Cloud Service Provider (CSP) or third party usually proposes principles and methods for cloud security risk evaluation, while cloud users have no choice but accept them. However, since cloud users and cloud service providers have conflicts of interests, cloud users may not trust the results of security evaluation performed by the CSP. Also, different cloud users may have different security risk preferences, which makes it difficult for third party to consider all users' needs during evaluation. In addition, current security evaluation indexes for cloud are too impractical to test (e.g., indexes like interoperability, transparency, portability are not easy to be evaluated). Methods: To solve the above problems, this paper proposes a practical cloud security risk evaluation method of decision-making based on conflicting roles by using the Analytic Hierarchy Process (AHP) with Aggregation of Individual priorities (AIP). Results: Not only can our method bring forward a new index system based on risk source for cloud security and corresponding practical testing methods, but also can obtain the evaluation result with the risk preferences of conflicting roles, namely CSP and cloud users, which can lay a foundation for improving mutual trusts between the CSP and cloud users. The experiments show that the method can effectively assess the security risk of cloud platforms and in the case where the number of clouds increased by 100% and 200%, the evaluation time using our methodology increased by only by 12% and 30%. Conclusion: Our method can achieve consistent decision based on conflicting roles, high scalability and practicability for cloud security risk evaluation.

scholarly journals A Generic Model for Identifying QoS Parameters Interrelations in Cloud Services Selection Ontology during Runtime

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 563
Author(s):  
Babu Rajendiran ◽  
Jayashree Kanniappan
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Operating Costs ◽  
Generic Model ◽  
Business Organizations ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Computer Based

Nowadays, many business organizations are operating on the cloud environment in order to diminish their operating costs and to select the best service from many cloud providers. The increasing number of Cloud Services available on the market encourages the cloud consumer to be conscious in selecting the most apt Cloud Service Provider that satisfies functionality, as well as QoS parameters. Many disciplines of computer-based applications use standardized ontology to represent information in their fields that indicate the necessity of an ontology-based representation. The proposed generic model can help service consumers to identify QoS parameters interrelations in the cloud services selection ontology during run-time, and for service providers to enhance their business by interpreting the various relations. The ontology has been developed using the intended attributes of QoS from various service providers. A generic model has been developed and it is tested with the developed ontology.

scholarly journals Addressing Semantics Standards for Cloud Portability and Interoperability in Multi Cloud Environment

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 317
Author(s):  
Chithambaramani Ramalingam ◽  
Prakash Mohan
Keyword(s):  
Service Providers ◽  
Research Work ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Environment ◽  
Cloud Service Providers ◽  
Application Programming ◽  
Increasing Demand ◽  
Programming Interfaces ◽  
Multi Cloud

The increasing demand for cloud computing has shifted business toward a huge demand for cloud services, which offer platform, software, and infrastructure for the day-to-day use of cloud consumers. Numerous new cloud service providers have been introduced to the market with unique features that assist service developers collaborate and migrate services among multiple cloud service providers to address the varying requirements of cloud consumers. Many interfaces and proprietary application programming interfaces (API) are available for migration and collaboration services among cloud providers, but lack standardization efforts. The target of the research work was to summarize the issues involved in semantic cloud portability and interoperability in the multi-cloud environment and define the standardization effort imminently needed for migrating and collaborating services in the multi-cloud environment.

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

Adiabatic Markov Decision Process: Convergence of Value Iteration Algorithm

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Thai Duong ◽  
Duong Nguyen-Huu ◽  
Thinh Nguyen
Keyword(s):  
Markov Decision Process ◽  
Decision Process ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Rate Of Change ◽  
Optimal Decision ◽  
Iteration Algorithm ◽  
Value Iteration ◽  
Markov Decision ◽  
Value Iteration Algorithm

Markov decision process (MDP) is a well-known framework for devising the optimal decision-making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not provide the expected performance. In this paper, we study the performance of the classic value iteration algorithm for solving an MDP problem under nonstationary environments. Specifically, the nonstationary environment is modeled as a sequence of time-variant transition probability matrices governed by an adiabatic evolution inspired from quantum mechanics. We characterize the performance of the value iteration algorithm subject to the rate of change of the underlying environment. The performance is measured in terms of the convergence rate to the optimal average reward. We show two examples of queuing systems that make use of our analysis framework.

Sign in / Sign up

Export Citation Format

Share Document