Blockchain-based Integrity Verification of Data Migration in Multi-cloud Storage

In the process of multi-cloud storage data migration, data integrity is vulnerable to corruption, but the existing data integrity verification schemes for data migration across clouds are not highly reliable. To address this problem, a blockchain-based data integrity verification scheme for migration across clouds is proposed in this paper. In this scheme, a blockchain network is used instead of a third-party auditor. For each migration, a multi-cloud broker will send an integrity verification request to blockchain at three different times, and a smart contract will verify the data integrity according to the RSA-based homomorphic verification tags. Then, the security of the scheme is analyzed. Finally, simulation experiments and tests are conducted on Ethereum, and the results show the feasibility of the scheme.

Decision Making Models on the Market of Cloud Services

Introduction. Optimization can be applied in developing profitability management tools for a cloud service broker working according to a certain business model. On behalf of the managing telecommunications holding company (telecommunications operator), this broker integrates, aggregates and configures software and data storage services of third-party Internet software vendors. Such a broker receives only fixed commissions from this company, based on the subscription fee, but does not pay royalties to an Internet software vendor and does not receive payments from the sale of service packages. The purpose. The cloud broker faces the problem of limited human resources required to carry out the relevant legal, technical and economic activities. In addition, the broker faces the problem of uncertainty in sales, service prices, the share of resource use, or the risk of losing operational and financial goals. Results. To run a broker?s business efficiently, one needs to find services and their bundles that increase profitability and reduce financial risk by solving certain optimization problems. Information on such services is needed to support negotiations on fixed and variable commissions, as well as to prioritize services and their packages to be provided. Thus, for the cloud services broker, both profitability management tools and services portfolio development tools are useful. In general, a cloud service broker is an organization that negotiates the relationships between cloud service clients and Internet software vendors. Cloud broker can be created on the basis of different business models regarding the type of service (platform, infrastructure, software), type of clients (enterprise, household), functions performed (identity management, accounting, billing, location, etc.), the degree of rebranding, measures of aggregation of services and other criteria. Conclusions. Different cloud brokers have different attitudes to choice of important solutions for their businesses. Solutions can relate to pricing, capacity planning and utilization in combination with service quality, security, scalability and other issues. Keywords: optimization, portfolio, uncertainty, Boolean variables, revenue generation.

Profit Maximization for Cloud Broker in Cloud Computing

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.

An optimal broker design for inter-cloud systems

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.

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

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.

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

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.

An optimal broker design for inter-cloud systems

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.