Profit Of Cloud Service Provider Research Articles

A Multiserver Configuration and Request Distribution Framework for Profit Maximization in a Three-Tier Cloud Service Architecture

The rapid development of cloud computing has generated numerous cloud service providers. In a three-tier cloud service architecture, maximizing the cloud service profit is not only a goal pursued by cloud service providers but also a potent force that drives the continuous development of cloud computing technology. The traditional methods of maximizing cloud service profits are either limited to cloud resource management or service request distribution. Few work contributes to maximizing the profit of cloud service providers while considering both resource management and request distribution. Besides, the heterogeneity of servers is also an important concern when configuring the multiserver system. Therefore, this paper proposes a multiserver configuration and request distribution framework oriented to a three-tier cloud service architecture for maximizing the profit of cloud service providers. Compared with the benchmark method, extensive numerical simulation experiments show that our proposed framework can not only maximize the profit of cloud service providers, but also has a well-time efficiency.

Prediction-Based Resource Assignment Scheme to Maximize the Net Profit of Cloud Service Providers

In a cloud computing environment, users using the pay-as-you-go billing model can relinquish their services at any point in time and pay accordingly. From the perspective of the Cloud Service Providers (CSPs), this is not beneficial as they may lose the opportunity to earn from the relinquished resources. Therefore, this paper tackles the resource assignment problem while considering users relinquishment and its impact on the net profit of CSPs. As a solution, we first compare different ways to predict user behavior (i.e. how likely a user will leave the system before its scheduled end time) and deduce a better prediction technique based on linear regression. Then, based on the RACE (Relinquishment-Aware Cloud Economics) model proposed in [1], we develop a relinquishment-aware resource optimization model to estimate the amount of resources to assign on the basis of predicted user behavior. Simulations performed with CloudSim show that cloud service providers can gain more by estimating the amount of resources using better prediction techniques rather than blindly assigning resources to users. They also show that the proposed prediction-based resource assignment scheme typically generates more profit for a lower or similar utilization.

A comparative review of meta-heuristic approaches to optimize the SLA violation costs for dynamic execution of cloud services

This paper presents comparative analysis results of research work done using the five most popular meta-heuristic techniques to optimize the service-level agreement (SLA) violation cost in cloud computing. The meta-heuristic algorithms have the ability to handle multifarious types of constraints and offer better results. The Quality of Service criteria, SLA penalty cost and the cloud-domain-specific constraints have been mathematically formulated in this paper. The sole motivation of this paper is that the constraints of feasible domain must be satisfied and the profit of cloud service provider should be maximized. An effort has been made to experimentally demonstrate the comparative performance of five meta-heuristic algorithms, namely Ant Colony Optimization, Particle Swarm Optimization, Genetic Algorithm, Gray Wolf Optimizer and Harmony Search. Eleven test benchmark functions have been applied to demonstrate the efficiency and performance. The best solutions of each meta-heuristic technique have been reported in four performance metric cases: worst, best, average and standard deviation.

Enhancing Provider’s Profit on Cloud Market Infrastructure

Cloud infrastructure and platform services of the cloud are progressively getting to be plainly well known everywhere throughout the world, however, resource scheduling and allocation of multiple virtual machines on clouds are still a difficult task to attain. Streamlining of these issues can be useful in enhancing the vitality savings and load adjusting in substantial datacenters. Since the request of assets from client fluctuates with time, therefore, the load on cloud generally remains low during normal hours and remains high during peak hours. A solitary cloud service provider might not have obliged assets to satisfy client's solicitations amid the pinnacle hour and on contrary, there may be some providers with under-utilized resources. These difficulties can be overcome by using cloud federation which allows outsourcing at peak time i.e., underutilized providers can rent their resources to different IaaS (Infrastructure as a service) providers. Resource allocation and scheduling also have an impact in federated clouds, assets can be purchased from different individuals of cloud federation. Existing practices cloud confederation and resource management are a bit intricate, which makes them less dynamic in nature and in some cases decreases the revenue and profit of cloud service provider. A prototype of new method for cloud confederation has expounded which focuses to enhance the gain for cloud service provider. Our parameters include free assets to be sold, a number of outsourced resources, the fare of maintaining servers, the fare of third party resources, and workload.

Customer-Satisfaction-Aware Optimal Multiserver Configuration for Profit Maximization in Cloud Computing

Along with the development of cloud computing, an increasing number of enterprises start to adopt cloud service, which promotes the emergence of many cloud service providers. For cloud service providers, how to configure their cloud service platforms to obtain the maximum profit becomes increasingly the focus that they pay attention to. In this paper, we take customer satisfaction into consideration to address this problem. Customer satisfaction affects the profit of cloud service providers in two ways. On one hand, the cloud configuration affects the quality of service which is an important factor affecting customer satisfaction. On the other hand, the customer satisfaction affects the request arrival rate of a cloud service provider. However, few existing works take customer satisfaction into consideration in solving profit maximization problem, or the existing works considering customer satisfaction do not give a proper formalized definition for it. Hence, we first refer to the definition of customer satisfaction in economics and develop a formula for measuring customer satisfaction in cloud computing. And then, an analysis is given in detail on how the customer satisfaction affects the profit. Lastly, taking into consideration customer satisfaction, service-level agreement, renting price, energy consumption, and so forth, a profit maximization problem is formulated and solved to get the optimal configuration such that the profit is maximized.

Guaranteeing Delay of Live Virtual Machine Migration by Determining and Provisioning Appropriate Bandwidth

The proliferation of cloud services makes virtualization technology more important. One important feature of virtualization is live Virtual Machine (VM) migration. Two main metrics of evaluating a live VM migration mechanism are total migration time and downtime . Most existing literature on live VM migration focus on designing migration mechanisms to shorten the two metrics or making a tradeoff between them. Few of them can be applied to applications with delay requirements, such as a VM backup process that needs to be done in a specific time. This will negatively impact the user experiences and reduce the profit of cloud service providers. Besides, the frequently varied bandwidth required by the widely used pre-copy mechanism is difficult to be provided by current network technologies. In this work, we theoretically analyze how much bandwidth is required to guarantee the total migration time and downtime of a live VM migration, and then propose a novel transport control mechanism to guarantee the computed bandwidth. The experimental results demonstrate that the bandwidth obtained from the proposed reciprocal-based model guarantees the expected total migration time and downtime, and the proposed transport control mechanism ensures that the live VM migration flow obtains the expected bandwidth even if there are background flows.

I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers

the advent of cloud computing in the arena of IT field energy consumption and service level agreement (SLA) violation emerge as a major problem, which reduces the profit of cloud service providers (CSP) and affect the cloud customers by fencing the reusability and scalability of the cloud data center services. This problem needs to be eradicate for the efficient resource provisioning in cloud data center. To satisfy the customer need virtual machine (VM) migration technique is required to balance the load of entire data center. Therefore we need to transfer the virtual machine of the overloaded host to the light weighted host using virtual machine migration technique. Due to frequent load balancing of cloud data center enormous amount of energy consumption takes place. This enhances the overall energy cost and degrades the performance of cloud data center. This paper proposes an Energy Efficient Dynamic VM Consolidation algorithm for reducing energy consumption. Keywordscomputing, Cloud service provider (CSP), Energy consumption, SLA violation, Load balancing, VM migration.

Payment-based incentive mechanism for secure cloud deduplication

Data deduplication is a very important technique to reduce the storage cost in cloud storage and management systems. Currently, various secure deduplication encryption schemes have be designed to protect the privacy of clients’ data. However, they cannot ensure an economical-selfish cloud service provider to manage the data system with an optimal duplication price. This will create a strong disincentive for the clients to be involved in the deduplication. In this paper, we first propose a secure payment-based incentive mechanism for deduplication systems which can enhance the efficiency of data management. The security and incentive analysis show that any malicious cloud service provider cannot deceive a client with a higher deduplication price. Our mechanism could incent the clients to participate the deduplication since the price per bit of an active client is always lower than that of a passive one. Moreover, our mechanism shows that the total profit of cloud service provider will increase even if the payment of each client is decreased. Therefore, the cloud service provider is also stimulated for deduplication.