Adapting Market-Oriented Scheduling Policies for Cloud Computing

Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers

Cost-effective cloud storage services attract users with their convenience; there is a trade-off between the service availability and the usage cost. We develop two cloud provider selection models for cloud storage services to minimize the total cost of usage. The models select multiple cloud providers with considering unavailability to meet the user requirements. The first model, called a user-copy (UC) model, allows to select multiple cloud providers, where a user itself makes copies of its data for multiple providers. In addition to the user copy function of the UC model, the second model, which is called a user and cloud-provider copy (UCC) model, allows cloud providers to make copies of the data to deliver them to other cloud providers. The cloud service is available if at least one cloud provider is available. We formulate both models as integer linear programming (ILP) problems. Our performance evaluation observes that both models reduce the total cost of usage, compared to the single cloud provider selection. As the cost of bandwidth usage between a user and a cloud provider increases, the UCC model becomes more beneficial than the UC model. We implement the prototype for cloud storage services.

Cloud computing is a promising technology, where the infrastructure, developing platform, software and storage are delivered as a service. With the development of cloud computing, more and more cloud service providers emerge. However, there are no metrics can be referred to compare these providers, so it is difficult for cloud consumers to select the most reliable providers or resources. Thus we present a platform of Services Level Agreement (SLA) in cloud computing. In the platform, we propose a Reputation System to evaluate the reliability of providers or resources to address this challenge, and we also propose a SLA template pool in order to make the SLA negotiation between cloud providers and cloud consumers become more equitable, transparent and convenient.

Despite the promising application of cloud computing within government organisations, determining the barriers to the successful implementation of cloud computing remains a major challenge. Often, government organisations face formidable barriers to fully adopting cloud computing functions. These barriers include organisational culture issues, a weak application of service-level agreements (SLAs), compliance issues, interoperability and integration issues, the lack of an organisational strategy, cost calculation methods, cloud service availability, and cloud data security and privacy, as well as insufficient trust in providers. Tackling these barriers while meeting the specifications of government cloud computing involves architectural requirements and mechanisms. In addition, the nature of cloud ecosystem operation and its alignment with appropriate strategies are known to be complex, also considering the growing desire for governance solutions. Although researchers and organisations have recognised cloud computing obstacles prior to the cloud implementation stage, fewer efforts have been made to investigate cloud barriers in-depth during and after cloud implementation projects or when introducing governance solutions. This might partly be attributable to inadequate enterprise requirements for addressing cloud barriers, the complexity of government cloud specifications, and the lack of involvement by cloud stakeholders, such as providers and consumers. Thus, the aim of this dissertation is to develop a governance method consisting of the generation and testing of architectural requirements to overcome dominant cloud barriers and improve cloud computing functionalities in the implementation stage. To achieve this, the roles of related cloud providers and consumers have been investigated. The study was guided by activities of The Open Group Architecture Framework (TOGAF) Architecture Development Method (ADM) to design related architectural requirements that would provide best practices for the development of the governance method. Using a sequential, exploratory mixed method, multiple qualitative case studies on the role of cloud providers were conducted to explore which and how architectural requirements are suitable and applicable for addressing the identified cloud barriers. Afterwards, a quantitative survey study was performed to examine and validate the findings from the qualitative phase and to discover the role of cloud consumers in tackling cloud barriers. The utilisation of dual perspectives, from cloud providers and consumers, to design and measure the suitability and applicability of the architectural requirements is a substantial theoretical contribution in the field of enterprise information systems and cloud governance. Both cloud providers and consumers in the selected research context balanced their roles in the composition of cloud ecosystem projects, reducing complexity and enabling cooperative solutions for handling cloud barriers with different levels of emphasis and prioritisation. The results of this thesis provide significant guidance in eliciting architectural requirements as well as in their successful contribution to addressing the 10 identified cloud barriers in the selected context. Seeking a cloud provider’s perspective through multiple case studies resulted in 24 confirmed, newly emerged architectural requirements and 48 sub-requirements for best practices to support Information Technology (IT) managers and practitioners during the implementation of government cloud projects. From the point of view of the cloud service consumer, statistical evidence showed that the architectural requirements proved to be relevant and applicable and resulted in the validation of only eight important cloud constructs with a scale of 36 architectural requirements. The results at the governance level also produced a clear method that can enhance the realisation of value when business/IT strategies and EA governance practices both take place in cloud projects. The governance method also consists of a set of architectural requirements to support managing and controlling cloud computing implementation projects with related stakeholders and change management initiatives. The architectural requirements have been modelled via the ArchiMate 3.0 modelling language as unique and beneficial contributions for the enhancement of enterprise architecture practices. This thesis thereby introduces a novel cloud governance method with clear mechanisms and practices to serve as crucial resources for related organisations, decision-makers, business practitioners and researchers.

SummaryEach cloud service provider provides only an interface of its own cloud infrastructure for enabling clients to use its cloud resources. However, there is a number of difficulties for cloud providers to ensure proper functioning. One of the main problems of a cloud provider is the lack of resources to support a huge number of on‐demand resources provisioning. Thus, resources cannot be distributed among different cloud providers since the federation is not the basic operation of the cloud provider. The most efficient way to overcome this problem is to extend the interface's cloud provider with an automatic negotiation to dynamically form the best agreement between the different cloud providers based on the service level agreement. In this article, we propose an extension for the Open Cloud Computing Interface which is the standardized interface for the cloud computing to support the automatic negotiation between the different cloud providers. To prove the efficiency and the effectiveness of our approach, we implement a prototype to evaluate the key presented in this article.

The availability and advancements of cloud computing service models such as IaaS, SaaS, and PaaS; introducing on-demand self-service, auto scaling, easy maintenance, and pay as you go, has dramatically transformed the way organizations design and operate their datacenters. However, some organizations still have many concerns like: security, governance, lack of expertise, and migration. The purpose of this paper is to discuss the cloud computing customers’ opinions, feedbacks, attitudes, and emotions towards cloud computing services using sentiment analysis. The associated aim, is to help people and organizations to understand the benefits and challenges of cloud services from the general public’s perspective view as well as opinions about existing cloud providers, focusing on three main cloud providers: Azure, Amazon Web Services (AWS) and Google Cloud. The methodology used in this paper is based on sentiment analysis applied to the tweets that were extracted from social media platform (Twitter) via its search API. We have extracted a sample of 11,000 tweets and each cloud provider has almost similar proportion of the tweets based on relevant hashtags and keywords. Analysis starts by combining the tweets in order to find the overall polarity about cloud computing, then breaking the tweets to find the specific polarity for each cloud provider. Bing and NRC Lexicons are employed to measure the polarity and emotion of the terms in the tweets. The overall polarity classification of the tweets across all cloud providers shows 68.5% positive and 31.5% negative percentages. More specifically, Azure shows 63.8% positive and 36.2% negative tweets, Google Cloud shows 72.6% positive and 27.4% negative tweets and AWS shows 69.1% positive and 30.9% negative tweets.

The continuing advancements in microprocessor technologies are putting more and more computing power into small devices. Today smartphones are especially popular. Nevertheless, for resource intensive tasks such devices are still too constrained. However, the simultaneous trend of providing computing resources as a commodity on a pay-as-you-go basis (cloud computing) combined with such mobile devices facilitates interesting applications: Mobile clients can simply outsource resource intensive tasks to the cloud. Since clients have to pay a cloud provider (CP) for consumed resources, e.g. instance hours of virtual machines, clients may consider it as privacy intrusive that the CP is able to record the activity pattern of users, i.e. how often and how much resources are consumed by a specific client. In this paper we present a solution to this dilemma which allows clients to anonymously consume resources of a CP such that the CP is not able to track users' activity patterns. We present a scenario which integrates up-to-date security enhanced platforms as processing nodes and a recent cloud payment scheme together with a concrete implementation supporting the practicality of the proposed approach.

Cloud computing has evolved to emerge the most topical IT paradigm in recent times. Cloud computing is rapidly transforming the IT landscape. On a pay-as-you-use basis, cloud consumers can access resources, applications and infrastructure provided by cloud providers. Such access could be in form of applications already deployed by cloud providers for use by the cloud users. It could be in form of the capability to develop and deploy user applications using services of a cloud provider. In addition, massive storage infrastructure is available for database and data supplied by the user. The cloud has several unique architectures and many more are still evolving. The primary ones are the SaaS, PaaS and the IaaS that can be deployed on private, public, community and hybrid clouds. This paper examines present developments in the cloud computing architecture and presents guidance for additional research. Papers published in journals, conferences, white papers were analyzed. The objective of this present work is to identify, examine and explain the current trends and development in cloud computing architecture. However, only 13% of the papers examined discussed Others-as-a-Service, while only 26% of the papers reviewed considered issues relating to the major actors involved in cloud computing. This will beneficial to cloud providers, users, and researchers alike

Cloud provider is central processing with shared resources to serve the vendors on demand over the internet where, Cloud model is divided into deployment and service model. In this paper, we address the service model especially privacy where, the privacy allows customers to ensure that their data in cloud not access by unauthorized persons. We implement a novel approach called multi-level security using covert channel to achieve privacy through cloud computing (which we coin it MLSCPC) that enables cloud provider to protect user information from unauthorized persons. We use covert channel to enable cloud provider and customers to communicate in the existence of unauthorized people (e.g. attackers). We have developed a prototype of approach to evaluate its security, feasibility and performance. Our results show that cloud provider can grant customers resources in acceptable time and low computation overhead. Also, attackers don't affect our approach whereby, the cloud provider can grant resources to customers in existent of attackers.

Cloud computing is an emerging technology in the IT world. Some features of cloud, such as low cost, scalability, robustness and availability are attracting large-scale industries as well as small business towards cloud. A virtual machine (VM) can be defined as a software that can run its own operating systems and applications like an operating system in physical computer. As the number of users increases, allocation of resources and scheduling become a complex task. The optimization of VM provisioning policies offer improvement like increasing provider's profit, energy savings and load balancing in large data centres. In cloud computing when resource requirement of user's requests exceed resources limits of cloud provider, to fulfil the requests the cloud provider outsources to other cloud providers resources, this concept is known as cloud federation. In this paper we propose an algorithm for VM provisioning in federated cloud environment. The approach tries to improve the cloud providers profit. We have used the CloudSim to find-out the results and result show that how Cloud federation help to Cloud providers in order to improve its profit.

Cloud Computing has become in just few years a key consideration for businesses and governments willing to externalize their infrastructure, increase flexibility and reduce the cost of their infrastructure (CAPEX), maintenance and operation (OPEX). Although several commercial solutions are available, there are still numerous issues to solve. Two important aspects to address are the lock-in risk with one Cloud Provider (CP) and the fulfillment of the contractual SLA (Service Level Agreement). In this paper, we propose an integrated approach based on the concept of Broker that takes benefit from different CPs to efficiently embed a complex service into the various available cloud infrastructures. The Broker approach allows Cloud Customer (CC) to be independent from any particular CP while taking benefit from the overall available resources and avoid the lock-in with a particular one. In addition, we leverage the service model to provide Customers with the possibility to request different types of services (e.g. compound service) and propose a solution to fulfill requested Customer SLA in terms of availability, cost and geographic location according to the contracted SLA between the Broker and the CPs. We have implemented the solution in a lab cloud infrastructure and performed several tests and simulations to highlight the benefit of our approach.

Cloud computing has emerged as a new computing paradigm, with provisioning model generally consisting of cloud service providers (CSPs), network service providers (NSPs), and end users. The associated economics has opened up a new research area; and with the expansion of the cloud computing market, the relationship between CSPs and NSPs, is changing profoundly. In addition to providing the default network services, traditional NSPs, in attempt to compete with CSPs, have started offering cloud services to end users. Though much progress has been made toward addressing competitions among CSPs themselves or among NSPs themselves, few studies have focused on the competition between CSPs and NSPs. In this paper, we investigate the problem of insufficient studies on the competition between CSPs and NSPs by presenting a new economic model to characterize the competition between CSPs and NSPs, and by conducting thorough theoretical analysis as well as numeric experiments to validate the proposed model. We believe, based on results, that the proposed economic model is general and feasible, and thus is applicable to modeling the competition among service providers in cloud computing market.

Elasticity is a key feature in cloud computing, and perhaps what distinguishes it from other computing paradigms. Despite the advantages of elasticity, realizing its full potential is hard due to multiple challenges stemming from the need to estimate workload demand. A desirable solution would require predicting system workload and allocating resources a priori, i.e., A predictive approach. Instead, what is mainly available are reactive solutions, requiring difficult parameter tuning. Since each Cloud Provider (CP) has its own implementation idiosyncrasies, it's impossible for developers to: (i) learn only about one platform and re-use that knowledge in others, (ii) migrate developed elasticity solutions between different CPs, and (iii) to develop reusable predictive elasticity rules or algorithms. This paper makes three contributions to provide an effective elasticity environment. First, Vadara, a totally generic elasticity framework, that transparently connects and abstracts several CPs API behaviour, and enables the use of pluggable CP-agnostic elasticity strategies. Second, it presents a predictive workload forecasting approach, which ensembles several individual forecasting methods, and introduces a padding system based on the most recent prediction errors for both under- and over-provisioning. Finally, results show (1) Vadara's successful connection to well-known CPs, (2) the improvements made regarding under- and over-provisioning due to our padding system, and (3) the effectiveness of our ensemble forecasting technique.

The advance of edge computing pushes computing functionalities to the network edge and brings lucrative opportunities for edge operators (EOs) to cater the users with low latency requirement. Unlike in cloud computing, edge servers have limited computing capacity and require a proper resource planning. To avoid loss of potential profit, a promising way is to outsource cloud resources from a public cloud with additional cost when the edge computing capacity is insufficient to meet the real-time demands. Besides, the uncertainty of future demands also affects EOs' profits. It's essential to consider the interaction among market participants with different risk attitudes. To this end, we study multiple risk-averse EOs with one risk-neutral Cloud Provider (CP) in an edge computing market, where each EO competes to serve the users by determining the optimal resource provision strategies given the demand and the outsource price charged by the CP, and the CP sets the price based on the best responses of the EOs. We model the interaction between EOs and CP as a two stage Stackelberg game, and employ a data-driven optimization approach to characterize the uncertainty. We explore the existence and uniqueness of subgame Nash equilibrium, and find the equilibrium based on the Sample Average Approximation (SAA) method. Extensive simulations using real-world cluster data traces verify the effectiveness of the proposed method.

Multiprocessor systems are increasingly becoming the systems of choice for low and high-end servers, running such diverse tasks as number crunching, large-scale simulations, data base engines and world wide web server applications. With such diverse workloads, system utilization and throughput, as well as execution time become important performance metrics. In this paper we present efficient kernel scheduling policies and propose a new kernel-user interface aiming at supporting efficient parallel execution in diverse workload environments. Our approach relies on support for user level threads which are used to exploit parallelism within applications, and a two-level scheduling policy which coordinates the number of resources allocated by the kernel with the number of threads generated by each application. We compare our scheduling policies with the native gang scheduling policy of the IRIX 6.4 operating system on a Silicon Graphics Origin2000. Our experimental results show substantial performance gains in terms of overall workload execution times, individual application execution times, and cache performance.