CloudLaunch: Discover and deploy cloud applications

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 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.

In multi-tenant collaborative cloud systems, the choice of cloud providers is based on pre-negotiated terms and conditions to help meet Service Level Agreements (SLAs) and streamline resource provisioning. However, these collaborations are not self-adaptive to accommodate changes in tenancy requirements, quality of resources and provider capabilities as provider collaborations remain static over tenancy period. In our paper, we present an approach towards achieving self-adaptive cloud collaborations. Our model selects the best possible cloud collaborations from amongst multiple possible dependent cloud provider collaboration links. The formation of cloud provider collaborations is broadly based on cloud provider capabilities, tenancy requirements, cost modeling of each cloud provider andits functional ability at the Software as a Service (SaaS) layer. We present an algorithm to form dynamic cloud collaborations and thereby determine the most appropriate linkages within the providers. We also illustrate our approach throughout our paper with a realistic running example, and present detailed experimental evaluation via a proof-of-concept prototype implementation.

More and more companies rely on cloud services to provide their online software solutions. Cloud services are offered by a multitude of providers, each of them offering services through proprietary, mostly incompatible interfaces. Developing applications employing these specific interfaces can create the vendor lock-in problem (i.e the application is tightly coupled to the underlying cloud provider). Consequently, such applications cannot be ported without incurring significant costs and time delay. A cloud services consumer can decide to switch to a different cloud provider based on different criteria such as changes in business requirements, continuously evolving offerings from cloud providers and costs control. Maintaining the flexibility to change cloud providers in an efficient way can be a challenging task. We propose an efficient model-driven framework for cloud application portability. Our approach enables applications consuming REST resources in the cloud to be transferred to different cloud providers without the need to refactor the applications. The framework supports a wide range of cloud resources. The framework produces an intermediation layer which translates the calls between the format of the initial cloud platform and the new target cloud platform. The intermediation layer can be consumed by any programming language. We demonstrate that cloud application portability can be achieved. Our solution successfully maps cloud-based services with an overall median of 100% for requests, and 74.8% for responses. Furthermore, we show that the intermediation layer introduces minimal additional latency.

Cloud Computing builds on the latest achievements of diverse research areas, such as Grid Computing, Service-oriented computing, business process modeling and virtualization. As this new computing paradigm was mostly lead by companies, several proprietary systems arisen. Recently, alongside these commercial systems, several smaller-scale privately owned systems are maintained and developed. In this paper we present our research results performed within the S-Cube European FP7 NoE project to enable automated service provisioning for users on a highly dynamic infrastructure consisting of multiple Cloud providers. We developed a Federated Cloud Management architecture that provides unified access to a federated Cloud that aggregates multiple heterogeneous IaaS Cloud providers in a transparent manner. We have also incorporated an integrated monitoring approach that enables more reliable provider selection in these heterogeneous environments.

Service composition in multi-Cloud environments must coordinate self-interested participants, automate service selection, (re)configure distributed services, and deal with incomplete information about Cloud providers and their services. This work proposes an agent-based approach to compose services in multi-Cloud environments for different types of Cloud services: one-time virtualized services, e.g., processing a rendering job, persistent virtualized services, e.g., infrastructure-as-a-service scenarios, vertical services, e.g., integrating homogenous services, and horizontal services, e.g., integrating heterogeneous services. Agents are endowed with a semi-recursive contract net protocol and service capability tables (information catalogs about Cloud participants) to compose services based on consumer requirements. Empirical results obtained from an agent-based testbed show that agents in this work can: successfully compose services to satisfy service requirements, autonomously select services based on dynamic fees, effectively cope with constantly changing consumers' service needs that trigger updates, and compose services in multiple Clouds even with incomplete information about Cloud participants.

Now, many users have stored files on multiple clouds, and sometime, a large number of files are migrated between clouds. Because cloud providers and cloud servers are not entirely trusted, the corruption of user’s files event occur from time to time during the processes of storage and migration. Therefore, integrity verification must be performed, and the time verification overhead should be as low as possible. The existing provable data migrate methods still have the issue of high time overhead when a large number of files are migrated. Aiming at this problem, this paper proposed a hierarchical provable data migration method, which can provide the efficiency of data transfer integrity verification when moving large number of continuous files between clouds. In this paper, the proposed method is described in detail as well as the security analysis performance evaluation. The results proved that the proposed method can significantly decrease the detection latency of files transfer between clouds.

The competition between cloud providers has led to an impressive set of cloud solutions offered to consumers. The ability to properly design and deploy multi-cloud applications (i.e., Applications deployed on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence optimizing the performance and cost of the applications. However, this is hindered by the large heterogeneity of the existing cloud offerings. In this work, we present the model-driven methodology and tools developed within the MODA Clouds European project to support the design of multi-cloud applications. In particular, the proposed framework promotes a model driven approach to help reducing vendor "lock-in", support multi-cloud deployments, and provide solutions for estimating and optimizing the performance of multi-cloud applications at design-time.

In today's cloud service market, different providers have very different low-level mechanisms to accommodate various types of policies from their users. Enforcement of policies over multiple cloud provider domains is an intrinsically complex problem for both sides. In reality, cloud providers have to either manually update enforcement mechanisms or negotiate adjusted policies with their users for enforcement. To save these high-cost and error-prone manual updates or adjustments, an automatic and flexible solution is desired. This paper proposes a semantic modeling and mapping based approach to help enforce high-level user policies across cloud domain boundaries when applications or IT operations have to span over multiple cloud domains. This approach creates policy models and maps these models across cloud domain boundaries automatically or semi-automatically. Policy rules following these mappings can be tied to multiple enforcement mechanisms in different cloud domains. If a rule cannot be mapped, a manual adjustment solution will be suggested. A case study is also included to demonstrate the efficiency and accuracy of this approach.

With the emergence of cloud computing, users are increasingly using storage services of cloud providers to satisfy their storage needs. However, these cloud providers are not 100% reliable, resulting in periodic service outages. End users require a solution that minimizes the impact of cloud service outages and optimizes the chances of successfully retrieving stored objects in cases of provider failures. In this paper, we propose to build a federated cloud agent, enabling end users to simultaneously deploy storage objects to multiple cloud service providers, based on their unit storage costs and failure probabilities. We study two service provider failure models: the first case assumes that at most one service provider fails at any given time, and the second case assumes that cloud service providers may fail independently with certain probabilities. We cast both scenarios as constrained optimization problems to minimize the overall storage cost while enhancing the chances of recovering all the storage objects in case of service outages. In the experiments, we evaluated the proposed optimal storage schemes against a fixed server deployment strategy and find our schemes can achieve good recovery ratios, while incurring minimal storage costs.

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.

To reduce the increasing cost of building and operating cloud data centers, cloud providers are seeking various mechanisms to achieve higher resource effectiveness. For example, cloud operators are leveraging dynamic resource management techniques to consolidate a higher density of application workloads into commodity physical servers to maximize server resource utilization. However, higher workload density is a major source of performance interference problems in multi-tenant clouds. Existing performance isolation techniques such as dedicated CPU cores for specific workloads are not enough as there are still common resource (e.g., last-level cache and memory bandwidth in memory subsystem) on the processor that are shared among all CPUs on the same NUMA node. While prior work has proposed a variety of resource partitioning techniques, it still remains unexplored to characterize the impact of memory subsystem resource partitioning for the consolidated workloads with different priorities and investigate software support to dynamically manage memory subsystem resource sharing in a real-time manner. To bridge the gap, we propose Themis, a feedback-based controller that enables a priority-aware and fairness-aware memory subsystem resource management strategy to guarantee the performance of high-priority workloads while maintaining fairness across all colocated workloads in high-density clouds. Themis is evaluated with multiple typical cloud applications in our data center environment. The results show that Themis improves the performance of various workloads by up to 3.15%, and fairness by more than 70% in memory subsystem resource allocation compared to existing state-of-the-art work.

Cloud computing providers such as Amazon and Google have recently begun offering container-instances, which provide an efficient route to application deployment within a lightweight, isolated and well-defined execution environment. Cloud providers currently offer Container Service Platforms (CSPs), which orchestrate containerised applications. Existing CSP frameworks do not offer any form of intelligent resource scheduling: applications are usually scheduled individually, rather than taking a holistic view of all registered applications and available resources in the cloud. This can result in increased execution times for applications, resource wastage through underutilised container-instances, and a reduction in the number of applications that can be deployed, given the available resources. The research presented in this paper aims to extend existing systems by adding a cloud-based Container Management Service (CMS) framework that offers increased deployment density, scalability and resource efficiency. CMS provides additional functionalities for orchestrating containerised applications by joint optimisation of sets of containerised applications, and resource pool in multiple (geographical distributed) cloud regions. We evaluated CMS on a cloud-based CSP i.e., Amazon EC2 Container Management Service (ECS) and conducted extensive experiments using sets of CPU and Memory intensive containerised applications against the direct deployment strategy of Amazon ECS. The results show that CMS achieves up to 25% higher cluster utilisation, and up to 70% reduction in execution times.

In the world of computer networking, cloud computing makes a technical shift of computing services being provided locally to being provided remotely by third party service providers. The data which was previously kept under control of users now under the control of service providers cloud computing brings many financial and functional benefits as well as serious security concerns that may threaten business continuity and corporate reputation. The definition of cloud computing is still blurry in a large part, because of the magnitude of the security risks and the virtually unlimited amount of information being published over the unsecure platform. The purpose of this paper is to assess how security risk factors are affecting the existing and prospective cloud users’ cloud usage strategies. Are they simply betting that financial benefits will surpass security risks, or are they confident that cloud providers are capable of assuring an equal or higher level of security than on-premise systems? This survey, through the examination of published materials and studies, analyzes existing issues along with available countermeasures in order to evaluate the overall assurance level of cloud security. The primary goal of the survey is to assess how security concerns have affected or will affect the respondents’ decision on adopting cloud and its services. This study includes basics of cloud computing by adding its characteristics, models and their categories. Analysis also embraced the existing security concerns faced by researchers and their imposed methodologies.

As the volume of digital data rapidly increases, storage clouds are becoming a popular solution for both enterprise and personal data, and the number of storage cloud solutions is also increasing. However, these solutions do not yet deal with the need of customers for interoperability and data migration from one cloud to another. These issues can be addressed through federation of cloud infrastructures. An important aspect of federation is delegation of access control, where one actor, e.g., an end user, authorizes another actor, e.g., a cloud provider, to act on its behalf, typically with a subset of its access rights, safely and securely. This paper deals with delegation across storage clouds. We describe a delegation architecture for on-boarding federation, which allows an enterprise to efficiently migrate its data from one storage cloud provider to another (e.g., for business or legal reasons), while providing continuous access and a unified view over the data during the migration. In our architecture a user delegates a subset of his access rights on the source and destination clouds to an on-boarding federation layer on the destination cloud. This enables on-boarding to occur in a safe and secure way, such that the on-boarding layer has the least privilege required to carry out its work. We evaluate the security implications of delegation that need to be taken into account for on-boarding. We also show how the delegation architecture can be implemented using the Security Assertion Markup Language.