Interoperability standards for cloud architecture

Enabling cloud infrastructures to evolve into a transparent platform raises interoperability issues. Interoperability requires standard data models and communication technologies compatible with the existing Internet infrastructure. To reduce vendor lock-in situations, cloud computing must implement common strategies regarding standards, interoperability and portability. Open standards are of critical importance and need to be embedded into interoperability solutions. Interoperability is determined at the data level as well as the service level. Relevant modelling standards and integration solutions shall be analysed in the context of clouds

A look at cloud architecture interoperability through standards

Enabling cloud infrastructures to evolve into a transparent platform while preserving integrity raises interoperability issues. How components are connected needs to be addressed. Interoperability requires standard data models and communication encoding technologies compatible with the existing Internet infrastructure. To reduce vendor lock-in situations, cloud computing must implement universal strategies regarding standards, interoperability and portability. Open standards are of critical importance and need to be embedded into interoperability solutions. Interoperability is determined at the data level as well as the service level. Corresponding modelling standards and integration solutions shall be analysed

An Implementation of Divide and Conquer Clustering Technique for Improving the Interoperability in Hybrid Cloud Environment

Cloud computing provides users with pool of resources ubiquitously on demand. While the resources are provided to the users, interoperability needs to be considered. Interoperability is the ability of the cloud environment to transfer the data internally or between the data centers seamlessly. Interoperability is the least studied issue in the field of cloud computing. This paper implements hybrid cloud as a solution to interoperability. Hybrid cloud is chosen for its powerful combination of high configured and secured private clouds and fast accessible and scalable public clouds. The interoperability is then proposed to be enhanced by implementing divide and conquer algorithm of clustering in hybrid cloud

Cloud Abstraction Libraries: Implementation and Comparison

Vendor lock-in makes it difficult for an organization to port their services, application or data. Cloud providers are in race to provide the best-in-class storage, networking and compute resources. Many organizations are moving towards micro-services and cloud services architecture. It is very important for an infrastructure platform to offer a high-quality cloud computing environment consistently across multiple cloud platforms. To enable this, a collaborative yet an independent cloud abstraction service is required. The cloud abstraction library should support the basic use cases of delivery pipeline, service management, cloud operations and security service. Cloud interoperability standards helps to improve availability and scalability by providing cross organizational or vendor independent projects. An important aspect of cloud interoperability is development of standardized APIs to send and receive data, irrespective of the underlying cloud implementation. Cloud interoperability helps application and data portability between public clouds and private clouds. This thesis explores the role of open source libraries to use cloud specific features. Our work is to qualitatively and quantitatively evaluate Dasein cloud and jClouds against Amazon EC2 and Google Compute Engine. We believe that cloud standardization can be accelerated by implementations based on open source and open standards

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Assessing and Improving Interoperability of Distributed Systems

Interoperabilität von verteilten Systemen ist eine Grundlage für die Entwicklung von neuen und innovativen Geschäftslösungen. Sie erlaubt es existierende Dienste, die auf verschiedenen Systemen angeboten werden, so miteinander zu verknüpfen, dass neue oder erweiterte Dienste zur Verfügung gestellt werden können. Außerdem kann durch diese Integration die Zuverlässigkeit von Diensten erhöht werden. Das Erreichen und Bewerten von Interoperabilität stellt jedoch eine finanzielle und zeitliche Herausforderung dar. Zur Sicherstellung und Bewertung von Interoperabilität werden systematische Methoden benötigt. Um systematisch Interoperabilität von Systemen erreichen und bewerten zu können, wurde im Rahmen der vorliegenden Arbeit ein Prozess zur Verbesserung und Beurteilung von Interoperabilität (IAI) entwickelt. Der IAI-Prozess beinhaltet drei Phasen und kann die Interoperabilität von verteilten, homogenen und auch heterogenen Systemen bewerten und verbessern. Die Bewertung erfolgt dabei durch Interoperabilitätstests, die manuell oder automatisiert ausgeführt werden können. Für die Automatisierung von Interoperabilitätstests wird eine neue Methodik vorgestellt, die einen Entwicklungsprozess für automatisierte Interoperabilitätstestsysteme beinhaltet. Die vorgestellte Methodik erleichtert die formale und systematische Bewertung der Interoperabilität von verteilten Systemen. Im Vergleich zur manuellen Prüfung von Interoperabilität gewährleistet die hier vorgestellte Methodik eine höhere Testabdeckung, eine konsistente Testdurchführung und wiederholbare Interoperabilitätstests. Die praktische Anwendbarkeit des IAI-Prozesses und der Methodik für automatisierte Interoperabilitätstests wird durch drei Fallstudien belegt. In der ersten Fallstudie werden Prozess und Methodik für Internet Protocol Multimedia Subsystem (IMS) Netzwerke instanziiert. Die Interoperabilität von IMS-Netzwerken wurde bisher nur manuell getestet. In der zweiten und dritten Fallstudie wird der IAI-Prozess zur Beurteilung und Verbesserung der Interoperabilität von Grid- und Cloud-Systemen angewendet. Die Bewertung und Verbesserung dieser Interoperabilität ist eine Herausforderung, da Grid- und Cloud-Systeme im Gegensatz zu IMS-Netzwerken heterogen sind. Im Rahmen der Fallstudien werden Möglichkeiten für Integrations- und Interoperabilitätslösungen von Grid- und Infrastructure as a Service (IaaS) Cloud-Systemen sowie von Grid- und Platform as a Service (PaaS) Cloud-Systemen aufgezeigt. Die vorgestellten Lösungen sind in der Literatur bisher nicht dokumentiert worden. Sie ermöglichen die komplementäre Nutzung von Grid- und Cloud-Systemen, eine vereinfachte Migration von Grid-Anwendungen in ein Cloud-System sowie eine effiziente Ressourcennutzung. Die Interoperabilitätslösungen werden mit Hilfe des IAI-Prozesses bewertet. Die Durchführung der Tests für Grid-IaaS-Cloud-Systeme erfolgte manuell. Die Interoperabilität von Grid-PaaS-Cloud-Systemen wird mit Hilfe der Methodik für automatisierte Interoperabilitätstests bewertet. Interoperabilitätstests und deren Beurteilung wurden bisher in der Grid- und Cloud-Community nicht diskutiert, obwohl sie eine Basis für die Entwicklung von standardisierten Schnittstellen zum Erreichen von Interoperabilität zwischen Grid- und Cloud-Systemen bieten.Achieving interoperability of distributed systems offers means for the development of new and innovative business solutions. Interoperability allows the combination of existing services provided on different systems, into new or extended services. Such an integration can also increase the reliability of the provided service. However, achieving and assessing interoperability is a technical challenge that requires high effort regarding time and costs. The reasons are manifold and include differing implementations of standards as well as the provision of proprietary interfaces. The implementations need to be engineered to be interoperable. Techniques that assess and improve interoperability systematically are required. For the assurance of reliable interoperation between systems, interoperability needs to be assessed and improved in a systematic manner. To this aim, we present the Interoperability Assessment and Improvement (IAI) process, which describes in three phases how interoperability of distributed homogeneous and heterogeneous systems can be improved and assessed systematically. The interoperability assessment is achieved by means of interoperability testing, which is typically performed manually. For the automation of interoperability test execution, we present a new methodology including a generic development process for a complete and automated interoperability test system. This methodology provides means for a formalized and systematic assessment of systems' interoperability in an automated manner. Compared to manual interoperability testing, the application of our methodology has the following benefits: wider test coverage, consistent test execution, and test repeatability. We evaluate the IAI process and the methodology for automated interoperability testing in three case studies. Within the first case study, we instantiate the IAI process and the methodology for Internet Protocol Multimedia Subsystem (IMS) networks, which were previously assessed for interoperability only in a manual manner. Within the second and third case study, we apply the IAI process to assess and improve the interoperability of grid and cloud computing systems. Their interoperability assessment and improvement is challenging, since cloud and grid systems are, in contrast to IMS networks, heterogeneous. We develop integration and interoperability solutions for grids and Infrastructure as a Service (IaaS) clouds as well as for grids and Platform as a Service (PaaS) clouds. These solutions are unique and foster complementary usage of grids and clouds, simplified migration of grid applications into the cloud, as well as efficient resource utilization. In addition, we assess the interoperability of the grid-cloud interoperability solutions. While the tests for grid-IaaS clouds are performed manually, we applied our methodology for automated interoperability testing for the assessment of interoperability to grid-PaaS cloud interoperability successfully. These interoperability assessments are unique in the grid-cloud community and provide a basis for the development of standardized interfaces improving the interoperability between grids and clouds

Security and Privacy Issues in Cloud Computing

Cloud computing transforming the way of information technology (IT) for consuming and managing, promising improving cost efficiencies, accelerate innovations, faster time-to-market and the ability to scale applications on demand (Leighton, 2009). According to Gartner, while the hype grew ex-ponentially during 2008 and continued since, it is clear that there is a major shift towards the cloud computing model and that the benefits may be substantial (Gartner Hype-Cycle, 2012). However, as the shape of the cloud computing is emerging and developing rapidly both conceptually and in reality, the legal/contractual, economic, service quality, interoperability, security and privacy issues still pose significant challenges. In this chapter, we describe various service and deployment models of cloud computing and identify major challenges. In particular, we discuss three critical challenges: regulatory, security and privacy issues in cloud computing. Some solutions to mitigate these challenges are also proposed along with a brief presentation on the future trends in cloud computing deployment

ooi: OpenStack OCCI interface

In this document we present an implementation of the Open Grid Forum’s Open Cloud Computing Interface (OCCI) for OpenStack, namely ooi (Openstack occi interface, 2015). OCCI is an open standard for management tasks over cloud resources, focused on interoperability, portability and integration. ooi aims to implement this open interface for the OpenStack cloud middleware, promoting interoperability with other OCCI-enabled cloud management frameworks and infrastructures. ooi focuses on being non-invasive with a vanilla OpenStack installation, not tied to a particular OpenStack release version

Component-wise application migration in bidimensional cross-cloud environments

We propose an algorithm for the migration of cloud applications' components between different providers, possibly changing their service level between IaaS and PaaS. Our solution relies on three of the key ingredients of the trans-cloud approach: a unified API, agnostic topology descriptions, and mechanisms for the independent specification of providers. We show how our approach allows us to overcome some of the current interoperability and portability issues of cloud environments to propose a solution for migration, present an implementation of our proposed solution, and illustrate it with a case study and experimental results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech