Application Level Interoperability between Clouds and Grids

Abstract—SAGA is a high-level programming interface which provides the ability to develop distributed applications in an infrastructure independent way. In an earlier paper, we discussed how SAGA was used to develop a version of MapReduce which provided the user with the ability to control the relative placement of compute and data, whilst utilizing different distributed infras-tructure. In this paper, we use the SAGA-based implementation of MapReduce, and demonstrate its interoperability across Clouds and Grids. We discuss how a range of cloud adaptors have been developed for SAGA. The major contribution of this paper is the demonstration – possibly the first ever, of interoperability between different Clouds and Grids, without any changes to the application. We analyse the performance of SAGA-MapReduce when using multiple, different, heterogeneous infrastructure concurrently for the same problem instance; However, we do not strive to provide a rigorous performance model, but to provide a proof-of-concept of application-level interoperability and illustrate its importance. I

Information standards to support application and enterprise interoperability for the smart grid

Copyright @ 2012 IEEE.Current changes in the European electricity industry are driven by regulatory directives to reduce greenhouse gas emissions, at the same time as replacing aged infrastructure and maintaining energy security. There is a wide acceptance of the requirement for smarter grids to support such changes and accommodate variable injections from renewable energy sources. However the design templates are still emerging to manage the level of information required to meet challenges such as balancing, planning and market dynamics under this new paradigm. While secure and scalable cloud computing architectures may contribute to supporting the informatics challenges of the smart grid, this paper focuses on the essential need for business alignment with standardised information models such as the IEC Common Information Model (CIM), to leverage data value and control system interoperability. In this paper we present details of use cases being considered by National Grid, the GB transmission system operator for information interoperability in pan-network system management and planning.This study is financially supported by the National Grid, UK

Integrating data from 3D CAD and 3D cameras for Real-Time Modeling

In a reversal of historic trends, the capital facilities industry is expressing an increasing desire for automation of equipment and construction processes. Simultaneously, the industry has become conscious that higher levels of interoperability are a key towards higher productivity and safer projects. In complex, dynamic, and rapidly changing three-dimensional (3D) environments such as facilities sites, cutting-edge 3D sensing technologies and processing algorithms are one area of development that can dramatically impact those projects factors. New 3D technologies are now being developed, with among them 3D camera. The main focus here is an investigation of the feasibility of rapidly combining and comparing – integrating – 3D sensed data (from a 3D camera) and 3D CAD data. Such a capability could improve construction quality assessment, facility aging assessment, as well as rapid environment reconstruction and construction automation. Some preliminary results are presented here. They deal with the challenge of fusing sensed and CAD data that are completely different in nature

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

An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure