Integrating Business Intelligence Services in the Cloud

Business Intelligence (BI) solutions are among the popular applications that businesses demand in the Cloud. Although Business Intelligence functionality is already provided in the Cloud, vendors concentrate on providing existing products like Software as a Service, ignoring changing business and provisioning models of software. Business Intelligence functionality provided in the Cloud is lacking important integration features needed by other Cloud-based applications. While a simple upload of the data to be analyzed into a Cloud-based BI solution is already possible and well established, the visualization of the results and the interactive parts of the analysis are always provided inside the Cloud-based BI solution itself. However, as this chapter shows, common usage scenarios of integrated Cloud applications demand an integration of the analysis reports from BI applications into the user interface of other Cloud-based applications. This chapter describes how a fully integrated Cloud-based BI solution can collaborate with other Cloud-based applications. The technical concept illustrated with an example delineates how the required interface can be provided.

Resource Provisioning in the Cloud

It is a challenge to provision and allocate resources in the Cloud so as to meet both the performance and cost goals of Cloud users. For a Cloud consumer, the ability to acquire and release resources dynamically and trivially in the Cloud, while being a powerful and useful aspect, complicates the resource provisioning and allocation task in the Cloud. While on the one hand, resource under-provisioning may hurt application performance and deteriorate service quality; on the other hand, resource over-provisioning could cost users more and offset Cloud advantages. Although resource management and job scheduling have been studied extensively in the Grid environments and the Cloud shares many common features with the Grid, the mapping from user objectives to resource provisioning and allocation in the Cloud has many challenges due to the seemingly unlimited resource pools, virtualization, and isolation features provided by the Cloud. This chapter focuses on surveying the research trends in resource provisioning in the Cloud based on several factors such as the type of the workload, the VM heterogeneity, data transfer requirements, solution methods, and optimization goals and constraints, and attempts to provide guidelines for future research.

Dynamic Reconfiguration of Component-Based Systems

Component-based approaches generalize basic object-oriented implementations by allowing large collections of objects to be grouped together and externalized in terms of public interfaces. A typical component-based system will include a large number of interacting components. Service-Oriented Architecture (SOA) organizes a system in terms of components that communicate via services. Components publish services that they implement as business processes. Consequently, a change to a single component can have a ripple effect on the service-driven system. Component reconfiguration is motivated by the need to evolve the component architecture and can take a number of forms. The authors define a dynamic architecture as one that supports changing the behavior and topology of existing components without stopping, updating, and redeploying the system. This chapter addresses the problem of dynamic reconfiguration of component-based architectures. It proposes a reification approach that represents key features of a language in data, so that a system can reason and dynamically modify aspects of it. The approach is described in terms of a new language called µLEAP and validated by implementing a simple case study.

Dynamically Reconfigurable Architectures

Dynamic aspects of behavior of software systems in dynamically reconfigurable runtime architectures can result in significant architectural violations during runtime. In such cases, a system's architecture evolves during the runtime according to the actual state of the system's environment, and consequently, runtime reconfigurations may eventually lead to incorrect architecture configurations that were not considered during the system's design phases. These architectural violations are known as architectural erosion or architectural drift, and they contribute to an increasing brittleness of the system, or a lack of its coherence and clarity of its form. This chapter describes and compares possible measures to prevent architectural violations in dynamic service and component models. The aim of this chapter is to evaluate the applicability of those measures in combination with advanced features of reconfigurable runtime architectures such as ad hoc reconfiguration, service or component mobility, composition hierarchy preservation, and architectural aspects.

Discovering Services in Mobile Environments

Mobile services have gained in importance for their ability to be consumed by mobile users regardless of their location. Mobile consumers are exposed to a large pool of services such as location-based applications, medical information, financial management, investments, and more. However, mobile service discovery needs further research to efficiently and effectively support mobility-related constraints such as availability, heterogeneity, and resource constrained devices. In this chapter, the authors define several criteria relating to mobile service discovery and categorize state-of-the-art service discovery approaches according to those criteria while paying particular attention to architectural choices, service description, and service discovery using semantic and reasoning techniques. The authors evaluate the approaches to identify their advantages and shortcomings and propose guidelines for future research for service discovery in mobile environments.

Admission Control in the Cloud

Cloud computing is a paradigm that allows the flexible and on-demand provisioning of computing resources. For this reason, many institutions and enterprises have moved their data centers to the Cloud and, in particular, to public infrastructures. Unfortunately, an increase in the demand for Cloud results in resource shortages affecting both providers and consumers. With this factor in mind, Cloud service providers need Admission Control algorithms in order to make a good business decision on the types of requests to be fulfilled. Cloud providers have a desire to maximize the net income derived from provisioning the accepted service requests and minimize the impact of unprovisioned resources. This chapter introduces and compares Admission Control algorithms and proposes a service model that allows the definition of Service Level Agreements for the Cloud.

Cloud Service Brokerage

Cloud service brokerage has been identified as a key concern for future Cloud technology research and development. Integration, customization, and aggregation are core functions of a Cloud service broker. The need to cater to horizontal and vertical integration in service description languages, horizontally between different providers and vertically across the different Cloud layers, has been well recognized. In this chapter, the authors propose a conceptual framework for a Cloud service broker in two parts: first, a reference architecture for Cloud service brokers; and second, a rich ontology-based template manipulation framework and operator calculus that describes the mediated and integrated Cloud services, facilitates manipulating their descriptions, and allows both horizontal and vertical dimensions to be covered. Structural aspects of that template are identified, formalized in an ontology, and aligned with the Cloud development and deployment process.

Integrating Compliance Management in Service-Driven Computing

The lack of effective controls over organizational business processes can cause serious consequences for a company's reputation and even jeopardize its existence. There is a need for continuous monitoring of controls and systematic collection and evaluation of relevant data. Compliance management is essential for ensuring that organizational business processes and supporting information system are in compliance with laws, regulations, and various legislative or technical documents pertaining to the place of business. The focus of this chapter is to provide an insight into compliance management and discuss the integration and automation of compliance management in service-driven computing. The chapter elaborates conceptual models for specifying compliance requirements originating from various sources and details aspects such as multi-view process modeling annotated with compliance requirements, annotation of service interfaces and behavioral characteristics, development and reuse of compliant process fragments, architectural patterns to simplify compliance management, and abstract frameworks to ensure compliance in the context of service-driven computing through service adaptation and runtime governance. Finally, approaches to automating compliance management through formalization of compliance requirements, rule- and event-based monitoring, and integration of compliance governance systems with automated reasoning and verification tools are detailed.

Legacy Software Integration in Service-Driven Environments

Maintaining and upgrading legacy systems is one of the challenges many enterprises face today. Despite their obsolescence, legacy systems continue to provide a competitive advantage by supporting unique business processes and acting as a repository for invaluable knowledge and historical data. However, enterprises would prefer to develop their applications with modern software technology instead of continuing to develop in the mainframe but leverage existing business processes and data from their legacy systems. This chapter presents an architectural framework and implementation methodology of a Central Intelligent Agent that is responsible for legacy integration. The framework uses an Enterprise Service Bus for service integration and agents to handle services. The Central Intelligent Agent uses a Prolog-style rule-based engine and context awareness for service handling and a complementary service agent on the mainframe side for legacy integration. The underlying framework provides a full set of functions to integrate legacy COBOL applications as services into the system without any programming effort in COBOL. The proposed technique enables fast prototyping and rapid development in an agile development process. It also facilitates legacy migration through successive and iterative processes.

A Semantically Enabled Service Delivery Platform

It is expected that virtual factories and enterprises of the future will be able to self-organize in distributed, autonomous, interoperable, non-hierarchical, innovation ecosystems and be dynamically delivered as services, end-to-end along the global value chain. In this scenario, services and service ecosystems become central artifacts, and it is necessary to model and manage them appropriately for automation and scalability. Two main popular architectural approaches for realizing service orientation are WSDL-based SOA and the RESTful style. The level of automation offered by these approaches is limited, and human intervention is required in order to achieve most of the service-related tasks such as discovery, ranking, invocation, and monitoring. In order for service-oriented technologies to scale, they need to offer a significant degree of automation. To address the scalability issues in service composition, this chapter proposes a semantically enabled service-oriented architectural approach (SESA) and its implementation in the form of a platform. The authors detail the principles, models, architecture, and implementation underlying the approach in which lightweight semantics play a central role.