For many years mobile devices were commonly recognized as Web consumers. However, the advancements in mobile device manufacturing, coupled with the latest achievements in wireless communication developments are both key enablers for shifting the role of mobile devices from service consumers to service providers. This paradigm shift is a major step towards the realization of pervasive and ubiquitous computing. Mobile Web service provisioning is the art of hosting and offering Web services from mobile devices, which actively contributes towards the direction of Mobile Internet. In this paper, we provide the state of the art of mobile service provisioning as it currently stands. We focus our discussions on its applicability, reliability, and challenges of mobile environments and resource constraints. We study the different provisioning architectures, enabler technologies, publishing and discovery mechanisms, and maintenance of up-to-date service registries. We point out the major open research issues in each provisioning aspect. Performance issues due to the resource constraints of mobile devices are also discussed.
Multidatabase systems (MDBSs) provide applications with integrated access to a collection of databases. The component database systems are typically heterogeneous, distributed, autonomous and pre-existing. MDBSs, like conventional database management systems (DBMSs), require catalogue information to provide their services. The catalogue must be stored in a separate system database, or repository, since component databases are assumed to be independent of the MDBS. We examine the approach taken to catalogue management in the CORDS MDBS which uses an X.500 directory service to store the MDBS catalogue and discuss the advantages and disadvantages of this approach. Storing the MDBS catalogue in a directory service is an appealing approach but is an application for which the directory service was never intended. There are, therefore, practical problems which must be addressed including the suitability of the information model and the performance of the system for typical repository requests. We discuss the design of the CORDS MDBS catalogue and present a set of experiments we conducted with it to examine the performance and scalability of the approach.
Computer system sizing involves estimating the amount of hardware resources needed to support a new workload not yet deployed in a production environment. In order to determine the type and quantity of resources required, a methodology is required for describing the new workload. In this paper, we discuss the sizing process for database management systems and describe an analysis for characterizing business intelligence (BI) workloads, using the TPC-H benchmark as our workload basis. The characterization yields four general classes of queries, each with different characteristics. Our approach for sizing a BI application's database tier quantifies a new BI workload in terms of the response time goals and mix of the different query classes obtained from the characterization analysis.
Advances in Information and Communication Technology (ICT) have enabled the provisioning of more cost-efficient means of delivering healthcare services through electronic healthcare systems (e-health). However, these solutions have constrained the mobility of medical professionals as well as patients. Mobile devices have been sought as a potential solution to free medical professionals and patients from mobility constraints. This chapter discusses the literature proposed in multimedia data transfer and retrieval, utilizing mobile devices and a multitude of wireless access technologies. A background section presents the different software technologies utilized by the proposed work, as well as a literature review. Following that, the authors compare these proposed systems and discuss issues and controversies found in these proposed systems, as well as propose means to address some of these issues. They conclude with an overall conclusion and outline future directions in this field.
BACKGROUND Blockchain technology is emerging as an innovative tool in data and software security. OBJECTIVE This study aims to explore the role of blockchain in supporting clinical trials data management and develop a proof-of-concept implementation of a patient-facing and researcher-facing system. METHODS Blockchain-based Smart Contracts were built using the Ethereum platform. RESULTS We described BlockTrial, a system that uses a Web-based interface to allow users to run trials-related Smart Contracts on an Ethereum network. Functions allow patients to grant researchers access to their data and allow researchers to submit queries for data that are stored off chain. As a type of distributed ledger, the system generates a durable and transparent log of these and other transactions. BlockTrial could be used to increase the trustworthiness of data collected during clinical research with benefits to researchers, regulators, and drug companies alike. In addition, the system could empower patients to become more active and fully informed partners in research. CONCLUSIONS Blockchain technology presents an opportunity to address some of the common threats to the integrity of data collected in clinical trials and ensure that the analysis of these data comply with prespecified plans. Further technical work is needed to add additional functions. Policies must be developed to determine the optimal models for participation in the system by its various stakeholders.
Cloud computing provides on-demand resources and removes the boundaries of resources' physical locations. By providing virtualized computing resources in an elastic manner over the internet, IaaS providers allow organizations to save upfront infrastructure costs and focus on features that discriminate their businesses. The growing number of providers makes manual selection of the most suitable configuration of IaaS resources, or IaaS services, difficult and time consuming while requiring a high level of expertise. In our previous paper we proposed QuARAM recommender, a general platform for automatic IaaS service selection. In this paper, we present in detail the hybrid approach to automatic service selection used in our platform. The selection process begins with automatic extraction of an application's features, requirements and preferences, which are then used to produce a list of potential services for the application's deployment. We use case-based reasoning and MCDM (Multi-criteria Decision Making) to provide a recommendation of suitable services for application deployment, clustering to handle the problem of a large search space and a service consolidation method to improve the resource utilization and decrease the total service price. We carry out a case study with a prototype implementation of our platform to demonstrate that automatic IaaS service selection using a combination of all the proposed approaches is both practical and achievable.
