Content architecture applications in healthcare

Healthcare delivery is undergoing significant transformation in the United States. Many hospitals and clinics are utilizing electronic means for maintaining patient records. Implementation of electronic health records is now a prevalent activity at many healthcare organizations. Despite the use of electronic health records by many healthcare organizations, it is still difficult to obtain meaningful information from electronic data pertaining to healthcare. Intelligent content applications organize the data within a company make all the data in the organization searchable and retrievable for faster access. This paper therefore explores SOA (Service oriented architecture) and intelligent content architecture in an attempt to suggest better structures that enable retrieval of related data from myriad sources within a company. While intelligent content applications are being slowly developed for areas such as electronic publishing, its use in healthcare organizations has been limited. This paper discusses applications of intelligent content architecture for the healthcare domain.

Workflow temporal verification for monitoring parallel business processes

Workflow temporal verification is conducted to guarantee on-time completion, which is one of the most important QoS (Quality of Service) dimensions for business processes running in the cloud. However, as today's business systems often need to handle a large number of concurrent customer requests, conventional response-time based process monitoring strategies conducted in a one-by-one fashion cannot be applied efficiently to a large batch of parallel processes because of significant time overhead. Similar situations may also exist in software companies where multiple software projects are carried out at the same time by software developers. To address such a problem, based on a novel runtime throughput consistency model, this paper proposes a QoS-aware throughput based checkpoint selection strategy, which can dynamically select a small number of checkpoints along the system timeline to facilitate the temporal verification of throughput constraints and achieve the target on-time completion rate. Experimental results demonstrate that our strategy can achieve the best efficiency and effectiveness compared with the state-of-the-art as and other representative response-time based checkpoint selection strategies.

Fault detection service architecture for grid computing systems

The ability to tolerate failures while effectively exploiting the grid computing resources in an scalable and transparent manner must be an integral part of grid computing infrastructure. Hence, fault-detection service is a necessary prerequisite to fault tolerance and fault recovery in grid computing. To this end, we present an scalable fault detection service architecture. The proposed fault-detection system provides services that monitors user applications, grid middlewares and the dynamically changing state of a collection of distributed resources. It reports summaries of this information to the appropriate agents on demand or instantaneously in the event of failures.

The design and development of an integrated system for object-oriented finite element computing

Finite Element Method (FEM) is widely used in Science and Engineering since 1960’s. The vast majority of FEM software is procedure-oriented. However, this conventional style of designing FEM software encounters problems in maintenance, reuse, and expansion of the software. Recently the object-oriented finite element method attracts the attention of lots of researchers, and now there is a growing interest in this method. In this paper, the object-oriented finite element (OOFE) is briefly introduced. Then the design and development of an integrated OOFE system is described. A comparison of the integrated OOFE system and a procedure-oriented system shows that our OOFE system has many advantages.

Successful web-based IT support services : service provider perceptions of stakeholder-oriented challenges

Web-based self-service systems (WSSs) are increasingly leveraged for the delivery of after-sales information technology (IT) support services. Such services are offered by IT service providers to customer firms and increasingly involve business partners. However little is known of the challenges faced by IT service providers as a result of the involvement of the other firms and their employees (end-users). This paper reports related findings from an interpretive study of IT service provider perceptions in six multinational IT service provider firms (Cooper, 2007). The findings highlight that, for IT service providers, (1) it is important to consider and resolve the needs and concerns of other key stakeholders, and (2) significant challenges exist in doing so. The main contribution of the paper is the identification of the key challenges involved. Important implications for theory and practice are discussed.

An online credential management service for InterGrid computing

Grid users and their jobs need credentials to access grid resources and services. It is important to minimize the exposure of credentials to adversaries. A practical solution is needed that works with existing software and is easy to deploy, administer, and maintain. Thus, credential management services are the wave of the future for virtual organizations such as Grid computing. This paper describes architecture of a scalable, secure and reliable on-line credential management service called SafeBox for InterGrid computing platform. SafeBox provides InterGrid users with secure mechanism for storing one or multiple credentials and access them based on need at anytime from anywhere.

Determining service trustworthiness in inter loud computing environments

Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous clouds to create cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.

Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

Service and cloud computing supporting genomic analysis of the mammalian species

 This research focused on building Software as a Service clouds to support mammalian genomic applications such as personalized medicine. Outcomes of this research included a Software as a Service cloud framework, the Uncinus research cloud and novel genomic analysis software. Results have been published in high ranking peer-reviewed international journals.

A survey of cloud-based service computing solutions for mammalian genomics

Cloud-based service computing has started to change the way how research in science, in particular biology, medicine, and engineering, is being carried out. Researchers in the area of mammalian genomics have taken advantage of cloud computing technology to cost-effectively process large amounts of data and speed up discovery. Mammalian genomics is limited by the cost and complexity of analysis, which require large amounts of computational resources to analyse huge amount of data and biology specialists to interpret results. On the other hand the application of this technology requires computing knowledge, in particular programming and operations management skills to develop high performance computing (HPC) applications and deploy them on HPC clouds. We carried out a survey of cloud-based service computing solutions, as the most recent and promising instantiations of distributed computing systems, in the context their use in research of mammalian genomic analysis. We describe our most recent research and development effort which focuses on building Software as a Service (SaaS) clouds to simplify the use of HPC clouds for carrying out mammalian genomic analysis.

Dynamic cloud service selection using an adaptive learning mechanism in multi-cloud computing

Cloud service selection in a multi-cloud computing environment is receiving more and more attentions. There is an abundance of emerging cloud service resources that makes it hard for users to select the better services for their applications in a changing multi-cloud environment, especially for online real time applications. To assist users to efficiently select their preferred cloud services, a cloud service selection model adopting the cloud service brokers is given, and based on this model, a dynamic cloud service selection strategy named DCS is put forward. In the process of selecting services, each cloud service broker manages some clustered cloud services, and performs the DCS strategy whose core is an adaptive learning mechanism that comprises the incentive, forgetting and degenerate functions. The mechanism is devised to dynamically optimize the cloud service selection and to return the best service result to the user. Correspondingly, a set of dynamic cloud service selection algorithms are presented in this paper to implement our mechanism. The results of the simulation experiments show that our strategy has better overall performance and efficiency in acquiring high quality service solutions at a lower computing cost than existing relevant approaches.

An energy-aware QoS enhanced method for service computing across clouds and data centers

QoS plays a key role in evaluating a service or a service composition plan across clouds and data centers. Currently, the energy cost of a service's execution is not covered by the QoS framework, and a service's price is often fixed during its execution. However, energy consumption has a great contribution in determining the price of a cloud service. As a result, it is not reasonable if the price of a cloud service is calculated with a fixed energy consumption value, if part of a service's energy consumption could be saved during its execution. Taking advantage of the dynamic energy-Aware optimal technique, a QoS enhanced method for service computing is proposed, in this paper, through virtual machine (VM) scheduling. Technically, two typical QoS metrics, i.e., the price and the execution time are taken into consideration in our method. Moreover, our method consists of two dynamic optimal phases. The first optimal phase aims at dynamically benefiting a user with discount price by transparently migrating his or her task execution from a VM located at a server with high energy consumption to a low one. The second optimal phase aims at shortening task's execution time, through transparently migrating a task execution from a VM to another one located at a server with higher performance. Experimental evaluation upon large scale service computing across clouds demonstrates the validity of our method.

A market-oriented hierarchical scheduling strategy in cloud workflow systems

A cloud workflow system is a type of platform service which facilitates the automation of distributed applications based on the novel cloud infrastructure. One of the most important aspects which differentiate a cloud workflow system from its other counterparts is the market-oriented business model. This is a significant innovation which brings many challenges to conventional workflow scheduling strategies. To investigate such an issue, this paper proposes a market-oriented hierarchical scheduling strategy in cloud workflow systems. Specifically, the service-level scheduling deals with the Task-to-Service assignment where tasks of individual workflow instances are mapped to cloud services in the global cloud markets based on their functional and non-functional QoS requirements; the task-level scheduling deals with the optimisation of the Task-to-VM (virtual machine) assignment in local cloud data centres where the overall running cost of cloud workflow systems will be minimised given the satisfaction of QoS constraints for individual tasks. Based on our hierarchical scheduling strategy, a package based random scheduling algorithm is presented as the candidate service-level scheduling algorithm and three representative metaheuristic based scheduling algorithms including genetic algorithm (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO) are adapted, implemented and analysed as the candidate task-level scheduling algorithms. The hierarchical scheduling strategy is being implemented in our SwinDeW-C cloud workflow system and demonstrating satisfactory performance. Meanwhile, the experimental results show that the overall performance of ACO based scheduling algorithm is better than others on three basic measurements: the optimisation rate on makespan, the optimisation rate on cost and the CPU time.

Knowledge transfer in enterprise information technology support using web-based self-service systems

This paper explores Critical Success Factors (CSFs) in the transfer
of after-sales support-oriented knowledge from Information Technology (IT)
support organisations to enterprise customers, using Web-based self-service Systems (WSS). As it appears that best-in-class companies are ahead of the academic work in this area, we approached the topic through an exploratory CSF study of a best-in-class multinational IT services firm and identified 26 CSFs. Key findings from the study indicate that best-in-class IT service organisations may be cognisant of a range of factors relating to supporting customers, but are less aware of what is needed to support their own frontline support agents. Such organisations also lack an understanding of what is needed to provide enterprise support in the later stages of knowledge transfer, where enterprise customers can experience problems attempting to integrate resolutions. The study further showed that many aspects that might be characterised as encompassing socio-technical issues relating to the provision of web-based self-service are still poorly understood.

Toward successful knowledge transfer in web-based self-service for information technology services

Web-based self-service has emerged as an important strategy for providing pre- and post-sales customer support. Yet, there is a dearth of theoretical or empirical research concerning the organisational, customer-oriented, knowledge-based, and employee-oriented factors that enable web-based self-service systems (WSS) to be successful in a competitive global marketplace. In this paper, we describe and discuss findings from the first phase of a multi-method research study designed to address this literature gap. This study explores critical success factors (CSFs) involved in the transfer of support-oriented knowledge from an information technology (IT) services firm to commercial customers when WSS are employed. Empirical data collected in a CSF study of a large multinational IT services business are used to identify twenty-six critical success factors. The findings indicate that best-in-class IT service providers are aware of a range of critical success factors in the transfer to commercial customers of resolutions and other support-oriented knowledge via WSS. However, such firms remain less certain about what is needed to support customer companies after support-oriented knowledge has initially been transferred to the customer firm.