37,688 research outputs found
Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient
Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices
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Adaptive use of task assignment models in team-based mobile business processes
Most mobile business processes are executed under uncertain and dynamic working environments. This makes the traditional centralized approach for the management of mobile tasks inappropriate to respond to the changes in working environment quickly as collecting the changing information from geographically distributed workforces in real time is expensive if not impossible. This raises the need of a distributed approach in the management of mobile tasks. This paper proposes a distributed architecture for team-based coordination support for mobile task management. In this architecture, tasks are managed via peer-to-peer style coordination between team members who have better understanding on the changing working environment than a centralised system. The novelty of the design of the architecture is explained by applying it to a real business process in the UK
A Time-driven Data Placement Strategy for a Scientific Workflow Combining Edge Computing and Cloud Computing
Compared to traditional distributed computing environments such as grids,
cloud computing provides a more cost-effective way to deploy scientific
workflows. Each task of a scientific workflow requires several large datasets
that are located in different datacenters from the cloud computing environment,
resulting in serious data transmission delays. Edge computing reduces the data
transmission delays and supports the fixed storing manner for scientific
workflow private datasets, but there is a bottleneck in its storage capacity.
It is a challenge to combine the advantages of both edge computing and cloud
computing to rationalize the data placement of scientific workflow, and
optimize the data transmission time across different datacenters. Traditional
data placement strategies maintain load balancing with a given number of
datacenters, which results in a large data transmission time. In this study, a
self-adaptive discrete particle swarm optimization algorithm with genetic
algorithm operators (GA-DPSO) was proposed to optimize the data transmission
time when placing data for a scientific workflow. This approach considered the
characteristics of data placement combining edge computing and cloud computing.
In addition, it considered the impact factors impacting transmission delay,
such as the band-width between datacenters, the number of edge datacenters, and
the storage capacity of edge datacenters. The crossover operator and mutation
operator of the genetic algorithm were adopted to avoid the premature
convergence of the traditional particle swarm optimization algorithm, which
enhanced the diversity of population evolution and effectively reduced the data
transmission time. The experimental results show that the data placement
strategy based on GA-DPSO can effectively reduce the data transmission time
during workflow execution combining edge computing and cloud computing
Adaptive Process Management in Cyber-Physical Domains
The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the âphysicalâ real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
Workflows and service discovery: a mobile device approach
Bioinformatics has moved from command-line standalone
programs to web-service based environments. Such trend has resulted
in an enormous amount of online resources which can be hard to find
and identify, let alone execute and exploit. Furthermore, these resources
are aimed -in general- to solve specific tasks. Usually, this tasks need to
be combined in order to achieve the desired results. In this line, finding
the appropriate set of tools to build up a workflow to solve a problem
with the services available in a repository is itself a complex exercise. Issues
such as services discovering, composition and representation appear.
On the technological side, mobile devices have experienced an incredible
growth in the number of users and technical capabilities. Starting from
this reality, in the present paper, we propose a solution for service discovering
and workflow generation while distinct approaches of representing
workflows in a mobile environment are reviewed and discussed. As a
proof of concept, a specific use case has been developed: we have embedded
an expanded version of our Magallanes search engine into mORCA,
our mobile client for bioinformatics. Such composition delivers a powerful
and ubiquitous solution that provides the user with a handy tool for
not only generate and represent workflows, but also services, data types,
operations and service types discoveryUniversidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂa Tech
Smart objects as building blocks for the internet of things
The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application
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