1,297 research outputs found
Middleware platform for distributed applications incorporating robots, sensors and the cloud
Cyber-physical systems in the factory of the future
will consist of cloud-hosted software governing an agile
production process executed by autonomous mobile robots
and controlled by analyzing the data from a vast number of
sensors. CPSs thus operate on a distributed production floor
infrastructure and the set-up continuously changes with each
new manufacturing task. In this paper, we present our OSGibased
middleware that abstracts the deployment of servicebased
CPS software components on the underlying distributed
platform comprising robots, actuators, sensors and the cloud.
Moreover, our middleware provides specific support to develop
components based on artificial neural networks, a technique that
recently became very popular for sensor data analytics and robot
actuation. We demonstrate a system where a robot takes actions
based on the input from sensors in its vicinity
Technical considerations towards mobile user QoE enhancement via Cloud interaction
This paper discusses technical considerations of a Cloud infrastructure which interacts with mobile devices in order to migrate part of the computational overhead from the mobile device to the Cloud. The aim of the interaction between the mobile device and the Cloud is the enhancement of parameters that affect the Quality of Experience (QoE) of the mobile end user through the offloading of computational aspects of demanding applications. This paper shows that mobile user’s QoE can be potentially enhanced by offloading computational tasks to the Cloud which incorporates a predictive context-aware mechanism to schedule delivery of content to the mobile end-user using a low-cost interaction model between the Cloud and the mobile user. With respect to the proposed enhancements, both the technical considerations of the cloud infrastructure are examined, as well as the interaction between the mobile device and the Cloud
Cloudlet computing : recent advances, taxonomy, and challenges
A cloudlet is an emerging computing paradigm that is designed to meet the requirements and expectations of the Internet of things (IoT) and tackle the conventional limitations of a cloud (e.g., high latency). The idea is to bring computing resources (i.e., storage and processing) to the edge of a network. This article presents a taxonomy of cloudlet applications, outlines cloudlet utilities, and describes recent advances, challenges, and future research directions. Based on the literature, a unique taxonomy of cloudlet applications is designed. Moreover, a cloudlet computation offloading application for augmenting resource-constrained IoT devices, handling compute-intensive tasks, and minimizing the energy consumption of related devices is explored. This study also highlights the viability of cloudlets to support smart systems and applications, such as augmented reality, virtual reality, and applications that require high-quality service. Finally, the role of cloudlets in emergency situations, hostile conditions, and in the technological integration of future applications and services is elaborated in detail. © 2013 IEEE
ENORM: A Framework For Edge NOde Resource Management
Current computing techniques using the cloud as a centralised server will
become untenable as billions of devices get connected to the Internet. This
raises the need for fog computing, which leverages computing at the edge of the
network on nodes, such as routers, base stations and switches, along with the
cloud. However, to realise fog computing the challenge of managing edge nodes
will need to be addressed. This paper is motivated to address the resource
management challenge. We develop the first framework to manage edge nodes,
namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for
provisioning and auto-scaling edge node resources are proposed. The feasibility
of the framework is demonstrated on a PokeMon Go-like online game use-case. The
benefits of using ENORM are observed by reduced application latency between 20%
- 80% and reduced data transfer and communication frequency between the edge
node and the cloud by up to 95\%. These results highlight the potential of fog
computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12
September 201
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