1,539 research outputs found
Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support.
A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends
Emerging Edge Computing Technologies for Distributed Internet of Things (IoT) Systems
The ever-increasing growth in the number of connected smart devices and
various Internet of Things (IoT) verticals is leading to a crucial challenge of
handling massive amount of raw data generated from distributed IoT systems and
providing real-time feedback to the end-users. Although existing
cloud-computing paradigm has an enormous amount of virtual computing power and
storage capacity, it is not suitable for latency-sensitive applications and
distributed systems due to the involved latency and its centralized mode of
operation. To this end, edge/fog computing has recently emerged as the next
generation of computing systems for extending cloud-computing functions to the
edges of the network. Despite several benefits of edge computing such as
geo-distribution, mobility support and location awareness, various
communication and computing related challenges need to be addressed in
realizing edge computing technologies for future IoT systems. In this regard,
this paper provides a holistic view on the current issues and effective
solutions by classifying the emerging technologies in regard to the joint
coordination of radio and computing resources, system optimization and
intelligent resource management. Furthermore, an optimization framework for
edge-IoT systems is proposed to enhance various performance metrics such as
throughput, delay, resource utilization and energy consumption. Finally, a
Machine Learning (ML) based case study is presented along with some numerical
results to illustrate the significance of edge computing.Comment: 16 pages, 4 figures, 2 tables, submitted to IEEE Wireless
Communications Magazin
Caching-Aided Collaborative D2D Operation for Predictive Data Dissemination in Industrial IoT
Industrial automation deployments constitute challenging environments where
moving IoT machines may produce high-definition video and other heavy sensor
data during surveying and inspection operations. Transporting massive contents
to the edge network infrastructure and then eventually to the remote human
operator requires reliable and high-rate radio links supported by intelligent
data caching and delivery mechanisms. In this work, we address the challenges
of contents dissemination in characteristic factory automation scenarios by
proposing to engage moving industrial machines as device-to-device (D2D)
caching helpers. With the goal to improve reliability of high-rate
millimeter-wave (mmWave) data connections, we introduce the alternative
contents dissemination modes and then construct a novel mobility-aware
methodology that helps develop predictive mode selection strategies based on
the anticipated radio link conditions. We also conduct a thorough system-level
evaluation of representative data dissemination strategies to confirm the
benefits of predictive solutions that employ D2D-enabled collaborative caching
at the wireless edge to lower contents delivery latency and improve data
acquisition reliability
Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices
Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications
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