749 research outputs found
Fog-enabled Edge Learning for Cognitive Content-Centric Networking in 5G
By caching content at network edges close to the users, the content-centric
networking (CCN) has been considered to enforce efficient content retrieval and
distribution in the fifth generation (5G) networks. Due to the volume,
velocity, and variety of data generated by various 5G users, an urgent and
strategic issue is how to elevate the cognitive ability of the CCN to realize
context-awareness, timely response, and traffic offloading for 5G applications.
In this article, we envision that the fundamental work of designing a cognitive
CCN (C-CCN) for the upcoming 5G is exploiting the fog computing to
associatively learn and control the states of edge devices (such as phones,
vehicles, and base stations) and in-network resources (computing, networking,
and caching). Moreover, we propose a fog-enabled edge learning (FEL) framework
for C-CCN in 5G, which can aggregate the idle computing resources of the
neighbouring edge devices into virtual fogs to afford the heavy delay-sensitive
learning tasks. By leveraging artificial intelligence (AI) to jointly
processing sensed environmental data, dealing with the massive content
statistics, and enforcing the mobility control at network edges, the FEL makes
it possible for mobile users to cognitively share their data over the C-CCN in
5G. To validate the feasibility of proposed framework, we design two
FEL-advanced cognitive services for C-CCN in 5G: 1) personalized network
acceleration, 2) enhanced mobility management. Simultaneously, we present the
simulations to show the FEL's efficiency on serving for the mobile users'
delay-sensitive content retrieval and distribution in 5G.Comment: Submitted to IEEE Communications Magzine, under review, Feb. 09, 201
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
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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