147 research outputs found
From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey
Context data is in demand more than ever with the rapid increase in the
development of many context-aware Internet of Things applications. Research in
context and context-awareness is being conducted to broaden its applicability
in light of many practical and technical challenges. One of the challenges is
improving performance when responding to large number of context queries.
Context Management Platforms that infer and deliver context to applications
measure this problem using Quality of Service (QoS) parameters. Although
caching is a proven way to improve QoS, transiency of context and features such
as variability, heterogeneity of context queries pose an additional real-time
cost management problem. This paper presents a critical survey of
state-of-the-art in adaptive data caching with the objective of developing a
body of knowledge in cost- and performance-efficient adaptive caching
strategies. We comprehensively survey a large number of research publications
and evaluate, compare, and contrast different techniques, policies, approaches,
and schemes in adaptive caching. Our critical analysis is motivated by the
focus on adaptively caching context as a core research problem. A formal
definition for adaptive context caching is then proposed, followed by
identified features and requirements of a well-designed, objective optimal
adaptive context caching strategy.Comment: This paper is currently under review with ACM Computing Surveys
Journal at this time of publishing in arxiv.or
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
Binary Task Offloading Model For Mobile Edge Computing using NDN Architecture
Driven by the advantages of Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) in nextgeneration networks we propose an architecture for MEC using Named Data Networking (NDN). NDN is one of the prominent architectures of ICN having features like unique-naming, in-network caching, inherit support for multicasting, and support for mobility. Placing MEC in NDN provides the additional facilities of edge computing like pushing of resource-hungry and time-critical applications of the mobile devices to the edge-computing server. Therefore, one of the research challenges is the decision regarding the task offloading process by the end-users to the edge-computing server. We propose a mathematical model that enables the end-user to take decisions in Yes/No regarding the binary task offloading process
Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control
In recent years, the exponential proliferation of smart devices with their
intelligent applications poses severe challenges on conventional cellular
networks. Such challenges can be potentially overcome by integrating
communication, computing, caching, and control (i4C) technologies. In this
survey, we first give a snapshot of different aspects of the i4C, comprising
background, motivation, leading technological enablers, potential applications,
and use cases. Next, we describe different models of communication, computing,
caching, and control (4C) to lay the foundation of the integration approach. We
review current state-of-the-art research efforts related to the i4C, focusing
on recent trends of both conventional and artificial intelligence (AI)-based
integration approaches. We also highlight the need for intelligence in
resources integration. Then, we discuss integration of sensing and
communication (ISAC) and classify the integration approaches into various
classes. Finally, we propose open challenges and present future research
directions for beyond 5G networks, such as 6G.Comment: This article has been accepted for inclusion in a future issue of
China Communications Journal in IEEE Xplor
A survey on cost-effective context-aware distribution of social data streams over energy-efficient data centres
Social media have emerged in the last decade as a viable and ubiquitous means of communication. The ease of user content generation within these platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges, including derivation of real-time meaningful insights from effectively gathered social information, as well as a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general. In this article we present a comprehensive survey that outlines the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centres supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. We systematize the existing literature and proceed to identify and analyse the main research points and industrial efforts in the area as far as modelling, simulation and performance evaluation are concerned
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