Multi-access edge computing: open issues, challenges and future perspectives View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12-21

AUTHORS

Sonia Shahzadi, Muddesar Iqbal, Tasos Dagiuklas, Zia Ul Qayyum

ABSTRACT

Latency minimization is a pivotal aspect in provision of real time services while adhering to Quality of Experience (QoE) parameters for assuring spectral efficiency. Edge Cloud Computing, being a potential research dimension in the realm of 5G networks, targets to enhance the network efficiency by harnessing effectiveness of both cloud computing and mobile devices in user’s proximity. Keeping in view the far ranging impact of Edge Cloud Computing in future mobile generations, a comprehensive review of the prevalent Edge Cloud Computing frameworks and approaches is presented with a detailed comparison of its classifications through various QoS metrics (pertinent to network performance and overheads associated with deployment/migration). Considering the knowledge accumulated, procedures analysed and theories discussed, the paper provides a comprehensive overview on sate-of-the-art and future research directions for multi-access mobile edge computing. More... »

PAGES

30

References to SciGraph publications

  • 2014-03-12. Fog Computing: A Platform for Internet of Things and Analytics in BIG DATA AND INTERNET OF THINGS: A ROADMAP FOR SMART ENVIRONMENTS
  • 2012. Cuckoo: A Computation Offloading Framework for Smartphones in MOBILE COMPUTING, APPLICATIONS, AND SERVICES
  • 2012. Mirroring Smartphones for Good: A Feasibility Study in MOBILE AND UBIQUITOUS SYSTEMS: COMPUTING, NETWORKING, AND SERVICES
  • 2012. Augmenting Pervasive Environments with an XMPP-Based Mobile Cloud Middleware in MOBILE COMPUTING, APPLICATIONS, AND SERVICES
  • 2006. Autonomic Management of Edge Servers in SELF-ORGANIZING SYSTEMS
  • 2009. Calling the Cloud: Enabling Mobile Phones as Interfaces to Cloud Applications in MIDDLEWARE 2009
  • 2010. Towards an Elastic Application Model for Augmenting Computing Capabilities of Mobile Platforms in MOBILE WIRELESS MIDDLEWARE, OPERATING SYSTEMS, AND APPLICATIONS
  • 2012-02-05. A Framework for Seamless Execution of Mobile Applications in the Cloud in RECENT ADVANCES IN COMPUTER SCIENCE AND INFORMATION ENGINEERING
  • 2006-06-08. A Scalable Cluster-based Infrastructure for Edge-computing Services in WORLD WIDE WEB
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13677-017-0097-9

    DOI

    http://dx.doi.org/10.1186/s13677-017-0097-9

    DIMENSIONS

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