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nmrg                                              Hong, Choong Seon
Internet-Draft                                   Kyung Hee University
Intended status: Standards Track          Kim, Kitae
Expires: August 09, 2022                     Kyung Hee University
                                                      YuMin Park
                                                      Kyung Hee University


MEC Resource Monitoring for Task Offloading to Mobile Edge Server
                        draft-mecmonitoring-nmrg-dfm-00

Abstract

Mobile Edge Cloud Computing(MEC) has been develeoped and
introduceto provide low-latency service in proximity to users.
By placing the computing resources on the edge of network such
as base stations and Access Points(AP), therefore users can downlaod
cached contents or use computing resources from nearby cloud nodes.
In recent, due to developement of communication technology and emergence of
various mobile device such as smartphone, smart wathch, there are many applications
that demand high computational ability have emearged such as regarding Virtual
Reality and Augmented Reality and machine learning. the problem is that mobile
devices has limited resources to process aforementioned application. In this situatiom,
mobile users can offload thier tasks to the mobile cloud.

Status of this Memo

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Hong, et al.          Expires  August 09, 2020                  [Page 1]

Internet-Draft Resource Monitoring for Task Offloading to Mobile Edge Server   May 2019

This Internet-Draft will expire on August 09, 2022.

Copyright Notice

Copyright (c) 2020 IETF Trust and the persons identified as the
document authors.  All rights reserved.

 This document is subject to BCP 78 and the IETF Trust's Legal
 Provisions Relating to IETF Documents
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Table of Contents

 1.  Introduction . . . . . . . . . . . . . . . . . . . .. . . . . .  2
      1.1.  Terminology and Requirements Language  . . . . . . . . .  3
 2.  Communication Process . . . . . . . . . . . . . . . . . . . . .  3
      2.1.  Task Offloading Procedure . . . . . . . . . . 4
      2.2.  Network Setup  . . . . . . . . . . . . . . .. . . .  . .  5
 3.  Collaboration between whole module. . . . . . . . . . . .  . .  7
      3.1   Computational Caching . . . . . . . .. . . . . . . . .  7
      3.2.  Flow Chart for Whole Offloading. .. . . . . . . . . .9
 4.  IANA Considerations  . . . . . . .. . . . .  . . . . . . . . . . 9
 5.  Security Considerations  . . . . . . . . . . . .  . . .  . . . .10
 6.  References . . . . . . . . . . . . . . . . . . . . . . . . . . .10
 6.1.  Normative References . . . . . . . . . . . . . . . . . . . . .10
 6.2.  Informative References . . . . . .. . . . .  . . . . . . . . .10
 Authors' Addresses . . . . . . . . . . . . . . . . . . . . .. . . . 11


1.  Introduction

 Mobile Edge Cloud Computing(MEC) has been developed and introduced to
provide low-latency service in close proximity to users. By placing the computing
resources on the edge of network, such as base stations and Access Point(AP)
therefore Users can download cached content or use computing resources from
nearby cloud nodes. In this point service provider can provide low-latency service
to users and save resources on backhaul network such as bandwidth.
In recent, due to development of communication technology and emergence of
various mobile device such as smart phone, smart watch, etc. There are many
application that demand high computational ability have emerged such as regarding
Virtual Reality(VR), Augmented Reality and machine learning. The problem is that
mobile device has limited resources to process aforementioned application.
In this situation mobile users can offload their tasks to the mobile cloud. However,
 A large number of offloading request may congest MEC nodes and the total processing
time takes more time when applications are processed at local device.
So we need to solve congestion problem to ensure time limitation for those applications.


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