Efficient Partitioning of On-Cloud Remote Executable Code and On-Chip Software for Complex-Connected IoT

Dongkyu Lee, Jeonghun Cho, Daejin Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A program running on one processor can easily model the system and analyze power consumption and execution time. However, complex systems in which multiple processors interact are very difficult to model. Creating and simulating a simulation model would be effective for analyzing a complex system. However, the simulation model changes as the connection structure of the system changes. In this paper, we propose a framework that takes a connection structure and creates a simulation model automatically. This framework allows developers to easily create a simulation model by inserting the connection structures between the IoT systems. And we can find efficient part of on-cloud remote executable code and on-chip software in terms of power consumption or execution time.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538677896
DOIs
StatePublished - 1 Apr 2019
Event2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan
Duration: 27 Feb 20192 Mar 2019

Publication series

Name2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings

Conference

Conference2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
Country/TerritoryJapan
CityKyoto
Period27/02/192/03/19

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