NDLI: Efficient Remote Software Execution Architecture Based on Dynamic Address Translation for Internet-of-Things Software Execution Platform

Content Provider	IEEE Xplore Digital Library
Author	Minwoo Jung Daejin Park Jeonghun Cho
Copyright Year	2015
Description	Author affiliation: Sch. of Electron. Eng., Kyungpook Nat. Univ. Daehakro, Daegu, South Korea (Minwoo Jung; Daejin Park; Jeonghun Cho)
Abstract	In this paper, an efficient remote code execution technique is proposed to implement a storage-less sensor in the internet-of-Things (IoT) paradigm. A statically installed sensor such as an environmental activity monitor includes statically compiled embedded software and only offers its pre-defined functionality. To realize a flexible code update mechanism and to optimize the use of an IoT device in terms of utilizing its various functions, we adopt the concept of remote on-demand code execution (ROCE) to implement a storage-less sensor. Instead of using conventional on-chip flash memory for an instruction code, an instruction memory is used wherein the remote storage area based on the IoT platform is virtually mapped onto the address space of the instruction memory using a dynamic address translation technique. A pervasive Internet-connected sensor enables on-demand code execution from the cloud-side remote storage resource, without the need for a direct instruction bus. The proposed storage-less approach using the remote resource as a virtual code space may be adopted to reduce the high access current and chip area overhead of an on-chip code flash memory. To reduce the access current overhead in order to retrieve the requested instruction, a small-sized RAM scratch pad is adopted for retaining the hot-spot instruction code. The experimental results show that the proposed technique reduces the energy consumption and packet delay of an IoT device for executing the remote embedded software, as well as realizing a storage-less sensor architecture.
Sponsorship	Tamkang University
Starting Page	371
Ending Page	378
File Size	349666
Page Count	8
File Format	PDF
e-ISBN	9781479999422
DOI	10.1109/NBiS.2015.57
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-02
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Locality of reference Remote software update Memory management Random access memory Ash Software Virtual machining System-on-chip Dynamic address translation IoT
Content Type	Text
Resource Type	Article

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