research-article

Oops: Optimizing Operation-mode Selection for IoT Edge Devices

Authors:

Vasileios Tsoutsouras,

Sotirios Xydis,

Dimitrios Soudris,

Jörg HenkelAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 19, Issue 2

Article No.: 22, Pages 1 - 21

https://doi.org/10.1145/3230642

Published: 28 March 2019 Publication History

Abstract

The massive increase of IoT devices and their collected data raises the question of how to analyze all that data. Edge computing provides a suitable compromise, but the question remains: How much processing should be done locally vs. offloaded to other devices? The diverse application requirements and limited resources at the edge extend the challenges.

We propose Oops, an optimization framework to adapt the resource management at runtime distributedly. It orchestrates the IoT devices and adapts their operation mode with respect to their constraints and the gateway’s limited shared resources. Oops reduces runtime overhead significantly while increasing user utility compared to state-of-the-art.

References

[1]

{n. d.}. Coin Cell / Button Cell Battery Guide. Retrieved from: https://www.batteries.com/pages/coin-cell-button-cell-battery-guide.

[2]

{n. d.}. Intel IoT Gateway. Retrieved from: http://www.intel.de/content/dam/www/public/us/en/documents/product-briefs/gateway-solutions-iot-brief.pdf.

[3]

Stephen Boyd and Lieven Vandenberghe. 2004. Convex Optimization. Cambridge University Press.

Digital Library

[4]

Energizer Brands. {n. d.}. Lithium coin, handbook and application manual. Retrieved from: http://data.energizer.com/pdfs/lithiumcoin_appman.pdf.

[5]

Luca Catarinucci, Danilo De Donno, Luca Mainetti, Luca Palano, Luigi Patrono, Maria Laura Stefanizzi, and Luciano Tarricone. 2015. An IoT-aware architecture for smart healthcare systems. IEEE Inter. Things J. 2, 6 (2015).

[6]

Xu Chen. 2015. Decentralized computation offloading game for mobile cloud computing. IEEE Trans. Parallel Distrib. Systems 26, 4 (2015), 974--983.

Digital Library

[7]

Mung Chiang and Tao Zhang. 2016. Fog and IoT: An overview of research opportunities. IEEE Inter. Things J. 3, 6 (2016), 854--864.

[8]

Soumya Kanti Datta, Christian Bonnet, and Navid Nikaein. 2014. An IoT gateway-centric architecture to provide novel M2M services. In Proceedings of the World Forum on Internet of Things (WF-IoT’14). 514--519.

[9]

Mostafa Dehghan, Laurent Massoulie, Don Towsley, Daniel Menasche, and Yong Chiang Tay. 2016. A utility optimization approach to network cache design. In Proceedings of the International Conference on Computer Communications (INFOCOM’16). 1--9.

Digital Library

[10]

Kai-Wei Fan, Zizhan Zheng, and Prasun Sinha. 2008. Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. In Proceedings of the ACM Conference on Embedded Network Sensor Systems (SenSys’08). 239--252.

Digital Library

[11]

Tuan Nguyen Gia, Mingzhe Jiang, Amir-Mohammad Rahmani, Tomi Westerlund, Pasi Liljeberg, and Hannu Tenhunen. 2015. Fog computing in healthcare Internet of Things: A case study on ECG feature extraction. In Proceedings of the International Conference on Computer and Information Technology. 356--363.

[12]

Wendi B. Heinzelman, Amy L. Murphy, Hervaldo S. Carvalho, and Mark A. Perillo. 2004. Middleware to support sensor network applications. IEEE Netw. 18, 1 (2004), 6--14.

Digital Library

[13]

Pengfei Hu, Sahraoui Dhelim, Huansheng Ning, and Tie Qiu. 2017. Survey on fog computing: Architecture, key technologies, applications, and open issues. J. Netw. Comput. Appl. 98 (2017).

Digital Library

[14]

Dejan Kovachev, Tian Yu, and Ralf Klamma. 2012. Adaptive computation offloading from mobile devices into the cloud. In Proceedings of the International Symposium on Parallel and Distributed Processing with Applications. IEEE, 784--791.

Digital Library

[15]

D. Kraft and K. Schnepper. 1989. SLSQP-A nonlinear programming method with quadratic programming subproblems. DLR, Oberpfaffenhofen (1989).

[16]

Jeongho Kwak, Yeongjin Kim, Joohyun Lee, and Song Chong. 2015. DREAM: Dynamic resource and task allocation for energy minimization in mobile cloud systems. IEEE J. Select. Areas Comm. 33, 12 (2015).

Digital Library

[17]

SangJoon Lee, Jungkuk Kim, and Myoungho Lee. 2011. A real-time ECG data compression and transmission algorithm for an e-health device. IEEE Trans. Biomed. Eng. 58, 9 (2011), 2448--2455.

[18]

Wei Li, Flávia C. Delicato, Paulo F. Pires, Young Choon Lee, Albert Y. Zomaya, Claudio Miceli, and Luci Pirmez. 2014. Efficient allocation of resources in multiple heterogeneous wireless sensor networks. J. Parallel and Distrib. Comput. 74, 1 (2014), 1775--1788.

Digital Library

[19]

Jie Lin, Wei Yu, Nan Zhang, Xinyu Yang, Hanlin Zhang, and Wei Zhao. 2017. A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications. IEEE Inter. Things J. 4, 5 (2017).

[20]

Qicheng Ma, David C. Parkes, and Matthew D. Welsh. 2007. A utility-based approach to bandwidth allocation and link scheduling in wireless networks. In Proceedings of the International Workshop on Agent Technology for Sensor Networks (ATSN’07).

[21]

Yuyi Mao and Jun Zhang. 2016. Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE J. Solid-State Circ. 51, 3 (2016), 712--723.

[22]

Peter Marbach. 2002. Priority service and max-min fairness. In Proceedings of the International Conference on Computer Communications (INFOCOM’02). 266--275.

[23]

Dimosthenis Masouros, Ioannis Bakolas, Vasileios Tsoutsouras, K. Siozior, and Dimitrios Soudris. 2017. From edge to cloud: Design and implementation of a healthcare internet of things infrastructure. In Proceedings of the International Workshop on Power and Timing Modeling Optimization and Simulation (PATMOS’17). 1--6.

[24]

Chris Raphael. 2016. Why edge computing is crucial for the IoT. Retrieved from: http://www.rtinsights.com/why-edge-computing-and-analytics-is-crucial-for-the-iot/.

[25]

Farzad Samie. 2018. Resource Management for Edge Computing in Internet of Things (IoT). Ph.D. Dissertation. Karlsruhe Institute of Technology, Karlsruhe, Germany.

[26]

Farzad Samie, Lars Bauer, and Jörg Henkel. 2016. IoT technologies for embedded computing: A survey. In Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS’16).

Digital Library

[27]

Farzad Samie, Sebastian Paul, Lars Bauer, and Jörg Henkel. 2018. Highly efficient and accurate seizure prediction on constrained IoT systems. In Proceedings of the Design, Automation 8 Test in Europe Conference 8 Exhibition (DATE’18).

[28]

Farzad Samie, Vasileios Tsoutsouras, Sotirios Xydis, Lars Bauer, Dimitrios Soudris, and Jörg Henkel. 2016. Computation offloading and resource allocation for low-power IoT edge devices. In Proceedings of the World Forum on Internet of Things (WF-IoT’16).

[29]

Farzad Samie, Vasileios Tsoutsouras, Sotirios Xydis, Lars Bauer, Dimitrios Soudris, and Jörg Henkel. 2016. Distributed QoS management for internet of things under resource constraints. In Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS’16).

Digital Library

[30]

Weisong Shi, Jie Cao, Quan Zhang, Youhuizi Li, and Lanyu Xu. 2016. Edge computing: Vision and challenges. IEEE Int. Things J. 3, 5 (2016).

[31]

Matti Siekkinen, Markus Hiienkari, Jukka K. Nurminen, and Johanna Nieminen. 2012. How low energy is Bluetooth low energy? Comparative measurements with ZigBee/802.15.4. In Proceedings of the IEEE Wireless Communications and Networking Conference Workshops (WCNCW’12).

[32]

Liansheng Tan, Zhongxun Zhu, Fei Ge, and Naixue Xiong. 2015. Utility maximization resource allocation in wireless networks: Methods and algorithms. IEEE Trans. Systems, Man, Cyber.: Systems 45, 7 (2015), 1018--1034.

[33]

Tamás Terlaky. 2013. Interior Point Methods of Mathematical Programming. Vol. 5. Springer Science 8 Business Media.

[34]

u-blox. 2017. SARA-G3 Data Sheet. Retrieved from: https://www.u-blox.com/sites/default/files/SARA-G3_DataSheet_(UBX-13000993).pdf.

[35]

u-blox. 2018. LARA-R2 Data Sheet. Retrieved from: https://www.u-blox.com/sites/default/files/LARA-R2_DataSheet_(UBX-16005783).pdf.

[36]

u-blox. 2018. SARA-U2 Data Sheet. Retrieved from: https://www.u-blox.com/sites/default/files/SARA-U2_DataSheet_(UBX-13005287).pdf.

[37]

Felix Ming Fai Wong, Carlee Joe-Wong, Sangtae Ha, Zhenming Liu, and Mung Chiang. 2015. Improving user QoE for residential broadband: Adaptive traffic management at the network edge. In Proceedings of the International Symposium on Quality of Service (IWQoS’15). 105--114.

[38]

Changjiu Xian, Yung-Hsiang Lu, and Zhiyuan Li. 2007. Adaptive computation offloading for energy conservation on battery-powered systems. In Proceedings of the International Conference on Parallel and Distributed Systems, Vol. 2. 1--8.

Digital Library

[39]

Thomas Zachariah, Noah Klugman, Bradford Campbell, Joshua Adkins, Neal Jackson, and Prabal Dutta. 2015. The internet of things has a gateway problem. In Proceedings of the Workshop on Mobile Computing Systems and Applications (HotMobile’15). 27--32.

Digital Library

[40]

Ben Zhang, Nitesh Mor, John Kolb, Douglas S. Chan, Nikhil Goyal, Ken Lutz, Eric Allman, John Wawrzynek, Edward Lee, and John Kubiatowicz. 2015. The cloud is not enough: Saving IoT from the cloud. In Proceedings of the USENIX Workshop on Hot Topics in Cloud Computing (HotCloud’15). 21--21.

Digital Library

[41]

Haibin Zhang, Jianpeng Li, Bo Wen, Yijie Xun, and Jiajia Liu. 2018. Connecting intelligent things in smart hospitals using NB-IoT. IEEE Inter.Things J. 5, 3 (2018).

Cited By

Shirke AChandane M(2023)Collaborative offloading decision policy framework in IoT using edge computingMultimedia Tools and Applications10.1007/s11042-023-14383-4Online publication date: 13-Jan-2023
https://doi.org/10.1007/s11042-023-14383-4
Riegler MSametinger JRozenblit J(2022)Context-Aware Security Modes For Medical Devices2022 Annual Modeling and Simulation Conference (ANNSIM)10.23919/ANNSIM55834.2022.9859283(372-382)Online publication date: 18-Jul-2022
https://doi.org/10.23919/ANNSIM55834.2022.9859283
Singh AGupta R(2022)LoRa-Based Sensing Network Setup and IoT Integration for Smart Agricultural ManagementProceedings of 2nd International Conference on Artificial Intelligence: Advances and Applications10.1007/978-981-16-6332-1_48(579-594)Online publication date: 14-Feb-2022
https://doi.org/10.1007/978-981-16-6332-1_48
Show More Cited By

Index Terms

Oops: Optimizing Operation-mode Selection for IoT Edge Devices

Recommendations

Distributed Trade-Based Edge Device Management in Multi-Gateway IoT
Special Issue on the Internet of Things: Part 2

The Internet-of-Things (IoT) envisions an infrastructure of ubiquitous networked smart devices offering advanced monitoring and control services. The current art in IoT architectures utilizes gateways to enable application-specific connectivity to IoT ...
Service priority queuing model-based internet of things middleware for load balancing among fog computing centres

The fog computing architectural component meets the major requirements of the internet of things (IoT) applications. Fog computing nodes are mainly used to handle delay sensitive requests generated by IoT devices. An increase in the service arrival rate ...
Challenges for building a cloud native scalable and trustable multi-tenant AIoT platform
ICCAD '20: Proceedings of the 39th International Conference on Computer-Aided Design

The arrival of 5G together with advances in artificial intelligence, machine learning, cloud computing, virtualization, and service orchestration have created a ubiquitous computing model at the network edge, enabling a host of new, AI driven edge ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 19, Issue 2

Special Issue on Fog, Edge, and Cloud Integration

May 2019

288 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3322882

Editor:
Ling Liu
Georgia Institute of Technology, USA

Issue’s Table of Contents

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2019

Accepted: 01 May 2018

Revised: 01 April 2018

Received: 01 December 2017

Published in TOIT Volume 19, Issue 2

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
370
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)1

Reflects downloads up to 24 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Shirke AChandane M(2023)Collaborative offloading decision policy framework in IoT using edge computingMultimedia Tools and Applications10.1007/s11042-023-14383-4Online publication date: 13-Jan-2023
https://doi.org/10.1007/s11042-023-14383-4
Riegler MSametinger JRozenblit J(2022)Context-Aware Security Modes For Medical Devices2022 Annual Modeling and Simulation Conference (ANNSIM)10.23919/ANNSIM55834.2022.9859283(372-382)Online publication date: 18-Jul-2022
https://doi.org/10.23919/ANNSIM55834.2022.9859283
Singh AGupta R(2022)LoRa-Based Sensing Network Setup and IoT Integration for Smart Agricultural ManagementProceedings of 2nd International Conference on Artificial Intelligence: Advances and Applications10.1007/978-981-16-6332-1_48(579-594)Online publication date: 14-Feb-2022
https://doi.org/10.1007/978-981-16-6332-1_48
Khan SLe Moullec YAlam M(2021)An NB-IoT-Based Edge-of-Things Framework for Energy-Efficient Image TransferSensors10.3390/s2117592921:17(5929)Online publication date: 3-Sep-2021
https://doi.org/10.3390/s21175929
Samie FBauer LHenkel J(2020)Hierarchical Classification for Constrained IoT Devices: A Case Study on Human Activity RecognitionIEEE Internet of Things Journal10.1109/JIOT.2020.29890537:9(8287-8295)Online publication date: Sep-2020
https://doi.org/10.1109/JIOT.2020.2989053
Longo FPuliafito ARana O(2019)Guest Editors’ Introduction to the Special Issue on Fog, Edge, and Cloud Integration for Smart EnvironmentsACM Transactions on Internet Technology10.1145/331940419:2(1-4)Online publication date: 12-Apr-2019
https://dl.acm.org/doi/10.1145/3319404
Samie FBauer LHenkel J(2019)From Cloud Down to Things: An Overview of Machine Learning in Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.28938666:3(4921-4934)Online publication date: Jun-2019
https://doi.org/10.1109/JIOT.2019.2893866

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Issue’s Table of Contents