research-article

Resource Constrained Offloading in Fog Computing

Authors:

Harshit Dohare,

Visali Mushunuri,

Hemant Kumar Rath,

Anantha SimhaAuthors Info & Claims

MECC '16: Proceedings of the 1st Workshop on Middleware for Edge Clouds & Cloudlets

Article No.: 1, Pages 1 - 6

https://doi.org/10.1145/3017116.3022871

Published: 12 December 2016 Publication History

Abstract

When focusing on the Internet of Things (IoT), communicating and coordinating sensor--actuator data via the cloud involves inefficient overheads and reduces autonomous behavior. The Fog Computing paradigm essentially moves the compute nodes closer to sensing entities by exploiting peers and intermediary network devices. This reduces centralized communication with the cloud and entails increased coordination between sensing entities and (possibly available) smart network gateway devices. In this paper, we analyze the utility of offloading computation among peers when working in fog based deployments. It is important to study the trade-offs involved with such computation offloading, as we deal with resource (energy, computation capacity) limited devices. Devices computing in a distributed environment may choose to locally compute part of their data and communicate the remainder to their peers. An optimization formulation is presented that is applied to various deployment scenarios, taking the computation and communication overheads into account. Our technique is demonstrated on a network of robotic sensor--actuators developed on the ROS (Robot Operating System) platform, that coordinate over the fog to complete a task. We demonstrate 77.8% latency and 54% battery usage improvements over large computation tasks, by applying this optimal offloading.

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Cited By

Sarker SArafat MLameesa AAfrin MMahmud RRazzaque MIqbal T(2024)FOLD: Fog-dew infrastructure-aided optimal workload distribution for cloud robotic operationsInternet of Things10.1016/j.iot.2024.10118526(101185)Online publication date: Jul-2024
https://doi.org/10.1016/j.iot.2024.101185
Hazra ARana PAdhikari MAmgoth T(2023)Fog computing for next-generation Internet of Things: Fundamental, state-of-the-art and research challengesComputer Science Review10.1016/j.cosrev.2023.10054948(100549)Online publication date: May-2023
https://doi.org/10.1016/j.cosrev.2023.100549
Ahammad I(2023)Fog Computing Complete Review: Concepts, Trends, Architectures, Technologies, Simulators, Security Issues, Applications, and Open Research FieldsSN Computer Science10.1007/s42979-023-02235-94:6Online publication date: 4-Oct-2023
https://doi.org/10.1007/s42979-023-02235-9
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Resource Constrained Offloading in Fog Computing
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Abstract
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cover image ACM Conferences

MECC '16: Proceedings of the 1st Workshop on Middleware for Edge Clouds & Cloudlets

December 2016

25 pages

ISBN:9781450346689

DOI:10.1145/3017116

Copyright © 2016 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]

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New York, NY, United States

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Published: 12 December 2016

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Middleware '16: 17th International Middleware Conference

December 12 - 16, 2016

Trento, Italy

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Overall Acceptance Rate 4 of 9 submissions, 44%

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Cited By

Sarker SArafat MLameesa AAfrin MMahmud RRazzaque MIqbal T(2024)FOLD: Fog-dew infrastructure-aided optimal workload distribution for cloud robotic operationsInternet of Things10.1016/j.iot.2024.10118526(101185)Online publication date: Jul-2024
https://doi.org/10.1016/j.iot.2024.101185
Hazra ARana PAdhikari MAmgoth T(2023)Fog computing for next-generation Internet of Things: Fundamental, state-of-the-art and research challengesComputer Science Review10.1016/j.cosrev.2023.10054948(100549)Online publication date: May-2023
https://doi.org/10.1016/j.cosrev.2023.100549
Ahammad I(2023)Fog Computing Complete Review: Concepts, Trends, Architectures, Technologies, Simulators, Security Issues, Applications, and Open Research FieldsSN Computer Science10.1007/s42979-023-02235-94:6Online publication date: 4-Oct-2023
https://doi.org/10.1007/s42979-023-02235-9
Kanduri AShahhosseini SNaeini EAlikhani HLiljeberg PDutt NRahmani A(2023)Edge-Centric Optimization of Multi-modal ML-Driven eHealth ApplicationsEmbedded Machine Learning for Cyber-Physical, IoT, and Edge Computing10.1007/978-3-031-40677-5_5(95-125)Online publication date: 7-Oct-2023
https://doi.org/10.1007/978-3-031-40677-5_5
Bharti SMcGibney A(2022)CoRoL: A Reliable Framework for Computation Offloading in Collaborative RobotsIEEE Internet of Things Journal10.1109/JIOT.2022.31555879:19(18195-18207)Online publication date: 1-Oct-2022
https://doi.org/10.1109/JIOT.2022.3155587
Shahhosseini SAnzanpour AAzimi ILabbaf SSeo DLim SLiljeberg PDutt NRahmani A(2022)Exploring computation offloading in IoT systemsInformation Systems10.1016/j.is.2021.101860107:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.is.2021.101860
Serdaroğlu Kİnanç BBaydere Ş(2022)Effect of Messaging Model on the Reliable Data Transfer Latency in a Fog SystemJournal of Network and Systems Management10.1007/s10922-022-09685-130:4Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s10922-022-09685-1
Gupta SSingh N(2022)Toward intelligent resource management in dynamic Fog Computing‐based Internet of Things environment with Deep Reinforcement Learning: A surveyInternational Journal of Communication Systems10.1002/dac.541136:4Online publication date: 27-Dec-2022
https://doi.org/10.1002/dac.5411
Afrin MJin JRahman ARahman AWan JHossain E(2021)Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2021.306143523:2(842-870)Online publication date: Oct-2022
https://doi.org/10.1109/COMST.2021.3061435
Alhakkak N(2021)Simulating a Smart Car Routing Model (Implementing MFR Framework) in Smart CitiesCloud and IoT‐Based Vehicular Ad Hoc Networks10.1002/9781119761846.ch16(349-368)Online publication date: 3-May-2021
https://doi.org/10.1002/9781119761846.ch16
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