skip to main content
10.1145/3127540.3127578acmconferencesArticle/Chapter ViewAbstractPublication PagesmswimConference Proceedingsconference-collections
short-paper

Providing Computing Services through Mobile Devices in a Collaborative Way - A Fog Computing Case Study

Published: 21 November 2017 Publication History

Abstract

The increasing number of mobile devices, such as smartphones, tablets and laptops, and also advances in their computing power enabled them to be considered as computing resources, having their proximity explored. The use of nearby resources for computing is growing year by year and it is called Fog Computing. The elements on the edge of the Internet are exploited once the computer service providers could be unavailable or overloaded. This work focuses on using mobile devices to provide computing services by using an heuristic called Adapted Maximum Regret, which tries to minimize energy and avoid unreliable devices. There is also a top-level meta-heuristic which has global information and interconnects different clusters of devices on the edge of the Internet to guarantee QoS. We conducted a set of experiments that demonstrated we should avoid devices with a high degree of failures to save more energy when allocating tasks as well as to decrease the applications response time and communication through adjustments in the selection algorithm of external agglomerates.

References

[1]
Luiz César Borro. 2013. Escalonamento em grades móveis: uma abordagem ciente do consumo de energia. Master's thesis. Universidade de São Paulo.
[2]
Per Nikolaj D Bukh and Raj Jain. 1992. The art of computer systems performance analysis, techniques for experimental design, measurement, simulation and modeling. (1992).
[3]
Valeria Cardellini, Vincenzo Grassi, Francesco Lo Presti, and Matteo Nardelli. 2015. On QoS-aware scheduling of data stream applications over fog computing infrastructures. In Computers and Communication (ISCC), 2015 IEEE Symposium on. IEEE, 271--276.
[4]
Amir Vahid Dastjerdi, Harshit Gupta, Rodrigo N Calheiros, Soumya K Ghosh, and Rajkumar Buyya. 2016. Fog Computing: Principals, Architectures, and Applications. arXiv preprint arXiv:1601.02752 (2016).
[5]
M.D. Dikaiakos, D. Katsaros, P. Mehra, G. Pallis, and A Vakali. 2009. Cloud Computing: Distributed Internet Computing for IT and Scientific Research. Internet Computing, IEEE 13, 5 (Sept 2009), 10--13. https://doi.org/10.1109/MIC.2009.103
[6]
Hoang T Dinh, Chonho Lee, Dusit Niyato, and Ping Wang. 2013. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless communications and mobile computing 13, 18 (2013), 1587--1611.
[7]
Paul A Fishwick. 1992. SimPack: getting started with simulation programming in C and C++. In Proceedings of the 24th conference on Winter simulation. ACM, 154--162.
[8]
Gonzalo Huerta-Canepa and Dongman Lee. 2010. A virtual cloud computing provider for mobile devices. In Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond. ACM, 6.
[9]
Priya A Kotwal and Adwitiy R Singh. 2012. Evolution and effects of mobile cloud computing, middleware services on cloud, future prospects: A peek into the mobile cloud operating systems. In Computational Intelligence & Computing Research (ICCIC), 2012 IEEE International Conference on. IEEE, 1--5.
[10]
Antonios Litke, Dimitrios Skoutas, Konstantinos Tserpes, and Theodora Varvarigou. 2007. Efficient task replication and management for adaptive fault tolerance in mobile grid environments. Future Generation Computer Systems 23, 2 (2007), 163--178.
[11]
Hazem Morsy and Hesham El-Rewini. 2013. Adaptive scheduling in a mobile ad-hoc grid for time-sensitive computing. In Computer Systems and Applications (AICCSA), 2013 ACS International Conference on. IEEE, 1--8.
[12]
Sung-Hoon Park, Tae-Gyu Lee, Hyung-Seok Seo, Seok-Jin Kwon, and Jong-Ho Han. 2009. An Election Protocol in Mobile Ad Hoc Distributed Systems. In Information Technology: New Generations, 2009. ITNG '09. Sixth International Conference on. 628--633. https://doi.org/10.1109/ITNG.2009.61
[13]
Pham Phuoc Hung and Eui-Nam Huh. 2015. An adaptive procedure for task scheduling optimization in mobile cloud computing. Mathematical Problems in Engineering 2015 (2015).
[14]
Danilo Costa Marim Segura. 2016. Integrando grades móveis em uma arquitetura orientada a serviços. Master's thesis. Universidade de São Paulo.
[15]
S. Vasudevan, J. Kurose, and D. Towsley. 2004. Design and analysis of a leader election algorithm for mobile ad hoc networks. In Network Protocols, 2004. ICNP 2004. Proceedings of the 12th IEEE International Conference on. 350--360. https: //doi.org/10.1109/ICNP.2004.1348124

Cited By

View all
  • (2023)Blockchain search engine: Its current research status and future prospect in Internet of Things networkFuture Generation Computer Systems10.1016/j.future.2022.08.008138(120-141)Online publication date: Jan-2023
  • (2020)Using Collaborative Edge-Cloud Cache for Search in Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.29463897:2(922-936)Online publication date: Feb-2020
  • (2020)Efficient Search for Moving Object Devices in Internet of Things Networks2020 IEEE International Conference on Web Services (ICWS)10.1109/ICWS49710.2020.00067(454-462)Online publication date: Oct-2020
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
MSWiM '17: Proceedings of the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems
November 2017
340 pages
ISBN:9781450351621
DOI:10.1145/3127540
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 the author(s) 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].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 November 2017

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. fog computing
  2. mobile grid

Qualifiers

  • Short-paper

Funding Sources

  • Capes
  • FAPESP
  • CNPq

Conference

MSWiM '17
Sponsor:

Acceptance Rates

MSWiM '17 Paper Acceptance Rate 29 of 142 submissions, 20%;
Overall Acceptance Rate 398 of 1,577 submissions, 25%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 10 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2023)Blockchain search engine: Its current research status and future prospect in Internet of Things networkFuture Generation Computer Systems10.1016/j.future.2022.08.008138(120-141)Online publication date: Jan-2023
  • (2020)Using Collaborative Edge-Cloud Cache for Search in Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.29463897:2(922-936)Online publication date: Feb-2020
  • (2020)Efficient Search for Moving Object Devices in Internet of Things Networks2020 IEEE International Conference on Web Services (ICWS)10.1109/ICWS49710.2020.00067(454-462)Online publication date: Oct-2020
  • (2018)Improved Convolutional Neural Network for Chinese Sentiment Analysis in Fog ComputingWireless Communications & Mobile Computing10.1155/2018/93401942018Online publication date: 23-Sep-2018
  • (2018) E 2 R‐F 2 N: Energy‐efficient retailing using a femtolet‐based fog network Software: Practice and Experience10.1002/spe.267349:3(498-523)Online publication date: 17-Dec-2018
  • (2017)Big Data Mining Algorithms for Fog ComputingProceedings of the International Conference on Big Data and Internet of Thing10.1145/3175684.3175730(57-61)Online publication date: 20-Dec-2017

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media