An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure

A Master of Science thesis in Computer Engineering by Ahmed Fahmy entitled, “An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure”, submitted in February 2020. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Taha Landolsi. Soft copy...

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Main Author: Fahmy, Ahmed (author)
Format: doctoralThesis
Published: 2020
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Online Access:http://hdl.handle.net/11073/16647
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author Fahmy, Ahmed
author_facet Fahmy, Ahmed
author_role author
dc.contributor.none.fl_str_mv Aburukba, Raafat
Landolsi, Taha
dc.creator.none.fl_str_mv Fahmy, Ahmed
dc.date.none.fl_str_mv 2020-03-03T09:11:53Z
2020-03-03T09:11:53Z
2020-02
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2020.02
http://hdl.handle.net/11073/16647
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Fog Computing
IoT
5G networks
Agent
Auction
Scheduling
Optimization
Game Theory
Decentralized
dc.title.none.fl_str_mv An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Computer Engineering by Ahmed Fahmy entitled, “An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure”, submitted in February 2020. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Taha Landolsi. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).
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identifier_str_mv 35.232-2020.02
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/16647
publishDate 2020
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spelling An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G InfrastructureFahmy, AhmedFog ComputingIoT5G networksAgentAuctionSchedulingOptimizationGame TheoryDecentralizedA Master of Science thesis in Computer Engineering by Ahmed Fahmy entitled, “An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure”, submitted in February 2020. Thesis advisor is Dr. Raafat Aburukba and thesis co-advisor is Dr. Taha Landolsi. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).The advent of the Internet of Things (IoT) has brought an unprecedented increase in the number of connected devices. Recently, IoT-based devices have been used in several applications including healthcare, data analytics, smart cities, and many others. Time-sensitive applications, such as Vehicle-to-Vehicle (V2V) communication, led to the need for an Ultra-High Reliable Low Latency Communication (URLLC). Consequently, 5G networks gained massive attention from the research community due to its ability to support enormous amounts of transfer rate. One of the main supporting computing paradigms for IoT is cloud computing, as it offers computing capabilities over the Internet. Nevertheless, cloud computing is unsuitable for time-critical applications. Hence, researchers proposed deploying fog computing as part of the 5G small cells to tackle the deficiencies of cloud computing. Many challenges arise while combining 5G technology and fog computing such as scheduling service requests across small cells to reduce the overall latency. In this work, the scheduling problem is modeled as an optimization problem with the objective of minimizing the overall latency. Furthermore, small cells are decentralized by nature. Therefore, a coordination framework is proposed to handle the interdependency between small cells. Accordingly, the decentralized scheduling problem is mapped to a combinatorial auction optimization problem. The proposed optimization model is validated using an optimization engine. The scheduling problem is known as an NP-hard problem. Thus, a decentralized heuristic solution is proposed to solve the scheduling problem in polynomial time. The proposed solution integrates a novel Simulated Annealing-Based Scheduling (SABS) and Auction-Based Winner Determination (ABWD) heuristic algorithms. To assess the performance and quality of the proposed heuristic solution, a centralized approach is used as a benchmark. Furthermore, sensitivity analysis is conducted in which the impact of each system parameter on the system behavior is investigated. The results prove the adequacy of the proposed solution as the execution time remained approximately constant, with an average of 726 μs, considering different problem sizes. Moreover, the proposed solution is found to be scalable and accommodates the exponential growth of IoT devices.College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)Aburukba, RaafatLandolsi, Taha2020-03-03T09:11:53Z2020-03-03T09:11:53Z2020-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2020.02http://hdl.handle.net/11073/16647en_USoai:repository.aus.edu:11073/166472026-02-16T06:45:27Z
spellingShingle An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
Fahmy, Ahmed
Fog Computing
IoT
5G networks
Agent
Auction
Scheduling
Optimization
Game Theory
Decentralized
status_str publishedVersion
title An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
title_full An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
title_fullStr An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
title_full_unstemmed An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
title_short An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
title_sort An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
topic Fog Computing
IoT
5G networks
Agent
Auction
Scheduling
Optimization
Game Theory
Decentralized
url http://hdl.handle.net/11073/16647