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Genetic Algorithm for Time-Effective IoT Service Function Placement

Authors:
Arvind Kalyan

Keywords: Keywords – Internet of Things; IoT Service Function Chaining; Minimax Problem; Genetic Algorithm; Natural Selection; Fitness.

Abstract:
This paper focuses on the concept of IoT Service Function Chains (IoTSFC): a set of Internet of Things (IoT) Network Functions that must be allocated and implemented on IoT nodes in a specific order. Our problem is of Integer Linear Programming (ILP) type and therefore NP-Hard, so an optimal solution cannot be found in polynomial time. Therefore, we attempt to devise a heuristic method to solve the problem at a lower time complexity. The paper develops a solution using a genetic algorithm that attempts to minimize the total processing time and incurred transmission delay time required to execute a group of network functions across IoT nodes. The genetic algorithm is run on a string denoting placement of the network functions and runs a set of genetic operators in order to work toward an optimal solution. Our experimental results are encouraging, however, remain in progress.

Pages: 23 to 27

Copyright: Copyright (c) IARIA, 2019

Publication date: November 24, 2019

Published in: conference

ISSN: 2163-9027

ISBN: 978-1-61208-753-5

Location: Valencia, Spain

Dates: from November 24, 2019 to November 28, 2019