Open AccessSimulated Annealing-Based Multilink Selection Algorithm in SDN-Enabled Avionic Networks
Author(s) -
Doanh Kim Luong,
Muhammad Ali,
Yim Fun Hu,
Jian Ping Li,
Rameez Asif,
Kanaan Abdo
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3121622
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In this paper, a novel multilink selection framework is developed for different applications with various quality of service (QoS) requirements in avionic systems, based on the multi-attribute decision-making model. Two metaheuristic algorithms are proposed to solve this model while optimizing the multilink selection performances. Multilink configuration and multi-homing capabilities are generally required for aircrafts operating in a heterogeneous wireless network environment. The first algorithm, called Analytic Hierarchy Process and Simulated Annealing (AHP-SA), utilizes a two-phase process. In Phase one, an analytic hierarchy process (AHP) is used to choose the decision weight factors. Then, in Phase two, a simulated annealing process is applied to select suitable networks, for various service requests, based on the weights obtained from first phase. Further, to improve customer satisfaction, Simulated Annealing algorithm for Simultaneous Weights and Network Selection Optimisation (SA-SWNO) is developed, in which a simulated annealing algorithm is applied to dynamically optimize weight factors of objective functions and the request-to-network assignment matrix. Simulation results demonstrate that both proposed algorithms outperform the commonly used price-based or QoS-based network selection scheme with much higher averaged satisfaction degree and lower computational complexity.