Whale Optimization Algorithm With Applications to Resource Allocation in Wireless Networks

Resource allocation plays a pivotal role in improving the performance of wireless and communication networks. However, the optimization of resource allocation is typically formulated as a mixed-integer non-linear programming (MINLP) problem, which is non-convex and NP-hard by nature. Usually, solvin...

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Vydané v:	IEEE transactions on vehicular technology Ročník 69; číslo 4; s. 4285 - 4297
Hlavní autori:	Pham, Quoc-Viet, Mirjalili, Seyedali, Kumar, Neeraj, Alazab, Mamoun, Hwang, Won-Joo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Communication networks Communication system security Computation offloading Edge computing Global optimization Heuristic algorithms Linear programming Machine learning meta-heuristic optimization Mobile computing non-orthogonal multiple access Nonlinear programming Optimization Optimization algorithms Resource allocation Resource management whale optimization algorithm Whales Wireless and communication networks Wireless communications Wireless networks
ISSN:	0018-9545, 1939-9359
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Abstract	Resource allocation plays a pivotal role in improving the performance of wireless and communication networks. However, the optimization of resource allocation is typically formulated as a mixed-integer non-linear programming (MINLP) problem, which is non-convex and NP-hard by nature. Usually, solving such a problem is challenging and requires specific methods due to the major shortcomings of the traditional approaches, such as exponential computation complexity of global optimization, no performance optimality guarantee of heuristic schemes, and large training time and generating a standard dataset of machine learning based approaches. Whale optimization algorithm (WOA) has recently gained the attention of the research community as an efficient method to solve a variety of optimization problems. As an alternative to the existing methods, our main goal in this article is to study the applicability of WOA to solve resource allocation problems in wireless networks. First, we present the fundamental backgrounds and the binary version of the WOA as well as introducing a penalty method to handle optimization constraints. Then, we demonstrate three examples of WOA to resource allocation in wireless networks, including power allocation for energy-and-spectral efficiency tradeoff in wireless interference networks, power allocation for secure throughput maximization, and mobile edge computation offloading. Lastly, we present the adoption of WOA to solve a variety of potential resource allocation problems in 5G wireless networks and beyond.
AbstractList	Resource allocation plays a pivotal role in improving the performance of wireless and communication networks. However, the optimization of resource allocation is typically formulated as a mixed-integer non-linear programming (MINLP) problem, which is non-convex and NP-hard by nature. Usually, solving such a problem is challenging and requires specific methods due to the major shortcomings of the traditional approaches, such as exponential computation complexity of global optimization, no performance optimality guarantee of heuristic schemes, and large training time and generating a standard dataset of machine learning based approaches. Whale optimization algorithm (WOA) has recently gained the attention of the research community as an efficient method to solve a variety of optimization problems. As an alternative to the existing methods, our main goal in this article is to study the applicability of WOA to solve resource allocation problems in wireless networks. First, we present the fundamental backgrounds and the binary version of the WOA as well as introducing a penalty method to handle optimization constraints. Then, we demonstrate three examples of WOA to resource allocation in wireless networks, including power allocation for energy-and-spectral efficiency tradeoff in wireless interference networks, power allocation for secure throughput maximization, and mobile edge computation offloading. Lastly, we present the adoption of WOA to solve a variety of potential resource allocation problems in 5G wireless networks and beyond.
Author	Pham, Quoc-Viet Kumar, Neeraj Hwang, Won-Joo Alazab, Mamoun Mirjalili, Seyedali
Author_xml	– sequence: 1 givenname: Quoc-Viet orcidid: 0000-0002-9485-9216 surname: Pham fullname: Pham, Quoc-Viet email: vietpq@pusan.ac.kr organization: Research Institute of Computer, Information and Communication, Inje University to Pusan National University, Busan, South Korea – sequence: 2 givenname: Seyedali surname: Mirjalili fullname: Mirjalili, Seyedali email: ali.mirjalili@gmail.com, ali.mirjalili@laureate.edu.au organization: Center for Artificial Intelligence Research and Optimization, Torrens University Australia, Brisbane, Australia – sequence: 3 givenname: Neeraj orcidid: 0000-0002-3020-3947 surname: Kumar fullname: Kumar, Neeraj email: neeraj.kumar@thapar.edu organization: Department of Computer Science and Engineering, Thapar University, Patiala, India – sequence: 4 givenname: Mamoun orcidid: 0000-0002-1928-3704 surname: Alazab fullname: Alazab, Mamoun email: alazab.m@ieee.org organization: College of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT, Australia – sequence: 5 givenname: Won-Joo orcidid: 0000-0001-8398-564X surname: Hwang fullname: Hwang, Won-Joo email: wjhwang@pusan.ac.kr organization: Department of Biomedical Convergence Engineering, Pusan National University, Busan, South Korea
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StartPage	4285
SubjectTerms	Algorithms Communication networks Communication system security Computation offloading Edge computing Global optimization Heuristic algorithms Linear programming Machine learning meta-heuristic optimization Mobile computing non-orthogonal multiple access Nonlinear programming Optimization Optimization algorithms Resource allocation Resource management whale optimization algorithm Whales Wireless and communication networks Wireless communications Wireless networks
Title	Whale Optimization Algorithm With Applications to Resource Allocation in Wireless Networks
URI	https://ieeexplore.ieee.org/document/8993843 https://www.proquest.com/docview/2392111051
Volume	69
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