QSACO: A QoS-based Self-adapted Ant Colony Optimization

被引：1

作者：

Sun, Weifeng ^{[1
]}

Xing, Yuanxun ^{[1
]}

Zhou, Chi ^{[1
]}

Zhang, Shenwei ^{[1
]}

机构：

[1] Dalian Univ Technol, Sch Software Technol, Dalian 116620, Peoples R China

来源：

2017 5TH IEEE INTERNATIONAL CONFERENCE ON MOBILE CLOUD COMPUTING, SERVICES, AND ENGINEERING (MOBILECLOUD) | 2017年

基金：

美国国家科学基金会;

关键词：

multi-UAV system; self-adaptive; QSACO; mobile cloud;

D O I：

10.1109/MobileCloud.2017.25

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Unmanned aerial vehicles have some characteristics such as strong flexibility and lower costs that are suitable for capturing information in special scenarios and environments. Collaborative working of multi-UAV system is an important performance metric for mobile computing in wireless networks. Ant Colony Algorithm is a dynamic path selecting optimization algorithm and it can be used in multi-UAV system to adapt dynamic situations. An improved ACO based on PSO algorithm called QSACO is proposed to dynamically adjust the parameters of ACO and to ensure the users' QoS demands. To solve the highcomputing- acquirement problems of QSACO, the proposed method could be used in the mobile cloud environment.

引用

页码：157 / 160

页数：4

共 50 条

[41] An ant colony optimization based layout optimization algorithm
Sun, ZG
Teng, HF
2002 IEEE REGION 10 CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND POWER ENGINEERING, VOLS I-III, PROCEEDINGS, 2002, : 675 - 678
[42] An Enhanced Ant Colony Optimization Based Algorithm to Solve QoS-Aware Web Service Composition
Dahan, Fadl
El Hindi, Khalil
Ghoneim, Ahmedy
Alsalman, Hussain
IEEE ACCESS, 2021, 9 : 34098 - 34111
[43] An Improved Ant Colony Optimization for QoS-Aware Web Service Composition
Chen, Jiacong
Zhou, Jingquan
2020 EIGHTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD 2020), 2020, : 20 - 24
[44] A Modify Ant Colony Optimization for the Grid Jobs Scheduling Problem with QoS Requirements
Pu, Xun
Lu, XianLiang
INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2011), 2011, 8285
[45] Enhancement of Ant Colony Optimization for QoS-Aware Web Service Selection
Alayed, Hashem
Dahan, Fadl
Alfakih, Taha
Mathkour, Hassan
Arafah, Mohammed
IEEE ACCESS, 2019, 7 : 97041 - 97051
[46] Shape Matching Based on Ant Colony Optimization
Zhu, Xiangbin
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES, 2008, 15 : 101 - 108
[47] Population based ant colony optimization on FPGA
Guntsch, M
Middendorf, M
Scheuermann, B
Diessel, O
ElGindy, H
Schmeck, H
So, K
2002 IEEE INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (FPT), PROCEEDINGS, 2002, : 125 - 132
[48] Ant Colony Optimization based clustering methodology
Inkaya, Tulin
Kayaligil, Sinan
Ozdemirel, Nur Evin
APPLIED SOFT COMPUTING, 2015, 28 : 301 - 311
[49] Group-Based Ant Colony Optimization
Voelkel, Gunnar
Maucher, Markus
Kestler, Hans A.
GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2013, : 121 - 128
[50] Ant Colony Optimization Based TDM for DUA
Goel, Shivendra
PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, 2016, : 42 - 44

← 1 2 3 4 5 →