Application of improved discrete marine predatiors algorithm in network cost optimization

GAO Ming; SHEN Yicheng; LIU Ming

doi:10.11959/j.issn.1000-0801.2025118

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Application of improved discrete marine predatiors algorithm in network cost optimization

Research and Development | 更新时间：2025-09-04

- Application of improved discrete marine predatiors algorithm in network cost optimization
- Telecommunications Science Vol. 41, Issue 8, Pages: 86-100(2025)
- 作者机构：
  
  1.浙江工商大学信息与电子工程学院，浙江杭州 310018
  2.浙江工业大学计算机科学与技术学院，浙江杭州 310023
- 作者简介：
- 基金信息：
  
  Zhejiang Key Laboratory of New Network Standards and Application Technology(2013E10012)
- DOI：10.11959/j.issn.1000-0801.2025118
  CLC： TP393
- Received：21 December 2024，
  
  Revised：2025-03-13，
  
  Published：20 August 2025
- 稿件说明：
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高明,沈艺程,刘铭.改进的海洋生物捕食算法在网络成本优化上的应用[J].电信科学,2025,41(08):86-100.

GAO Ming,SHEN Yicheng,LIU Ming.Application of improved discrete marine predatiors algorithm in network cost optimization[J].Telecommunications Science,2025,41(08):86-100.
高明,沈艺程,刘铭.改进的海洋生物捕食算法在网络成本优化上的应用[J].电信科学,2025,41(08):86-100. DOI： 10.11959/j.issn.1000-0801.2025118.

GAO Ming,SHEN Yicheng,LIU Ming.Application of improved discrete marine predatiors algorithm in network cost optimization[J].Telecommunications Science,2025,41(08):86-100. DOI： 10.11959/j.issn.1000-0801.2025118.

摘要

容器技术作为轻量级虚拟化方案，已成为多云网络架构的核心支撑技术，但跨云通信的高昂成本仍是关键挑战。创新点在于将多云网络资源调度问题建模为二次分配问题（QAP），并提出一种改进的离散海洋捕食算法（DMPA）。DMPA通过以下策略显著提升性能：基于均匀分布与伪反向学习的混合种群初始化策略，避免初始解陷入局部最优；引入自适应收敛因子动态调整搜索范围，平衡全局探索与局部开发；采用可变交换间隔的2-exchange突变策略，增强种群多样性；结合禁忌搜索优化精英解，避免重复搜索。实验表明，DMPA在30个QAP实例中22个达到已知最优解，平均偏差率低于3%；在多云网络真实数据集下，优化效果明显，通信成本有所降低。相比MPA、HPSO等算法，DMPA在优化精度与稳定性上均表现突出，为多云网络成本优化提供了高效解决方案。

Abstract

Container technology

as a lightweight virtualization solution

remains a core supporting technology for multi-cloud network architectures. However

the high cost of cross-cloud communication remains a critical challenge. The key innovation of models of the resource scheduling problem in multi-cloud networks as a quadratic assignment problem (QAP) and an improved discrete marine predators algorithm (DMPA) was proposed. The DMPA was significantly enhanced performance through the following strategies: a hybrid population initialization strategy based on uniform distribution and pseudo-reverse learning

which avoided the initial solution from falling into local optima; an adaptive convergence factor was introduced to dynamically adjust the search range

balancing global exploration and local exploitation; a 2-exchange mutation strategy with variable exchange intervals was employed to enhance population diversity; the integration of tabu search to optimize elite solutions and avoid repetitive searches. Experiments show that DMPA achieves known optimal solutions in 22 out of 30 QAP instances

with an average deviation rate of less than 3%. Under real-world multi-cloud network datasets

the optimization effect is significant

and communication costs are reduced. Compared to algorithms such as MPA and HPSO

DMPA demonstrates outstanding performance in both optimization accuracy and stability

providing an efficient solution for cost optimization in multi-cloud networks.

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references

中国信息通信研究院 . 云原生发展白皮书（2020 年） [R ] . 2020 .

China Academy for Information and Communications Technology . Cloud native development white paper (2020) [R ] . 2020 .

ACHAR S . An overview of environmental scalability and security in hybrid cloud infrastructure designs [J ] . Asia Pacific Journal of Energy and Environment , 2021 , 8 ( 2 ): 39 - 46 .

VIEIRA C C A , BITTENCOURT L F , GENEZ T A L , et al . RAaaS: Resource Allocation as a Service in multiple cloud providers [J ] . Journal of Network and Computer Applications , 2024 , 221 : 103790 .

MANGALAMPALLI S S , KARRI G R , MOHANTY S N , et al . Multi-objective prioritized task scheduler using improved asynchronous advantage actor critic (a3c) algorithm in multi cloud environment [J ] . IEEE Access , 2024 , 12 : 11354 - 11377 .

SURESH P , KEERTHIKA P , MANJULA DEVI R , et al . Optimized task scheduling approach with fault tolerant load balancing using multi-objective cat swarm optimization for multi-cloud environment [J ] . Applied Soft Computing , 2024 , 165 : 112129 .

ABUALIGAH L , DIABAT A , MIRJALILI S , et al . The arithmetic optimization algorithm [J ] . Computer Methods in Applied Mechanics and Engineering , 2021 , 376 : 113609 .

MOIN M M , NARAYAN D G , PATIL S . A hybrid bio-inspired algorithm for routing in software defined networks [C ] // Proceedings of the 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) . Piscataway : IEEE Press , 2021 : 1 - 7 .

FULBER-GARCIA V , LUIZELLI M C , DOS SANTOS C R P , et al . Customizable mapping of virtualized network services in multi-datacenter environments based on genetic metaheuristics [J ] . Journal of Network and Systems Management , 2023 , 31 ( 4 ): 71 .

RANKOTHGE W , MA J F , LE F , et al . Towards making network function virtualization a cloud computing service [C ] // Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM) . Piscataway : IEEE Press , 2015 : 89 - 97 .

CAÑETE A , AMOR M , FUENTES L . HADES: an NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures [J ] . Journal of Network and Computer Applications , 2024 , 221 : 103764 .

MIANO S , RISSO F , BERNAL M V , et al . A framework for eBPF-based network functions in an era of microservices [J ] . IEEE Transactions on Network and Service Management , 2021 , 18 ( 1 ): 133 - 151 .

WANG Z , SUN D , XUE G T , et al . Ada-Things: an adaptive virtual machine monitoring and migration strategy for Internet of Things applications [J ] . Journal of Parallel and Distributed Computing , 2019 , 132 : 164 - 176 .

MARQUES G , SENNA C , SARGENTO S , et al . Proactive resource management for cloud of services environments [J ] . Future Generation Computer Systems , 2024 , 150 : 90 - 102 .

FARAMARZI A , HEIDARINEJAD M , MIRJALILI S , et al . Marine predators algorithm: a nature-inspired metaheuristic [J ] . Expert Systems with Applications , 2020 , 152 : 113377 .

CIEPLIŃSKI P , GOLAK S . Crossover operator inspired by the selection operator for an evolutionary task sequencing algorithm [J ] . Applied Sciences , 2024 , 14 ( 24 ): 11786 .

TAILLARD E . Robust taboo search for the quadratic assignment problem [J ] . Parallel Computing , 1991 , 17 ( 4/5 ): 443 - 455 .

BURKARD R E , ÇELA E , KARISCH S E , et al . QAPLIB [DB ] . 2011 .

SADIQ A S , DEHKORDI A A , MIRJALILI S , et al . Nonlinear marine predator algorithm: a cost-effective optimizer for fair power allocation in NOMA-VLC-B5G networks [J ] . Expert Systems with Applications , 2022 , 203 : 117395 .

AMIRTEIMOORI A , MAHDAVI I , SOLIMANPUR M , et al . A parallel hybrid PSO-GA algorithm for the flexible flow-shop scheduling with transportation [J ] . Computers & Industrial Engineering , 2022 , 173 : 108672 .

KıLıÇ H , YUZGEC U Y . Improved antlion optimization algorithm for quadratic assignment problem [J ] . Malaysian Journal of Computer Science , 2021 , 34 ( 1 ): 34 - 60 .

XUE J K , SHEN B . Dung beetle optimizer: a new meta-heuristic algorithm for global optimization [J ] . The Journal of Supercomputing , 2023 , 79 ( 7 ): 7305 - 7336 .

高明 , 刘铭 , 陈泱婷 , 等 . 基于Kubernetes的多云网络成本优化模型 [J ] . 电信科学 , 2023 , 39 ( 2 ): 71 - 82 .

GAO M , LIU M , CHEN Y T , et al . Cost optimization model for multi-cloud network based on Kubernetes [J ] . Telecommunications Science , 2023 , 39 ( 2 ): 71 - 82 .

SADEGHI M , AGHAYAN I , GHAZNAVI M . A cuckoo search based approach to design sustainable transit network [J ] . Transportation Letters , 2021 , 13 ( 9 ): 635 - 648 .

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