Multi-objective optimization of advanced sleep mode for energy saving in cognitive radio network

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications Pub Date : 2025-06-13 DOI:10.1016/j.comcom.2025.108232

Ajay Singh, Rakhee Kulshrestha, Vijaypal Poonia

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引用次数: 0

Abstract

The Advanced Sleep Modes (ASM) concept corresponds to entering the Base Station (BS) progressively deeper and less energy-intensive states to reduce energy consumption. Introducing the ASM can mitigate energy wastage during low-traffic periods in the Cognitive Radio Network (CRN). In this study, we propose a strategy for integrating ASM within the CRN architecture to effectively handle primary and secondary traffic across varying ASM sleep states. Additionally, we study the general scenario of CRN with heterogeneous secondary users, imperfect sensing, and unreliable BS due to the arrival of negative packets (virus attack). By modeling the entire system as a three-dimensional discrete-time Markov chain, we conduct the transient analysis of the proposed model. Through numerical demonstrations involving reliability and queueing analyses, we substantiate the validity of the proposed model and examine the impact of reliability on its performance. Then, we showcased the effectiveness of the ASM strategy by comparing it with the Sleep Mode (SM) strategy in terms of the waiting time and blocking probability of the secondary user and the degree of energy savings. Also, simulation experiments are conducted to corroborate the accuracy and validity of the numerical results. Finally, we formulate the Cost Benefit Function (CBF), which depends on both the successful transmission and waiting time of secondary packets. Subsequently, we obtain the Pareto optimal solution for CBF and the degree of energy saving using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques for multi-objective optimization.

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面向认知无线网络节能的高级睡眠模式多目标优化

高级睡眠模式（ASM）概念对应于逐步进入基站（BS）更深和更低能耗的状态，以减少能源消耗。引入ASM可以缓解认知无线网络（CRN）低流量时段的能量浪费。在本研究中，我们提出了一种将ASM集成到CRN架构中的策略，以有效地处理不同ASM睡眠状态下的主流量和从流量。此外，我们还研究了具有异构辅助用户、不完全感知和由于负数据包到达（病毒攻击）而导致的不可靠BS的CRN的一般场景。通过将整个系统建模为三维离散马尔可夫链，我们对所提出的模型进行了瞬态分析。通过涉及可靠性和排队分析的数值演示，我们证实了所提出模型的有效性，并检验了可靠性对其性能的影响。然后，通过将ASM策略与休眠模式（SM）策略在次要用户的等待时间和阻塞概率以及节能程度方面进行比较，证明了ASM策略的有效性。通过仿真实验验证了数值结果的准确性和有效性。最后，我们建立了成本效益函数（Cost - Benefit Function， CBF），该函数依赖于二次包的成功传输和等待时间。随后，利用非支配排序遗传算法（NSGA-II）和多目标粒子群优化（MOPSO）技术进行多目标优化，得到了CBF的Pareto最优解和节能程度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Communications 工程技术-电信学

CiteScore

14.10

自引率

5.00%

发文量

397

审稿时长

66 days

期刊介绍： Computer and Communications networks are key infrastructures of the information society with high socio-economic value as they contribute to the correct operations of many critical services (from healthcare to finance and transportation). Internet is the core of today''s computer-communication infrastructures. This has transformed the Internet, from a robust network for data transfer between computers, to a global, content-rich, communication and information system where contents are increasingly generated by the users, and distributed according to human social relations. Next-generation network technologies, architectures and protocols are therefore required to overcome the limitations of the legacy Internet and add new capabilities and services. The future Internet should be ubiquitous, secure, resilient, and closer to human communication paradigms. Computer Communications is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and survey papers covering all aspects of future computer communication networks (on all layers, except the physical layer), with a special attention to the evolution of the Internet architecture, protocols, services, and applications.