{"title":"Cost-Aware Resource Allocation with Probabilistic Latency Guarantee in B5G Industrial Private Networks","authors":"Maosheng Zhu, Xi Li, Hong Ji, Heli Zhang","doi":"10.1109/iccworkshops53468.2022.9814520","DOIUrl":null,"url":null,"abstract":"Industrial private networks (IPNs), having enhanced communication characteristics in a specific area, emerge to fulfill the demanding industrial use cases. However, users' demands for flexibility and low latency in the B5G era are in inevitable conflict with limited and isolated resources in IPNs; thus, scalability and flexibility of resources are required, which can be realized by jointly funneling users' traffic and resource allocation spanning IPN s to promote load balancing and resource efficiency. In this paper, we devise a cost-aware resource allocation (CARA) approach embedded with a proba-bilistic latency guarantee for resource efficiency achievement and low latency fulfillment. Specifically, we first establish a unified cost model for coupling funneled traffic and resource allocated in each lPN, avoiding the optimization penalty of alternating them. Then, to solve the conflict between limited computing and communication resources, we propose the CARA approach based on the non-dominated sorting genetic algorithm-III (NSGA-III). Furthermore, a probabilistic latency guarantee sub-algorithm is embedded in CARA to fulfill the latency constraint and relax it for advanced industrial implementation. Additionally, compared with other existing algorithms, simulation results reveal that our proposed algorithm not only globally minimizes unified cost across IPNs, but also individually balances the funneled traffic.","PeriodicalId":102261,"journal":{"name":"2022 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Communications Workshops (ICC Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccworkshops53468.2022.9814520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Industrial private networks (IPNs), having enhanced communication characteristics in a specific area, emerge to fulfill the demanding industrial use cases. However, users' demands for flexibility and low latency in the B5G era are in inevitable conflict with limited and isolated resources in IPNs; thus, scalability and flexibility of resources are required, which can be realized by jointly funneling users' traffic and resource allocation spanning IPN s to promote load balancing and resource efficiency. In this paper, we devise a cost-aware resource allocation (CARA) approach embedded with a proba-bilistic latency guarantee for resource efficiency achievement and low latency fulfillment. Specifically, we first establish a unified cost model for coupling funneled traffic and resource allocated in each lPN, avoiding the optimization penalty of alternating them. Then, to solve the conflict between limited computing and communication resources, we propose the CARA approach based on the non-dominated sorting genetic algorithm-III (NSGA-III). Furthermore, a probabilistic latency guarantee sub-algorithm is embedded in CARA to fulfill the latency constraint and relax it for advanced industrial implementation. Additionally, compared with other existing algorithms, simulation results reveal that our proposed algorithm not only globally minimizes unified cost across IPNs, but also individually balances the funneled traffic.
工业专用网络(IPNs)在特定领域具有增强的通信特性,可以满足苛刻的工业用例。然而,B5G时代用户对灵活性和低时延的需求与IPNs有限、孤立的资源不可避免地发生冲突;因此,对资源的可扩展性和灵活性提出了更高的要求,这可以通过跨IPN共同汇集用户流量和资源分配来实现,以促进负载均衡和资源效率。在本文中,我们设计了一种成本感知资源分配(CARA)方法,该方法嵌入了概率延迟保证,以实现资源效率和低延迟实现。具体而言,我们首先建立了一个统一的成本模型,将漏斗流量和资源分配耦合到每个lPN中,避免了它们交替的优化惩罚。然后,为了解决有限的计算资源和通信资源之间的冲突,我们提出了基于非支配排序遗传算法- iii (NSGA-III)的CARA方法。此外,在CARA中嵌入了概率延迟保证子算法,以满足延迟约束,并放宽延迟约束,以便于高级工业实现。此外,与其他现有算法相比,仿真结果表明,我们提出的算法不仅在全局上最大限度地降低了ipn之间的统一成本,而且在各个ipn之间实现了流量均衡。