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Hybrid fog/cloud computing resource allocation: Joint consideration of limited communication resources and user credibility

机译:混合雾/云计算资源分配:联合考虑有限的通信资源和用户可信度

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摘要

In this paper, we study the communication and computation resource allocation problem with the assumption of enough computation resources but limited communication resources. This assumption is indeed practical in a hybrid fog/cloud computing system, when there exists a large amount of data to be executed. More specifically, a powerful cloud computing center can help fog nodes (FNs) release the heavy computation burden. Namely, with the assistance of cloud computing, the system usually has enough computation resources to execute such computation-intensive applications. However, since the system has a certain amount of subchannels, the communication resources of the system may be limited at times, especially when the number of subchannels is insufficient. Therefore, with the aim of handling tasks in an energy efficient way, we propose a communication resource-aware cooperated with computation resources (CRACCR) scheme which has two components. The one is called spectral multiplexing computation consideration, where the system multiplexes communication resources under the consideration of computation resource allocation. The other is called FN scale adjustment (FNSA), where the number of FNs in use is influenced by the communication resource allocation. Furthermore, to develop a user-aware CRACCR scheme, we also design a mechanism to sketch users' credibility. Then a limited communication resource allocation problem with the consideration of user credibility is formulated as a mixed integer non-linear programming problem (MINLP). After transforming the problem by l(p)-box constraints and scale conversion, the problem is tackled by the alternating direction multiplier method. Simulation results prove the improvement of energy efficiency achieved by the proposed scheme, and show the variation of FNs' number while considering the communication resource allocation.
机译:在本文中,我们通过假设足够的计算资源但通信资源有限,研究通信和计算资源分配问题。当存在要执行大量数据时,这种假设在混合雾/云计算系统中确实是实用的。更具体地说,强大的云计算中心可以帮助雾节点(FNS)释放沉重的计算负担。即,在云计算的帮助下,系统通常具有足够的计算资源来执行此类计算密集型应用程序。然而,由于系统具有一定量的子信道,因此系统的通信资源可能有时受到限制,尤其是当子信道的数量不足时。因此,通过以节能方式处理任务,我们提出了一种与具有两个组件的计算资源(CRACCR)方案的通信资源知识。该一个被称为光谱复用计算考虑,其中系统在考虑计算资源分配下复用通信资源。另一个被称为FN比例调整(FNSA),其中使用中的FN数受通信资源分配的影响。此外,要开发用户感知Craccr方案,我们还设计了一种为绘制用户信誉的机制。然后将有限的通信资源分配问题与用户可信度的考虑相同,作为混合整数非线性编程问题(MINLP)。在通过L(P) - 箱约束和比例转换的改变问题之后,通过交替方向乘法器方法解决问题。仿真结果证明了所提出的方案实现的能效的提高,并在考虑通信资源分配时显示了FNS号码的变化。

著录项

  • 来源
    《Computer Communications》 |2021年第3期|48-58|共11页
  • 作者单位

    Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Peoples R China;

    Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China;

    Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China;

    Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Energy efficiency; Fog computing; Cloud computing; Resource allocation;

    机译:能量效率;雾计算;云计算;资源分配;

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