مقاله انگلیسی رایگان در مورد زنجیره های عملکردی خدمات در شبکه ابر توزیع شده – IEEE 2019

 

مشخصات مقاله
ترجمه عنوان مقاله زنجیره سازی آگاه از منابع و مقیاس بندی ظرفیت سازگار برای زنجیره های عملکردی خدمات در شبکه ابر توزیع شده
عنوان انگلیسی مقاله Resource Aware Chaining and Adaptive Capacity Scaling for Service Function Chains in Distributed Cloud Network
انتشار مقاله سال 2019
تعداد صفحات مقاله انگلیسی 17 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.641 در سال 2018
شاخص H_index 56 در سال 2019
شاخص SJR 0.609 در سال 2018
شناسه ISSN 2169-3536
شاخص Quartile (چارک) Q2 در سال 2018
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های مرتبط مهندسی الگوریتم و محاسبات، رایانش ابری، شبکه های کامپیوتری
نوع ارائه مقاله
ژورنال
مجله / کنفرانس دسترسی – IEEE Access
دانشگاه  Institute of Command and Control Engineering, Army Engineering University, Nanjing 210007, China
کلمات کلیدی مجازی سازی عملکرد شبکه، زنجیره های عملکردی خدمات، شبکه ابر توزیع شده، بهینه سازی منابع
کلمات کلیدی انگلیسی  Network function virtualization, service function chain, distributed cloud network, resource optimization
شناسه دیجیتال – doi
https://doi.org/10.1109/ACCESS.2019.2950424
کد محصول E13964
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
I. Introduction
II. Related Work
III. System Model
IV. Problem Formulation
V. Proposed Algorithm
Authors
Figures
References

 

بخشی از متن مقاله:
Abstract

With the development of network technology such as software-defined network (SDN) and network function virtualization (NFV), Internet service providers (ISPs) are increasingly placing the virtual network function(VNF) instances at the network edge to provide network service. However, there are some issues to be tackled in the distributed SDN/NFV enabled cloud. Firstly, VNF instances require to be chained in predefined order to provide network services. It is a challenge to optimally select and chain VNF instances from the multi-instances. Moreover, due to the capacity limitation of the distributed edge nodes. The capacity of the Virtual Machines (VMs) that host VNFs should be proactively adjusted to cope with traffic demands. Since most existing works ignore the vertical capacity scaling problem in routing commodities with Service Function Chain (SFC) requests. In this paper, a fine-grained scheduling scheme at VM-level is proposed. Firstly, we formulate the SFC chaining problem as an Integer Linear Programming (ILP) model aiming to embed SFC requests with minimum estimated latency cost. Furthermore, we formulate the adaptive VNF resource allocation (VNF-AR) problem as a convex optimization. The theoretical optimal capacity for each VM can be derived from the Karush-Kuhn Tucker (KKT) conditions. At last, a novel joint optimization approach of VNF chaining and adaptive scaling (VNF-CAS) is proposed to efficiently embed the SFC requests. Performance evaluation shows that VNF-CAS can achieve better performance in SFC requests acceptance rate, average effective throughput, average load utilization and VM load balancing when it is compared with other algorithms in existing works.

Introduction

In traditional, the Internet service providers (ISPs) use the dedicated hardware equipment to offer different network functions such as Firewalls, Proxies, Network Address Translators (NATs) and Intrusion Detection Systems (IDSs), this can result in high cost and inflexible management of ISP’s network. To reduce the Operating Expenditures (OPEX) and Capacity Expenditures (CAPEX), network function virtualization (NFV) [1] was proposed to migrate network functions from the hardware-based equipment to softwaredefined instances and allow scalable and flexible deployment of network functions. In NFV, different network functions are executed in virtual machines (VMs) or containers on standardized servers. In general, the NFV architecture [2] is composed of three main components, Virtual Network Functions (VNF), Network Function Virtualization Infrastructure (NFVI), management and orchestration architectural framework (NFV MANO). The VNFs are controlled and managed by MANO according to software-defined networking (SDN) paradigm [3]. Typically, NFV is used in the data center network, which brings great advantages in flexibility and cost-efficiency. However, the centralized orchestration of a large number of VNFs becomes a problem. To reduce the complexity of orchestration, the ISPs can place a few VNFs in distributed Micro-Data Centers (MDCs) [4] with the network edge computing technology [5]. These distributed MDCs can be deployed in buildings or neighbors near users to achieve better QoS and lower latency.

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