An accurate retransmission timeout estimator for content-centric networking based on the Jacobson algorithm

作     者：Mortaza Nikzad Kamal Jamshidi Ali Bohlooli Faiz Mohammad Faqiry Mortaza Nikzad;Kamal Jamshidi;Ali Bohlooli;Faiz Mohammad Faqiry

作者机构：Faculty of Computer ScienceKabul Polytechnic UniversityKabulAfghanistan Faculty of Computer EngineeringUniversity of IsfahanIsfahanIran 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2022年第8卷第6期

页      面：1085-1093页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Content-centric networking Retransnissi on timeout Popularity distribution gain Jacobson RTO estimator 

摘      要：Accurately estimating of Retransmission TimeOut (RTO) in Content-Centric Networking (CCN) is crucial for efficient rate control in end nodes and effective interface ranking in intermediate routers. Toward this end, the Jacobson algorithm, which is an Exponentially Weighted Moving Average (EWMA) on the Round Trip Time (RTT) of previous packets, is a promising scheme. Assigning the lower bound to RTO, determining how an EWMA rapidly adapts to changes, and setting the multiplier of variance RTT have the most impact on the accuracy of this estimator for which several evaluations have been performed to set them in Transmission Control Protocol/Internet Protocol (TCP/IP) networks. However, the performance of this estimator in CCN has not been explored yet, despite CCN having a significant architectural difference with TCP/IP networks. In this study, two new metrics for assessing the performance of RTO estimators in CCN are defined and the performance of the Jacobson algorithm in CCN is evaluated. This evaluation is performed by varying the minimum RTO, EWMA parameters, and multiplier of variance RTT against different content popularity distribution gains. The obtained results are used to reconsider the Jacobson algorithm for accurately estimating RTO in CCN. Comparing the performance of the reconsidered Jacobson estimator with the existing solutions shows that it can estimate RTO simply and more accurately without any additional information or computation overhead.