{"title":"Optimizing data retrieval latency in IoT through information centric in-network caching","authors":"Muhammad Ali Naeem , Meng Yahui , Ahmad Abrar","doi":"10.1016/j.aej.2024.10.067","DOIUrl":null,"url":null,"abstract":"<div><div>The integration of Information Centric Networking (ICN) with the Internet of Things (IoT) will meet the expectations of end users by providing an admirable network system. ICN enhances the IoT by utilizing in-network caching regarding data dissemination with the help of various paths labeled by the name of the path by which the data is returned. Caching is a significant technique for improving content accessibility, reducing hops while transferring data, and finally shortening data access time, which in turn improves IoT networks. This study develops a novel caching strategy that caches content in suitable locations at highly requested nodes, thereby improving the information caching efficiency of ICN-based IoT systems. When comparing the proposed caching scheme with other caching methods, it pay attention to the data retrieval latency, cache hit ratio, and the average number of hops. These results consistently show that the proposed strategy enhances cache performance by a high margin. The future context of the utilization of the specified caching strategy will lie in the advancements of fog, edge, and ad hoc networks concerning the concept of IoT and new trends like 5 G and 6 G.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"111 ","pages":"Pages 468-481"},"PeriodicalIF":6.2000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016824012213","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The integration of Information Centric Networking (ICN) with the Internet of Things (IoT) will meet the expectations of end users by providing an admirable network system. ICN enhances the IoT by utilizing in-network caching regarding data dissemination with the help of various paths labeled by the name of the path by which the data is returned. Caching is a significant technique for improving content accessibility, reducing hops while transferring data, and finally shortening data access time, which in turn improves IoT networks. This study develops a novel caching strategy that caches content in suitable locations at highly requested nodes, thereby improving the information caching efficiency of ICN-based IoT systems. When comparing the proposed caching scheme with other caching methods, it pay attention to the data retrieval latency, cache hit ratio, and the average number of hops. These results consistently show that the proposed strategy enhances cache performance by a high margin. The future context of the utilization of the specified caching strategy will lie in the advancements of fog, edge, and ad hoc networks concerning the concept of IoT and new trends like 5 G and 6 G.
以信息为中心的网络(ICN)与物联网(IoT)的整合将提供一个令人钦佩的网络系统,从而满足终端用户的期望。ICN 借助以数据返回路径名称为标记的各种路径,在数据传播方面利用网内缓存来增强物联网。缓存是提高内容可访问性、减少数据传输跳数并最终缩短数据访问时间的重要技术,从而改善物联网网络。本研究开发了一种新颖的缓存策略,将内容缓存在高请求节点的合适位置,从而提高了基于 ICN 的物联网系统的信息缓存效率。在将所提出的缓存方案与其他缓存方法进行比较时,本研究关注了数据检索延迟、缓存命中率和平均跳数。这些结果一致表明,所提出的策略能大幅提高缓存性能。未来,特定缓存策略的应用范围将包括与物联网概念有关的雾网络、边缘网络和特设网络的发展,以及 5 G 和 6 G 等新趋势。
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering