Qaiser Firdous, Hussain Mudassar, Ahad Abdul, Pires Ivan Miguel
Department of Computer Science, University of Sialkot, Sialkot, Pakistan.
Knowledge Unit of Systems and Technology, University of Management and Technology, Sialkot, Pakistan.
PeerJ Comput Sci. 2024 Feb 8;10:e1854. doi: 10.7717/peerj-cs.1854. eCollection 2024.
Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including 'request rates' and 'past popularity'. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as 'distance cost,' 'delivery time,' and the specific 'status of the requested content'. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures.
命名数据网络（NDN）已成为一种在边缘基础设施中用于内容交付的很有前景的网络架构，主要得益于其基于名称的路由和集成的网络内缓存。尽管有这些优点，但缓存设备的分散决策过程往往导致性能欠佳。本文引入了一种范式转变，即通过实现软件定义网络（SDN）控制器来优化NDN节点中热门内容的放置。优化过程考虑了关键的网络因素，包括网络拥塞、安全性、拓扑修改和流规则更改，这些对于制定内容缓存策略至关重要。本文提出了一种新颖的内容缓存框架，即流行可编程NDN节点中的流行度感知缓存（PaCPn）。PaCPn采用由SDN控制器驱动的多变量向量自回归（VAR）模型，根据包括“请求率”和“过去流行度”在内的时间序列数据定期更新内容流行度。它还引入了一种控制器驱动的启发式算法，该算法考虑诸如“距离成本”、“交付时间”和请求内容的特定“状态”等因素来评估缓存点与消费者的接近程度。PaCPn利用定制的DATA命名数据包来确保源存储具有有效剩余新鲜期的内容，同时防止中间节点缓存它。实验结果表明，与现有方案相比，所提出的技术PaCPn取得了显著改进。具体而言，该技术在包括缓存大小、齐普夫参数和边缘基础设施内的交换流量等各种指标上，将缓存命中率提高了20%。此外，考虑到缓存容量、消费者数量和网络吞吐量等指标，它将内容检索延迟降低了28%。这项研究推动了NDN内容缓存的发展，并为边缘基础设施提供了潜在的优化方案。
