An optimal content indexing approach for named data networking in software‐defined IoT system

Abstract

The evolution of the Internet of Things (IoT) has increased the number of connected devices in the network. This has shifted the focus from IP‐based network architecture towards content‐centric networking (CCN). CCN eliminates the need for address‐content binding in the conventional IP‐based networks and allows the content to be accessed based on the name instead of the physical location. Named data networking (NDN) is a promising technique that can fulfil the increasing demand for connected devices through the CCN approach. NDN distributes the content on the network and focusses on the security of the content rather than the communication channel. However, the increase in traffic due to the escalation in the number of connected devices can lead to congestion in the network. The content distribution approach on the nodes is generalised and suitable for small networks. In the case of larger networks, an optimal approach is required to decide the optimal location to store the required content. However, a linear search approach is used to search (or lookup) the content in the assigned cache of the NDN node. In this work, the authors have combined the software‐defined networking (SDN) with the NDN approach to overcome the above‐highlighted challenge. Thus, the authors have designed an optimal content storage and indexing approach based on NDN‐SDN coalesce in the IoT ecosystem. The proposed approach includes different phases, (a) a hashing‐based content searching approach is formulated to reduce the look‐up time of the content, (b) a red‐black tree‐based content storage approach is introduced for optimal utilisation of the assigned cache memory of the different NDN nodes, and (c) SDN controller facilitates automated network management and helps to administer the network requirements centrally and locate the content accordingly. The proposed approach was validated through the simulation experiments concerning network delay, packet rate, throughput, and cache hit ratio. The results obtained show the effectiveness of the proposed approach.

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices

“…In recent work ( Dudeja et al, 2022 ; Liu et al, 2022 ), an SDN-based secure content caching and forwarding approach was introduced. Routers maintain an index table in their cache memory with unique signatures for data.…”

“…However, the rigidity of fixed popularity threshold values may lead to an escalation in inter-exchange traffic ( Suksomboon et al, 2013 ; Bernardini, Silverston & Festor, 2013 ; Nguyen et al, 2019 ). Subsequently, specific popularity-aware caching approaches incorporate popularity and freshness metrics as decision factors ( Ong et al, 2014 ; Dudeja et al, 2022 ; Liu et al, 2022 ; Gupta et al, 2023 ). Unfortunately, they achieve suboptimal performance in maximizing cache hit rates because their caching decisions are primarily based on request rates, regardless of the network’s topological characteristics.…”