Content Placement Aware Cache Decision: A Caching Policy Based on the Content Replacement Ratio for Information-Centric Network

Sena, Paulo; Carvalho, Igor; Abelém, Antônio

doi:10.1109/cybermatics_2018.2018.00317

Cited by 1 publication

(1 citation statement)

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“…The authors then present a Deep Reinforcement Learning (DRL)-based green resource allocation scheme to allocate cache capacity with a suitable transmission rate accordingly to enhance the QoE level dynamically. Also, it is shown that with a suitable replacement ratio and ratio cache for the dynamic caching scheme, the network performance in ICN can be improved [44]. In [45], a Central Control Caching (CCC) Scheme is proposed for ICN-based IoT by maintaining a table containing information of different contents on different autonomous systems (AS) for caching decision of inter-AS content exchanges.…”

Section: Green Networking In Icnmentioning

confidence: 99%

A Cross-Layer Green Information-Centric Networking Design Toward the Energy Internet

Nguyễn

Ullah

Kim

et al. 2022

IEEE Trans. Netw. Sci. Eng.

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To address the energy-efficiency issue in Information-Centric Networking (ICN), this article proposes a novel Green ICN design, which adapts the power consumption of network nodes to the optimized utilization level proportionally. By learning over the consumers' interactive data traffic pattern/behavior, we introduce a new concept of cross-layer power adaption conducted through dynamically adjusting link rate corresponding to content popularity to reduce the wasteful power consumption of Content Routers (CRs). We also develop a controlling policy for each content provider to map its status to the most suitable operating mode to diminish power consumption. Moreover, we propose a smart Selective Caching Scheme (SCS) so that the caching portion in a CR's cache memory is adjusted according to content popularity and available spaces of two customized content cache spaces, namely hot and cold caching queues, for storing popular and unpopular content objects. This scheme can further decrease the power from caching since it is diminished when the traffic load is reduced via the proposed CRs' adaptive mechanism. The evaluation results with practical insights in several distinct scenarios show that the proposal can provide considerably higher energy efficiency and network performance at the same time, typically achieving at least 20% power-saving with a higher hop reduction ratio, compared to existing Internet designs with relevant state-of-the-art caching strategies.

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Section: Green Networking In Icnmentioning

confidence: 99%