An Energy Reward-Based Caching Mechanism for Information-Centric Internet of Things

Abstract

Existing information-centric networking (ICN) designs for Internet of Things (IoT) mostly make caching decisions based on probability or content popularity. From the energy-efficient perspective, those strategies may not always be energy efficient in resource-constrained IoT because without considering the energy reward of caching decisions, inappropriate routers and content objects may be selected for caching, which may lead to negative energy rewards. In this paper, we analyze the energy consumption of content caching and content retrieval in resource-constrained IoT and calculate caching energy reward as a key metric to measure the energy efficiency of a caching decision. We then propose an efficient cache placement and cache replacement mechanism based on the caching energy reward to improve the energy efficiency of caching decisions. Through analysis and experimental results, we show that the proposed mechanism achieves a significant improvement in terms of energy efficiency, stretch ratio, and cache hit ratio compared to state-of-the-art caching schemes.

A survey of classification cache replacement techniques in the contentcentric networking domain

“…Although this technique leverages the caching resources of neighboring nodes, coordinating the migration of content requires communication between them, which can lead to increased communication overhead. Dinh and Kim (2022) The ERC mechanism operates on the principle that a content object is only cached if the residual energy of a node is equal to or exceeds a specified threshold. Additionally, a content object will replace an existing cached object if the energy benefit of doing so is positive; otherwise, the content may be cached on a different node along the forwarding path.…”

An efficient algorithm for data transmission certainty in IIoT sensing network: A priority-based approach

“…If the user requests the content to be cached, the delay is the time for the content to be transmitted from the edge node to the user, that is, the delay is the cache read time d . If the content requested by the user is not in the cache, the edge cache device needs to request the factory private cloud to cache the content [ 28 , 70 , 71 ], and the data transmission will be limited by the capacity of the backhaul link. γ represents the transmission factor of the link, that is, the delay caused by network instability or congestion.…”

“…Fig 8 compared the hit ratio and latency delay of the proposed and references [ 28 , 70 , 71 ] algorithms under different cache resource capacity. As can be seen from Fig 8(a) , the hit ratio of the proposed algorithm under dynamic contents is superior than that of existing algorithms which further validates its effectiveness.…”