Clustered and Distributed Caching Methods for F-RAN-Based mmWave Communications

Abstract

Fog-radio access networks (F-RANs) alleviate fronthaul delays for cellular networks as compared to their cloud counterparts. This allows them to be suitable solutions for networks that demand low propagation delays. Namely, they are suitable for millimeter wave (mmWave) operations that suffer from short propagation distances and possess a poor scattering environment (low channel ranks). The F-RAN here is comprised of fog nodes that are collocated with radio remote heads (RRHs) to provide local processing capabilities for mobile station (MS) terminals. These terminals demand various network functions (NFs) that correspond to different service requests. Now, provisioning these NFs on the fog nodes also yields service delays due to the requirement for service migration from the cloud, i.e., offloading to the fog nodes. One solution to reduce this service delay is to provide cached copies of popular NFs in advance. Hence, it is critical to study function popularity and allow for content caching at the F-RAN. This is further a necessity given the limited resources at the fog nodes, thus requiring efficient resource management to enhance network capacity at reduced power and cost penalty. This paper proposes novel solutions that allocate popular NFs on the fog nodes to accelerate services for the terminals, namely, the clustered and distributed caching methods. The two methods are analyzed and compared against the baseline uncached provisioning schemes in terms of service delay, energy consumption, and cost.

Caching of popular content at F‐RAN for mmWave new radio

“…It is used as the structure for the novel proposed caching method in Section 5. Along this, consider the details from Aldalbahi et al 20 Following the network architecture in Section 3, consider that each of the primary and secondary fog nodes is collocated with a single RRH. This allows the MS users to communicate directly with the RRH via the mmWave links, after which the RRH processes their requests using the fog nodes, which act as the BBU that stores the NFs.…”

“…F I G U R E 5 Energy consumption in network for numbers of incoming requests from MS users where z x ð Þ is the power consumption for switch x and X represents the total number of switches in the network. 20 Figure 5 depicts the energy consumption for the four schemes. As discussed in the delay and cost metrics, the detrimental effect of network saturation in online NF mapping results in high power and energy consumption levels that reach 250 J at 200 requests.…”

“…The network model in this work adopts the same model that is proposed in Aldalbahi et al, 20 as described next. It is used as the structure for the novel proposed caching method in Section 5.…”

“…It is used as the structure for the novel proposed caching method in Section 5. Along this, consider the details from Aldalbahi et al 20 …”

“…The variable src represents the gateway primary node that first receives the request r from MS user m ; the destination of the request r is specified by the variable dst ; is the set of NFs, = { }, where is a single function of type t T , where T is the number of function types. Further, the variable represents the processing and memory resources, as expressed in Equation () from Aldalbahi et al 20 Finally, the variables and account for the requested bandwidth and the delay bound, respectively. …”