Queues, in the context of SDN (Software-Defined Networking) refer to the mechanisms used to manage and prioritize network traffic within SDN-enabled devices, such as switches and routers. Queues play a crucial role in controlling the flow of data through the network, ensuring efficient utilization of resources, and meeting quality of service (QoS) requirements.

In SDN, queues are buffers or storage spaces within network devices where incoming data packets are temporarily held before they are transmitted. These queues allow for the orderly processing of packets and help in managing network congestion.


5GLoR: 5G LAN Orchestration for Enterprise IoT Applications

5G-LAN is an enterprise local area network (LAN) that leverages 5G technology for wireless connectivity instead of WiFi. 5G technology is unique: it uses network slicing to distinguish customers in the same traffic class using new QoS technologies in the RF domain. This unique ability is not supported by most enterprise LANs, which rely primarily on DiffServ-like technologies that distinguish among traffic classes rather than customers. We first show that this mismatch in QoS between the 5G network and the LAN affects the accuracy of insights from the LAN-resident analytics applications. We systematically analyze the root causes of the QoS mismatch and propose a first-of-a-kind 5G-LAN orchestrator (5GLoR). 5GLoR is a middleware that applications can use to preserve the QoS of their 5G data streams through the enterprise LAN. In most cases, the loss of QoS is not due to the oversubscription of LAN switches but primarily due to the inefficient assignment of 5G data to queues at ingress and egress ports. 5GLoR periodically analyzes the status of these queues, provides suitable DSCP identifiers to the application, and installs relevant switch re-write rules (to change DSCP identifiers between switches) to continuously preserve the QoS of the 5G data through the LAN. 5GLoR improves the RTP frame level delay and inter-frame delay by 212% and 122%, respectively, for the WebRTC application. Additionally, with 5GLoR, the accuracy of two example applications (face detection and recognition) improved by 33%, while the latency was reduced by about 25%. Our experiments show that the performance (accuracy and latency) of applications on a 5G-LAN performs well with the proposed 5GLoR compared to the same applications on MEC. This is significant because 5G-LAN offers an order of magnitude more computing, networking, and storage resources to the applications than the resource-constrained MEC, and mature enterprise technologies can be used to deploy, manage, and update IoT applications.