Advances, Systems and Applications
Table 4 Characteristics of architecture-based load balancing techniques
From: An overview of QoS-aware load balancing techniques in SDN-based IoT networks
Application | Objectives | Architecture | Balance entity | LB method | Network type | Year | Ref |
|---|---|---|---|---|---|---|---|
Vehicles | Delay | Centralized | Cloud, Fog servers | Architecture/ Allocation | SDN-IoV | 2016 | [33] |
Real-time face recognition | Delay | Centralized | Cloud, Fog servers | Architecture/ Allocation | SDC-FN | 2016 | [86] |
Large scale | Response time, resource utilization | Distributed | Controllers | Hierarchical architecture | SDN-IoT | 2019 | [20] |
Large scale | Bandwidth, load-balancing | Distributed | Link/Server | Architecture | SDN- Fog/Cloud | 2020 | [11] |
VoIP, Video | Scalability, delay | Distributed | Controllers | Hierarchical Controllers/ Allocation | SDN- Edge/Cloud | 2020 | [45] |
Wi-Fi | throughput, packet loss ratio | Centralized | Access points | Architecture | SDN -Wi-Fi | 2020 | [44] |
Image processing | Waiting, turnaround, processing times | Distributed | Device clusters | Hierarchical architecture of the control layer | SDN-IoT | 2021 | [22] |
Critical scenarios | Response time, packet loss ratio, processing time | Distributed | Gateway | FoTa pattern | SDN- FoT | 2021 | [17] |
Smart city | Response time, throughput | Distributed | Controllers | Architecture | SDN-IoT | 2021 | [36] |
Industry | Throughput, packet loss ratio, response time | Distributed | Controllers | Architecture | SDN/NFV -IoT | 2022 | [3] |
- | Response time, energy consumption, delay | Centralized | Fog nodes | Architecture | SDN- Fog | 2022 | [87] |
Dense networks | Throughput, delay, packet loss rate | Centralized | Base stations | Architecture | SDN- IOMT | 2022 | [88] |
Industry | Throughput, response time, delay, resource utilization | Distributed | Cloud servers | Architecture | SDN-IIoT | 2023 | [15] |