| Title | Self-Healing Solutions for Wi-Fi Networks to Provide Seamless Handover |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Hao, Lina, Ng, Bryan |
| Conference Name | 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) |
| Date Published | apr |
| Keywords | Cellular networks, cellular radio, composability, fault diagnosis, fault tolerant computing, Handover, IEEE 802.11 Standard, learning (artificial intelligence), machine learning algorithms, ML algorithms, mobility management (mobile radio), Packet loss, pubcrawl, QoS, quality of service, resilience, Resiliency, seamless handover, self-healing networks, self-healing solutions, self-organizing network paradigm, SON developments, unexpected network faults, uniform seamless network quality of service, Wi-Fi Networks, wireless channel, wireless channels, wireless LAN |
| Abstract | The dynamic nature of the wireless channel poses a challenge to services requiring seamless and uniform network quality of service (QoS). Self-healing, a promising approach under the self-organizing networks (SON) paradigm, and has been shown to deal with unexpected network faults in cellular networks. In this paper, we use simple machine learning (ML) algorithms inspired by SON developments in cellular networks. Evaluation results show that the proposed approach identifies the faulty APs. Our proposed approach improves throughput by 63.6% and reduces packet loss rate by 16.6% compared with standard 802.11. |
| Citation Key | hao_self-healing_2019 |
Self-Healing Solutions for Wi-Fi Networks to Provide Seamless Handover