PSO-ANFIS tuned real-time VVoIP in Cloud with access control security

This paper introduces Cloud-Mobile Computing system to realize a real-time video/voice over IP (VVoIP) applications, called Cloud-VVoIP. In addition, access control designs authentication authorization, and accounting mechanism using biometrics technology (including face recognition and fingerprint identification) that is applied to secure legal access from the outsider, giving a safer way to login into Cloud-VVoIP. After that adaptive network-based fuzzy inference system (ANFIS) together with particle swarm optimization (PSO) has been employed to tune seamless handoff properly and analyze network traffic flow over time. Finally the performance of Cloud-VVoIP is measured and discussed. Cloud-based VVoIP outperforms the traditional peer-to-peer type of VVoIP due to three benefits. According to the analysis of Cloud-VVoIP, power consumption will be estimated in web-based browsing and Android APP. In addition, through stress test to analyze the performance of Cloud-VVoIP, we found the resources allocation about CPU, memory, bandwidth and disk.