Service Oriented Virtual Machine for Maximising Quality of Service in Wireless Networks

Abstract

A traditional big data network is a wireless multimedia network, as multiple video/audio streaming account for 70 percent of mobile traffic and the fifth generation wireless networks are projected to rise 500 times. However, it does raise various new and transparent challenges for multimedia big data communication over 5G wireless systems because multimedia big data services provide timely, throughput broadcasts through time-sensitive communication networks with restricted wireless resources. In order to address the above issues, we suggest in this paper information-centric virtualization architectures for a statistical latency consistency of content delivery across 5G wireless large media platforms for technology. In particular, three successful nominee strategies to promise the mathematical time limit for interactive large-data communications are implemented in our proposed scheme: information-centered network which extracts an optimum in-network storage location for multimedia big data; a virtualization of the network feature which transforms PHY architecture into many virtualized channels. In our architectures we build the 3 primary computer-generated machine collection besides power distribution plans to collectively simplify the application of NFV and SDN techniques in the ICN architecture: to improve performance for single users, to integrate effective combining capability with equity allocation for all users besides under non-cooperative betting Via models and computational assesses, we prove that our suggested designs and applications greatly perform better other existing systems to enable QoS provisioning with statistical delays over 5G immersive Large Data Wireless communication.