Research On Service Stratum Interfaces Technology In Integrated Sensing Network

Recent years, Next Generation Network (NGN) has received much attention and deep investigation, but it’s still difficult to implement network integration, user management, service delivery and constitute a unified architecture and feasible interfaces between layers. Integrated Sensing Network (ISN), as a kind of network which supplies physical perception, data transfer and service processing capabilities, has been proposed to combine network architecture with practice and implement data and management information communication between layers through various interfaces, which providing reliable and feasible solutions for users. Service stratum interfaces are mainly discussed in this paper.Firstly, the position and functional structure of service stratum are introduced. Then service categories, priorities and service levels are defined, and service data features are also explained from three aspects of service transmission, convergence and processing, which analyzing data flows thoroughly. Secondly, the definition and functions of service stratum interfaces are discussed. Successively the concept and design of service middleware are proposed, based on which, the service priorities oriented mixed time-sharing users traffic model is presented to simulate traffic properties of visual and auditory services. Results show that visual services with higher priority reduces 0.19% of overall packet loss rate and 0.11MTu of average delay. But for the same class, packet loss and average delay of visual services with higher level are decreased by 0.04% and 0.02MTu respectively, and auditory services with higher level decreased by 0.14% and 0.10MTu respectively. Next the multiple services scheduling model is set up to understand the transmission situation under various services, which reaching good performances with delay time of less than 15ms, average queuing length of less than 50 packets and packet loss rate lower than 0.01%. Finally, service middleware on the local node is designed to implement data-frame parsing, buffering and storing into the database. Results show that ISN services scheduling scheme reduces 0.15s of average delay than RR scheme and overall performance jumps 7.56%, which meeting requirements upon real-time property.