Self-Adaptive Resource-Allocation Scheme Combining Traffic Prediction With User Satisfaction in Multi-Wavelength VPON

Abstract

In this paper, a self-adaptive resource-allocation scheme combining traffic prediction with user satisfaction is firstly established in multi-wavelength VPON. Among VPONs, by proposing a (wavelength utility)-based dynamic wavelength allocation algorithm, the optimal allocation of wavelengths can be achieved. In a VPON: under condition that the total requested bandwidth is larger than the total bandwidth, by introducing a bandwidth constraint factor <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ϵ</i> , the maximum amount of bandwidth granted for high-priority service can be limited, and the “starvation” problem of low-priority service can be prevented. By solving the user satisfaction model, not only the optimal allocation of low-priority service can be obtained, but also the comprehensive user satisfaction is maximized. Under condition that the total requested bandwidth is smaller than the total bandwidth, by combining an ANN prediction model with a user satisfaction model, a bandwidth allocation model based on traffic prediction and user satisfaction is created. By this model, not only the resource utilization is improved but also the transmission delay is reduced. At the same time, user satisfaction is maximized. By adjudicating on the set judgment condition, the self-adaptive function of control system for the above two conditions is implemented. By simulation, the effectiveness of the proposed scheme is demonstrated.