Exploring analytical models to maintain quality-of-service for resource management using a proactive approach in highly mobile environments

Abstract

The next generation networks are expected to provide a wide variety of high data rate services and seamless connectivity in all environments including highly mobile networks. Today, there is a rapid increase in high mobile systems and applications. This rapid increase causes the requirement of systems to be reliable to share their resources without delay in order to ensure a better quality of service (QoS) for mobile users. In order to provide better QoS and ubiquitous communication in highly mobile environments, the proactive handover techniques are recommended to be used rather than the traditional reactive approaches. This paper presents a proactive approach for resource allocation in highly mobile networks and analysed the user contention for common resources such as radio channels in wireless networks. The proposed approach uses Markov chains to model the contention and results are obtained showing enhanced system performance in terms of mean queue length, the mean response time, throughput and blocking probability. Based on these results an operational space has been explored and are shown to be useful for emerging future networks such as 5G by allowing base stations to calculate the probability of contention based on the demand for network resources. The model has been validated using simulation and the results show that the proactive approach can be evaluated efficiently and accurately using the proposed analytical model. In addition, this study indicates that the proactive model enhances handover and resource allocation for highly mobile networks.