Resource-based mobility management for video users in 5G using catalytic computing

Abstract

The upcoming 5G era emphasizes on a dramatic increase in the transmission rate of smartphone traffic. With more users operating at high rates, the type of data shared over the network is going to be complex and a majority of it will include video traffic. Such complex structure of traffic and heavy load over the components of the network are difficult to control. Further, the mobility of users adds up to this issue and makes it difficult to manage and operate the network without any breakdown. Thus, it important to control traffic as well as manage the mobility of users to provide efficient communication, which can support video traffic at high delivery rates. This paper proposes a novel resource-based mobility management approach for 5G networks comprising video users. A novel resource sharing paradigm, termed as "Catalytic Computing", provides efficient management of user mobility as well as network resources. The proposed approach relies on Homogeneous discrete Markov model for user mobility patterns and a novel n-step algorithm for congestion prediction and selection of optimal routes between the serving terminals. An activation energy based handover mechanism is also presented in this paper, which reduces the handover latency in comparison with the existing solutions. The evaluation presented in the paper suggests that the proposed approach provides a minimum of 5.9 ms, maximum of 9.1 ms and an average of 6.5 ms latency during handoffs.