Bus Arrival Time Prediction Based on Mixed Model

How to predict the bus arrival time accurately is a crucial problem to be solved in Internet of Vehicle. Existed methods cannot solve the problem effectively for ignoring the traffic delay jitter. In this paper,a three-stage mixed model is proposed for bus arrival time prediction. The first stage is pattern training. In this stage,the traffic delay jitter patterns(TDJP)are mined by K nearest neighbor and K-means in the historical traffic time data. The second stage is the single-step prediction,which is based on real-time adjusted Kalman filter with a modification of historical TDJP. In the third stage,as the influence of historical law is increasing in long distance prediction,we combine the single-step prediction dynamically with Markov historical transfer model to conduct the multi-step prediction. The experimental results show that the proposed single-step prediction model performs better in accuracy and efficiency than short-term traffic flow prediction and dynamic Kalman filter. The multi-step prediction provides a higher level veracity and reliability in travel time forecasting than short-term traffic flow and historical traffic pattern prediction models.

A dynamic network Qo S control mechanism based on traffic prediction

A dynamic network Qo S control mechanism was proposed based on traffic prediction. It first predicts network traffic flow and then dynamically distributes network resources, which makes full use of network flow self-similarity and chaos. So it can meet changing network needs very well. The simulation results show that the dynamic Qo S control mechanism based on prediction has better network performance than that based on measurement.

Joint Optimization of Communications and Computing Resources Allocation for Deterministic Transmission in Wireless Edge Networks

Motivated by 5th generation wireless systems(5G),a large number of emerging applications appear,which put forward higher requirements for the task’s transmission determinacy,which refers to the delay and jitter.To satisfy the deterministic requirement,mobile edge computing(MEC)is envisioned as a promising technique for reducing the end-to-end delay significantly.In this paper,we consider delaysensitive task and jitter-sensitive task,and then formulate the joint communications and computing optimization problem under the latency,the total bandwidth,the total transmission power of base station(BS)and the computing ability of the MEC server constraints to minimize the delay and jitter in a multiuser MEC system.Because of the problems are nonconvex,we decouple them into some subproblems and propose the corresponding algorithms to obtain a suboptimal solution.Finally,numerical results show that the proposed algorithms have a significant performance gain over the traditional solution in terms of the delay and the jitter.