Study On Scheduling Method For Multi-channel Wireless Networks Based On Optimization Of Age Of Information

Age of Information is a metric that describes the timeliness of data delivery proposed for time-sensitive applications in recent years,which has been broadly used in wireless networks.Different from some classic metrics such as delay,Age of Information represents the interval between the generation time of the latest packet received by the destination node and the current time,which focuses on measuring the freshness of the most recently received packet from the perspective of receiver.At present,the existing researches on scheduling method based on Age of Information optimization mainly concentrate on the single-channel network scenarios,while for the multi-channel wireless network scenarios,there is still a lack of relevant research.The multi-channel mechanism is widely applied in many industrial wireless systems like WIA-PA network.Howerver,the inevitable perblems like the channel conflicts and link conflicts in multi-channel wireless network scenarios make the design of link scheduling strategy based on Age of Information more complicated.To address the above problems,this thesis proposes Max-Weight scheduling policy for multi-channel wireless network with link and channel conflict constraints,which minimizes the average Age of Information and effectively improves the freshness of network data by applying Lyapunov Drift scheduling method and Kuhn-Munkres matching algorithm.The main work of this thesis includes:1.This dissertation investigates the relevant technologies of multi-channel wireless network scheduling methods based on Age of Information optimization,including the conflict constraints of multi-channel,the definition of Age of Information and the problems in existing scheduling algorithms.2.For the multi-channel wireless networks with multiple sources and multiple destinations,a link scheduling method based on Age of Information optimization is proposed.In this method,the optimization problem of Age of Information is first formulated into a Lyapunov Optimization problem.To solve this problem,the iterative process of Age of Information is calculated by utilizing the probability of packet generation and the success rate of data transmission,and the weight function of Lyapunov Drift is derived.On the basis of these,the channel allocation problem under conflict constraints is constructed as the maximum weight matching problem with weighted dichotomous graphs,which is addressed by using the Kuhn-Munkres matching algorithm.The proposed method avoids the data collision in multi-channel transmission and the communication overhead caused by obtaining the source node data generation time.In additions,it effectively minimizes the average Age of Information of for the system and reduces the time complexity in the process of channel allocation.3.In simulations with appropriate network parameters,the proposed method is compared with the improved existing methods.The simulation results demonstrate that the proposed method can obtain lower average Age of Information compared with the similar methods under different channel quality and network scale,which implies that the timeliness of data delivery is improved.Therefore,the work of this thesis has a certain reference value for the Age of Information optimization in wireless networks.