Research On Approach Of QoS Constrained Routing And Channel Allocation For Edge Computing

With the vigorous development of 5G technology,how to integrate the Mobile Internet and Internet of things business with the latest communication technology,to avoid the mobile carrier network being pipelined,so as to maximize the value of mobile network bandwidth is gradually emerging.In response to the situation,the European telecommunication standards association proposed the mobile edge computing technology.Mobile edge computing technology lightens the network burden by shifting the computing load from the core cloud data center to the mobile edge near the client.It pulls traditional cloud computing closer to the edge of the network on the user side and speeds up access to content,services and applications,thus achieving rapid response on the edge.This thesis focuses on the wireless sensor information transmission and multicast communication in the wireless mesh network under the background of smart farm by using edge computing technology,and studies the QoS(Quality of Service) routing protocol and channel interference problems respectively.First consider the problem of routing protocol in wireless sensor network.We studied the current existing multipath routing protocol,it can meet the end-to-end delay between nodes and the reliability of the service requirements,but more energy.Therefore,to study the more adapt to era development trend of QoS routing protocol.By considering the three QoS constrains of end-to-end delay,reliability and energy consumption,this thesis innovatively uses the related techniques in edge computing and machine learning to construct a sensor network as a multi-constrained optimal path model.At the same time,introducing the energy-aware node wake-up mechanism and the reward and punishment mechanism of learning automata,this thesis proposes a oriented edge computing nodes energy optimized QoS constrained routing algorithm.The mechanism of this algorithm is to optimize the network energy consumption and extend the network life cycle by creatively combining the edge computing technology to preprocess the original data of the node,accelerating the transmission and processing of effective data,accelerating the algorithm convergence by using the way of automata interacting with the environment and controlling the dormant activation state of the node.Through experimental testing and comparison,this thesis gave the MQEN(Multi-QoS constrained routing algorithm for Edge computing and Node energy optimization)algorithm,which can meet the requirements of end-to-end delay and reliability service with multi-QoS constraints when significantly reducing network energy consumption.Secondly,the problem of channel interference caused by multicast in wireless mesh networks is considered.Wireless mesh network is a kind of wireless network technology which can carry out multi-hop information transmission.It has been regarded as one of the key technologies to configure wireless machine.In this thesis,we study the problems of channel interference and time slot multi-user collisions caused by radio during WMNs(Wireless Mesh Networks) information transmission.Through innovative use of edge computing technology to construct a node data cache model and step-by-step calculation of node channel separation,a multi-strategy channel allocation algorithm for edge computing is proposed.The mechanism of this algorithm is to use edge computing technology to pre-store the data in the nodes in the multicast tree and calculate the channel separation between the nodes,and then select the transmission channel number of the node with the least interference to avoid mutual interference between node information transmissions.Through experimental tests and comparisons,the MSCA(Multi-Strategy Channel Allocation algorithm for edge computing)algorithm presented in this thesis can minimize channel interference and overall network energy consumption while satisfying throughput and end-to-end delay.