Edge　intelligent　computing　devices　are　often　deployed　in　some　extreme　environments,　where　the　transmission　network　bandwidth　is　low　or　the　network　environment　changes　greatly.　Therefore,　the　traditional　queue　scheduling　algorithms　cannot　guarantee　the　QoS　of　edge　intelligent　computing.　WF2Q+　allocates　bandwidth　according　to　a　fixed　weight,　which　causes　real-time　data　flow　delay　to　increase　when　the　network　is　unstable.　The　dynamic　perception　scheduling　strategy　proposed　in　this　paper　is　to　dynamically　change　the　weight　of　WF2Q+　by　dynamically　sensing　the　backlog　length　of　the　queue.　At　the　same　time,　combined　with　the　queue　scheduling　algorithm　of　PQ,　this　algorithm　can　prioritize　the　transmission　of　real-time　data　with　certain　fairness.　In　addition,　the　token　bucket　algorithm　is　used　to　limit　the　sending　rate　of　the　device　and　prevent　network　congestion　caused　by　burst　data　injection　into　the　network.　After　experimental　simulation,　the　improved　algorithm　can　achieve　good　results　on　the　delay　index.　©　2019　Published　under　licence　by　IOP　Publishing　Ltd.