In　today＇s　era　of　Internet　of　Things　(IoT),　efficient　and　real-time　processing　of　massive　data　generated　by　IoT　device　has　become　the　primary　issue　for　traditional　cloud　computing　network　architectures.　As　a　supplement　of　cloud　computing,　edge　computing　enhances　the　real-time　performance　of　service　completion　by　offloading　services　to　edge　servers　closer　to　the　terminal　device　for　execution,　while　reducing　power　consumption　and　computing　load　in　the　cloud.　In　this　article,　we　propose　the　following　solutions　to　resolve　the　different　requests　of　the　IoT　device:　in　an　＂edge-cloud＂　heterogeneous　network　environment,　create　a　mapping　scheme　between　application　modules　and　basic　resource　equipment,　considering　the　two　factors　of　tolerant　task　latency　and　system　power　consumption.　In　the　application　step-by-step　execution　process,　heuristic　dynamic　task　processing　algorithm　is　used　to　reduce　the　task　latency　time.　Experiments　with　the　＂iFogSim＂　simulator　show　that,　application　service　quality　is　significantly　improved　and　system　power　consumption　is　greatly　reduced,　which　compared　with　the　stable　application　module　placement　strategy　and　the　static　task　scheduling　strategy.