The　emergence　of　cloud　computing　has　promoted　the　explosive　growth　of　applications,　however,　with　the　repaid　generation　of　an　unprecedented　volume　and　variety　of　data,　the　demand　for　high-quality　mobile　services　with　low　latency　has　been　increasing.　Edge　computing　is　an　emerging　paradigm　that　settles　some　servers　on　the　near-user　side　and　allows　sonic　real-time　requests　from　users　to　be　directly　returned　to　the　user　after　being　processed　by　these　servers　settled　on　the　near-user　side.　At　present,　the　industry　has　two　major　problems　for　edge　computing.　One　is　to　reduce　the　delay　for　the　tasks.　The　other　one　is　to　consider　the　endurance　of　power　consumption.　In　this　paper,　we　focus　on　saving　the　power　consumption　of　the　system　to　provide　an　efficient　scheduling　strategy　in　mobile　edge　computing.　Our　objective　is　to　reduce　the　power　consumption　for　the　providers　of　the　edge　nodes　while　meeting　the　resources　and　delay　constraints.　We　first　approach　the　problem　by　virtualizing　the　edge　nodes　into　master　and　slave　nodes　based　on　the　sleep　power　consumption　mode.　After　that,　we　propose　a　scheduling　strategy　through　balancing　the　resources　of　virtual　nodes　that　reducing　the　power　consumption　and　guarantees　the　user＇s　delay　as　well.　We　use　iFogSim　to　simulate　our　strategy.　The　simulation　results　show　that　our　strategy　can　effectively　reduce　the　power　consumption　of　the　edge　system.　In　the　test　of　idle　tasks,　the　highest　energy　consumption　was　27.9%　lower　than　the　original　algorithm.