With　the　widespread　utilization　of　intelligent　devices,　massive　mobile　users＇　needs　for　rich　multimedia　services　bring　serious　challenges　in　the　aspects　of　network　traffic,　energy　consumption　and　carbon　emission.　How　to　realize　green　content　distribution　by　optimizing　resource　allocation　is　an　urgent　problem　to　solve　in　complex　and　dynamic　networks.　In　this　paper,　we　design　a　cross-layer　cooperative　scheme　to　promote　energy　efficiency　in　non-orthogonal　multiple　access　(NOMA)-assisted　cloud-edge-side　environments.　To　be　specific,　we　formulate　the　joint　optimization　issue　of　computation,　caching　and　communication　resources　as　an　energy　minimization　model　while　considering　request　aggregation.　Next,　we　propose　a　new　deep　reinforcement　learning　(DRL)-based　task　offloading　strategy　to　minimize　energy　consumption　by　making　optimal　resource　allocation　decisions　according　to　content　request　history　and　resource　availability.　Simulation　results　show　that　the　proposed　solution　has　better　performance　than　current　typical　strategies　in　cloud-edge-end　collaboration　environments.　©　2023　IEEE.