The　Multi-access　Edge　Computing　(MEC)　network　enhances　the　processing　capability　of　Internet　of　Things　(IoT)　terminals　by　deploying　3C　resources　(computing　resources,　cache　resources,　and　communication　resources)　at　the　IoT　edge　side,　effectively　improving　the　quality　of　service　(QoS)　of　IoT　applications.　The　majority　of　current　MEC　network　research　focuses　on　task　offloading　and　energy　management,　with　few　studies　looking　at　resource　allocation　from　a　service　provisioning　perspective.　In　this　paper,　we　focus　on　the　resource　allocation　problem　when　processing　multiple　tasks　requested　by　IoT　terminal　devices　in　the　MEC　network.　Firstly,　we　transform　various　tasks　requested　by　IoT　end　devices　into　an　SFC-based　resource　allocation　problem.　Then,　we　model　the　problem　as　a　graph　theory-based　virtualized　network　function　(VNF)　node　deployment　cost　optimization　problem.　Furthermore,　we　propose　two　resource　allocation　and　deployment　strategies　by　jointly　considering　the　computing　cost　and　security　cost　in　VNF　node　deployment.　Finally,　extensive　simulation　experiments　show　that　the　proposed　method　can　significantly　improve　the　success　rate　of　SFC　task　processing　by　more　than　30%　and　network　resource　utilization　by　more　than　20%　when　compared　to　other　deployment　methods　for　processing　multiple　SFC　tasks　with　dynamic　requests.　©　2024　The　Author(s)