Burst　growing　IoT　and　cloud　computing　demand　exascale　computing　systems　with　high　performance　and　low　power　consumption　to　process　massive　amounts　of　data.　Modern　system　platforms　based　on　fundamental　requirements　encounter　a　performance　gap　in　chasing　exponential　growth　in　data　speed　and　amount.　To　narrow　the　gap,　a　heterogamous　design　gives　us　a　hint.　A　network-on-chip　(NoC)　introduces　a　packet-switched　fabric　for　on-chip　communication　and　becomes　the　de　facto　many-core　interconnection　mechanism;　it　refers　to　a　vital　shared　resource　for　multifarious　applications　which　will　notably　affect　system　energy　efficiency.　Among　all　the　challenges　in　NoC,　unaware　application　behaviors　bring　about　considerable　congestion,　which　wastes　huge　amounts　of　bandwidth　and　power　consumption　on　the　chip.　In　this　paper,　we　propose　a　hybrid　NoC　framework,　combining　buffered　and　bufferless　NoCs,　to　make　the　NoC　framework　aware　of　applications＇　performance　demands.　An　optimized　congestion　control　scheme　is　also　devised　to　satisfy　the　requirement　in　energy　efficiency　and　the　fairness　of　big　data　applications.　We　use　a　trace-driven　simulator　to　model　big　data　applications.　Compared　with　the　classical　buffered　NoC,　the　proposed　hybrid　NoC　is　able　to　significantly　improve　the　performance　of　mixed　applications　by　17%　on　average　and　24%　at　the　most,　decrease　the　power　consumption　by　38%,　and　improve　the　fairness　by　13.3%.