Load Balanced and Energy Aware Cloud Resource Scheduling Design for Executing Data-intensive Application in SDVC

Cloud computational platform provisions numerous cloud-based Vehicular Adhoc Network (VANET) applications. For providing better bandwidth and connectivity in dynamic manner, Software Defined VANET (SDVN) is developed. Using SDVN, new framework are modeled; for example, (SDVC). In SDVC, the vehicle enables virtualization technology through SDVN provides complex data-intensive workload execution scalable efficient manner. Edge Computing (VEC) addresses various challenges of fifth generation (5G) applications performance deadline requirement. VEC aid reducing response time, delay with high reliability execution. Here tasks executed to nearby edge devices connected Road Side Unit (RSU) limited computing capability. If resources not available RSU, then task offloaded SDN toward heterogeneous cloud server. Existing scheduling environment designed considering minimizing cost delay; however, very work has been done energy minimization This paper presents a Load Balanced Energy Aware Resource Scheduling (LBEACRS) design framework. Experiment outcome shows LBEACRS achieves makespan efficiency when compared standard resource design.