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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Load Balanced and Energy Aware Cloud Resource Scheduling Design for Executing Data-intensive Application in SDVC
Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0121040
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 10, 2021.
Abstract: 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 VANET framework are modeled; for example, Software Defined Vehicular Cloud (SDVC). In SDVC, the vehicle enables virtualization technology through SDVN and provides complex data-intensive workload execution in scalable and efficient manner. Vehicular Edge Computing (VEC) addresses various challenges of fifth generation (5G) workload applications performance and deadline requirement. VEC aid in reducing response time, delay with high reliability for workload execution. Here the workload tasks are executed to nearby edge devices connected to Road Side Unit (RSU) with limited computing capability. If the resources are not available in RSU, then the task execution is offloaded through SDN toward heterogeneous cloud server. Existing workload scheduling in cloud environment are designed considering minimizing cost and delay; however, very limited work has been done considering energy minimization for workload execution. This paper presents a Load Balanced and Energy Aware Cloud Resource Scheduling (LBEACRS) design for heterogeneous cloud framework. Experiment outcome shows the LBEACRS achieves better makespan and energy efficiency performance when compared with standard cloud resource scheduling design.
Keywords: Cloud computing; data-intensive applications; heterogenous server; IEEE 802.11p; software defined network; software defined vehicular cloud; vehicular adhoc network; workload scheduling; road side unit; vehicular edge cloud
Shalini. S and Annapurna P Patil, “Load Balanced and Energy Aware Cloud Resource Scheduling Design for Executing Data-intensive Application in SDVC” International Journal of Advanced Computer Science and Applications(IJACSA), 12(10), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121040
@article{S2021,
title = {Load Balanced and Energy Aware Cloud Resource Scheduling Design for Executing Data-intensive Application in SDVC},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121040},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121040},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {10},
author = {Shalini. S and Annapurna P Patil}
}
