(untitled) (International Journal of Engineering and Computer Science, 2018)
Achieving energy efficiency during computational offloading is the critical and is the prime objective of this work. Energy efficient Computational offloading with CO2 reduction (EECOC) is proposed for achieving energy efficiency. Load balancing and CO2 minimization are the control parameters considered during the work. Green computing is accomplished when CO2 is minimized. Hence load balancing and computational offloading leads to the desired objective. Run time migration is considered to reduce the overhead in terms of idle machines. CO2 is emitted by VMs in case they are over burdened. Computation offloading is accomplished to reduce load on VMs hence reducing levels of CO2. Load distribution considers the configuration of VMs. Machines with higher configuration is selected at first place for allocation. Load is further reduced by removing redundancy in given job. Results indicate that Energy efficient Computational offloading with CO2 reduction reduces energy consumption by 23%.