Nowadays, mobile devices perform almost all tasks that can be performed by a computer but empties the battery and consumes memory. It is not necessary to execute the tasks on mobile devices; instead, it is executed in the far-away cloud. To save battery energy, the tasks are offloaded and hopped through several access points to reach the cloud and executed which increased the execution time of the task. Therefore, to save execution time and energy, the tasks are offloaded to a nearby cloudlet and as the device moves, the cloudlet and mobile device are disconnected. The mobile device is connected to the next cloudlet; while the offloaded tasks are partially executed in the previous cloudlet VM migrates to the new cloudlet. The previous cloudlet examined the remaining execution time of the task. If it is less than the connection time, the task is finished and the result is transferred to the new cloudlet; otherwise, the task is offloaded to the new cloudlet. It is seen that the mobility and execution time aware task offloading model reduces the execution time and power consumption by 21-40% and 26-34% approximately to the existing mobility-aware offloading approach.
Awais AhmedArif Mohammad AbdulOmprakash KaiwartyaMuhammad UsmanO SyedAanchal Aanchal
Bidoura AhmadMohammad IrfanMd. Shariful
Sura KhalilS. A. R. Al-HaddadFazirulhisyam HashimAzizol AbdullahSalman Yussof