In Covid-19 pandemic, the number of users connecting to the Internet using mobile devices increased. People are doing there every task using mobile phones [16]. These devices are battery-powered and have limited computation capabilities. Their computational capabilities can be enhanced by computation offloading in which required computation is to be done on a third-party server on a cloud instead of the device itself. The cloud offers virtually infinite computation and storage. We proposed that by exploiting parallelism within an application call hierarchy we can decrease the execution time of off-loadable parts and minimize data resend in case of VM crash. We determine function call paths that are independent of each other within an application and schedule each of them on separate VMs in a distributed way. Wherever such independent paths merge, we collapse to a single VM and whenever the paths diverge again, we schedule multiple VMs. If any single VM fails another copy will be created. However, only the code and data associated with the crashed VM needs to be re-transmitted from the client device. In the case of face reorganization application and montage application we decrease execution time to 27.5% and 43.43% respectively. Whereas the data resend in case if any of both VMs crash will be the portion of the application that had been offloaded to respective VM at depending upon the level of parallelism they have which save mobile battery in case of Resend. We will also discuss the energy consumption effect of using multiple Vms for a job VS single Vm for the same job.

翻译：在新冠疫情期间，使用移动设备连接互联网的用户数量显著增加。人们正通过手机完成日常各项任务[16]。这些设备依赖电池供电且计算能力有限。通过计算卸载技术——将所需计算任务交由云端第三方服务器执行而非设备自身——可有效增强其计算能力。云端提供近乎无限的计算与存储资源。我们提出通过挖掘应用程序调用层级间的并行性，能够降低可卸载部分的执行时间，并在虚拟机崩溃时最小化数据重传量。具体而言，我们识别应用程序中彼此独立的函数调用路径，以分布式方式将各路径调度至独立虚拟机执行。当独立路径交汇时，合并为单一虚拟机；当路径再次分叉时，重新调度多虚拟机。若任一虚拟机失效，将创建其副本。但仅需从客户端设备重传与崩溃虚拟机关联的代码及数据。在面部识别应用与蒙太奇应用测试中，执行时间分别降低至原值的27.5%和43.43%。当两个虚拟机中任意一个崩溃时，需重传的数据量仅为已卸载至对应虚拟机的应用程序部分（具体取决于并行化程度），该机制在数据重传时可节省移动设备电量。我们还将讨论使用多虚拟机执行单任务与使用单虚拟机执行同等任务在能耗方面的差异。