<![CDATA[In the current era, almost every person uses a mobile device for tasks that range from basic phone calls to advanced computations. To increase the QoE of the mobile user, tasks may be offloaded to a cloudlet because of the lack of a large battery, large memory, and sufficient processing power. Cloudlets can be heavily loaded with tasks when they are in a heavily populated area, where tasks are overflowing. Meanwhile, other cloudlets are lightly loaded and their resources are often idle when they are in a moderately populated area, getting fewer tasks. When tasks are queued up for a long time in a heavily loaded cloudlet, the response time and dropout rate of tasks increase. These two parameters deteriorate further when a big task is waiting for a long time. Such big tasks waiting for a long time can be migrated to other cloudlets to utilize the idle resources available in lightly loaded cloudlets, which may provide better QoE to the user. This article uses the Firefly optimization algorithm for choosing which tasks to migrate to which cloudlet for load balancing based on task details such as total waiting task size, task waiting time, and total virtual machine size. The proposed method, called TALBMCC (Task-Aware Load Balancing in Mobile Cloud Computing), also increases the number of tasks executed by cloudlets and reduces the execution time of tasks and the power consumption of mobile devices.]]>
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