A/2, Jahurul Islam Avenue
Jahurul Islam City, Aftabnagar
Cloud Computing, Network Function Virtualization, Edge Computing
Instagram is very popular worldwide, however, a few studies have been conducted regarding the impact of Instagram on academic results. These studies are based on self-reported data which may provide inaccurate findings. Using actual usage data of 7 days, this paper presents a quantitative study [N=71] to examine the impact of Instagram on academic results. We also present how much Instagram is used in different time ranges (e.g. morning) and what is the impact of that on CGPA. We found that Instagram usage behaviour varies by time range. Students used it maximum in the evening and minimum in the morning. However, our correlational analysis shows that there is no correlation between Instagram usage data and CGPA. Supporting this, our comparative study also shows that high and low Instagram users have indifferent CGPA. These findings highlight the possibility that negative impact of social media can be mitigated through proper use.
Mobile Edge Cloud (MEC) provides computation ability close proximate of user compared to Internet Cloud (IC), which ensures flexibility and reliability in executing codes on mobile devices. Offloading resource hungry mobile application to MEC by mobile devices for computation is challenging. On the other hand, maintaining task provisioning within delay constraint is important too. This assignment policy still requires improvement in decreasing completion time of task and thus providing better Quality of Experience (QoE) for users. In this paper, we formulated a delay-aware task assignment as an optimization problem. The optimal assignment of task is Integer Linear Problem (ILP) and NP-Complete. As optimal solution is time costly, hence we proposed a heuristic algorithm, which is done by cooperating the MEC and IC servers to provide feasible task assignment within delay constraint. Extensive performance evaluation of the proposed algorithm indicates significant improvement in successful tasks execution and better QoE can be achieved compared to existing state-of-the-art works.