A prediction and budget-aware offloading scheme for wearable computing

Wearable devices are very popular nowadays due to their computing and communication abilities. Limited computation, battery, and storage capabilities hinder the growth of emerging latency-sensitive wearable device-based applications. At present, the existing works on wearable computing suffered from higher latency, energy, and user payment due to lack of wearable device users mobility prediction, budget-aware offloading, deadline, resources availability, cooperation, and energy cost awareness. This paper proposes a prediction and budget-aware task offloading for wearable computing by investigating the wearable device users' payment, mobility, cloud, and network resource availability, and task requirements. The effectiveness of the proposed prediction and budget-aware offloading scheme for wearable computing is evaluated by comparing its results with the baseline greedy and independent resource selection scheme. The experimental results demonstrate that our proposed scheme provides a significant performance gain than the compared schemes in terms of makespan delay, user payment, utility, energy cost, and service provider profit.