Energy and latency-balanced osmotic-offloading algorithm for healthcare systems

Healthcare has become an on-the-fly service that is available at one's fingertips through smartphones, smart wearables, etc. Many a task related to health are solved on these devices. However, certain tasks require higher computational resources, leading to high energy consumption. Moreover, various latency-intensive tasks demand immediate actions and need to be completed within a stipulated time or a certain deadline. Offloading tasks to nearby edge devices or moving them to the cloud could be a viable solution to address the problem of latency and energy consumption. We present an offloading algorithm for healthcare systems by leveraging osmotic computing to handle compute-intensive, energy-consuming and latency-intensive tasks. The proposed algorithm is simulated and evaluated using various synthetic test cases to show its efficacy. We have analyzed the performance of our proposed energy and latency-balanced osmotic-offloading (ELBO) algorithm in terms of average latency, success ratio, task failure rate and energy consumption.