Sensors, Vol. 24, Pages 2381: Multi-Objective Task-Aware Offloading and Scheduling Framework for Internet of Things Logistics

Sensors, Vol. 24, Pages 2381: Multi-Objective Task-Aware Offloading and Scheduling Framework for Internet of Things Logistics
Sensors doi: 10.3390/s24082381
Authors:
Asif Umer
Mushtaq Ali
Ali Imran Jehangiri
Muhammad Bilal
Junaid Shuja

IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon is called task offloading. Researchers have developed efficient task offloading and scheduling mechanisms for IoT devices to reduce energy consumption and response time. However, most research has not considered fault-tolerance-based job allocation for IoT logistics trucks, task and data-aware scheduling, priority-based task offloading, or multiple-parameter-based fog node selection. To overcome the limitations, we proposed a Multi-Objective Task-Aware Offloading and Scheduling Framework for IoT Logistics (MT-OSF). The proposed model prioritizes the tasks into delay-sensitive and computation-intensive tasks using a priority-based offloader and forwards the two lists to the Task-Aware Scheduler (TAS) for further processing on fog and cloud nodes. The Task-Aware Scheduler (TAS) uses a multi-criterion decision-making process, i.e., the analytical hierarchy process (AHP), to calculate the fog nodes’ priority for task allocation and scheduling. The AHP decides the fog nodes&...

Source: Sensors - April 9, 2024 Category: Biotechnology Authors: Asif Umer Mushtaq Ali Ali Imran Jehangiri Muhammad Bilal Junaid Shuja Tags: Article Source Type: research