<p>The capacity to collect, store, and process vast amount of data has increased with the development of IoT devices. More processing tasks may be moved closer to the locations where the data is collected by Internet of Things(IoT) devices through edge computing. The edge computing units (ECUs) may be used for processing tasks in this situation. Every ECU may have a cloudlet, or collection of virtual machines, where tasks can be carried out. Owing to the requirement for nearly instantaneous job response, an effective job offloading plan is necessary. Devising an effective job offloading strategy while optimizing energy consumption and simultaneous minimization of job cancellation, are not found to be considered in literature. To address these issues, we have therefore proposed in this paper a job offloading strategy based on the Cuckoo search meta-heuristic algorithm, subject to energy efficiency and minimal job cancellation. In a simulation, the proposed algorithm performs noticeably better than a state-of-the art edge computing-based job offloading strategy. According to reports, the work is found to achieve 12.8% fewer task cancellations than a cutting-edge approach. It achieves up to 26% lower energy consumption compared to state-of-the-art approaches.</p>