Abstract
Mobile cloud computing (MCC) plays a significant role in obtaining virtualized data stored on cloud servers without additional waiting time. However, the limited battery power of mobile devices limits access to ample data. To address this problem, job scheduling algorithms based on completion time constraints are introduced to reduce energy consumption. The time complexity of scheduling algorithms increases for applications not based on completion time constraints. This paper proposes a hybrid energy-efficient (HEE) paradigm to support the Internet of Things (IoT). The proposed HEE algorithm leverages the features from known pheromone termite (PT) and cuckoo search (CS) algorithms, supporting IoT-enabled users and devices. The integration of PT and CS helps determine the optimal path that leads to improved throughput and reduced energy consumption. The performance of the HEE algorithm is considerably higher than that of the PT and CS algorithms when the number of tasks increases. The proposed paradigm involves several modules (e.g., physical machine (PM) module, controller module, blockchain-enabled authentication module, and data mining-enabled mobile cloud user (MCU) authentication). The PM module helps to attain a higher energy efficiency, regardless of whether the cloud’s level of utilization is at its maximum efficiency. The controller module schedules the PMs efficiently and thus effectively provides resources to MCUs. Securing the identity of MCUs is of paramount significance. Safeguarding the identity of the MCU, the blockchain-enabled authentication module is employed, which authenticates the MCU to control the malicious role of the adversary. Furthermore, the data-mining blockchain-enabled authentication module authenticates the insider and outsider MCUs based on the data contents. The legitimate MCUs are allowed, and illegitimate MCUs are restricted. The proposed HEE paradigm is tested on the CloudSim simulator. Finally, the performance of the HEE paradigm is compared with that of known algorithms in terms of energy, security, throughput, and latency.
•Proposes a hybrid energy-efficient (HEE) paradigm to support the IoT.•Leverages the features from known pheromone termite (PT) and cuckoo search (CS).•The proposed algorithm has the support of a data oriented detection algorithm.•The Blockchain enabled detection module is incorporated to authenticate the MCU to control malicious adversaries.