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Nowadays, Cloud Computing (CC) has emerged as a new paradigm for hosting and delivering services over the Internet. However, the wider deployment of Cloud and the rapid increase in the capacity, as well as the size of data centers, induces a tremendous rise in electricity consumption, escalating data center ownership costs and increasing carbon footprints. This expanding scale of data centers has made energy consumption an imperative issue. Besides, users’ requirements regarding execution time, deadline, QoS have become more sophisticated and demanding. These requirements often conflict with the objectives of cloud providers, especially in a high-stress environment in which the tasks have very critical deadlines. To address these issues, this paper proposes an efficient Energy-Aware Tasks Scheduling with Deadline-constrained in Cloud Computing (EATSD). The main goal of the proposed solution is to reduce the energy consumption of the cloud resources, consider different users’ priorities and optimize the makespan under the deadlines constraints. Further, the proposed algorithm has been simulated using the CloudSim simulator. The experimental results validate that the proposed approach can effectively achieve good performance by minimizing the makespan, reducing energy consumption and improving resource utilization while meeting deadline constraints.

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Wireless sensor nodes are resource constrained and have limited amount of energy. Therefore, designing protocols that conserve energy is an important area of research. Researchers have investigated architectures and topologies that allow energy efficient operation of WSNs. One of the popular techniques in this regard is clustering. The different methods of node clustering techniques have appeared in the literature. In this paper, we propose a new protocol called Gateway and Cluster Head Election using Fuzzy Logic in heterogeneous wireless sensor networks (GCHE-FL), this protocol uses two election fuzzy logic to evaluate the chance of sensors to become gateway and cluster head. In the first election (Gateway Election), the qualified nodes are selected based on their energy and proximity to base station. Then, in the second election (Cluster Head Election), two fuzzy parameters are used. These parameters are efficiency which is the ratio between residual energy of each node and the average energy of the cluster, and Cluster_Distance which is the sum of distances between the node and the others nodes which is within cluster. Simulation results show that the proposed approach consumes less energy and prolongs the network life time compared with other protocols.