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Cloud computing offers a pool of virtual resources to users on demand. Among the main challenge facing cloud computing is job scheduling which is an NP-hard problem. Usually, scheduling should consider job priority, where high-priority jobs should be immediately allocated required resources, whereas low-priority jobs can wait. In this paper, we propose a scheduling algorithm that imitates the parasitic behaviour of the cuckoo bird. Cuckoos reproduce by exploiting the nests of other birds with eggs similar to their own. We have evaluated the proposed cuckoo scheduling algorithm under varying number of nodes and percentage of high priority jobs. The experimental results demonstrate the superiority of our proposed algorithm over the benchmarks in terms of average CPU utilization and average turnaround time for each type of job. [ABSTRACT FROM AUTHOR]

As the use of Wireless Sensor Networks grows, many challenging issues with these networks arise. The utilization of power consumption is one of the most significant issue due to the limited energy constraints of the individual sensor nodes. This limitation imposes a challenge to design the best energy-efficient routing mechanism. This work presented an Energy-Efficient Gossiping protocol (EEGossip) that routes data to the sink by choosing the optimal next node. EEGossip uses Chebyshev distance, residual energy and the sink distance as factors when determining the optimal next node. The result of the proposed work has shown that the proposed protocol improves the total energy consumption of the network and leverages the network lifetime since it decreases the computational overhead and ensures that the best next node is chosen. [ABSTRACT FROM AUTHOR]