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The efficient and safe management of air conditioner (AC), Piped Natural Gas (PNG) and water pipelines in large buildings is a major challenge for the safety of these buildings. In recent years, Linear Wireless Sensor Networks (LWSN) are being used extensively for monitoring of long natural gas, water, and oil pipelines. LWSNs can also be used for efficient and safe management of AC, PNG and water pipelines in large buildings. In this paper, a scheme for optimal placement of sensors and base stations in a linear fashion to monitor the various pipelines used in large buildings has been proposed. The proposed scheme utilizes the Lion Optimization Algorithm (LOA) and has been compared with three strategies, namely Ant Colony Optimization (ACO), Genetic Algorithm (GA) and Greedy Approach with respect to throughput, lifetime and end-to-end delay. The simulation results show that the proposed scheme exhibits better performance in comparison to the other three considered techniques for all the three parameters. The most striking feature of the proposed approach is that optimization is more effective when the length of the pipeline is more as far as end-to-end delay is concerned. The lifetime of the network is significantly improved using the proposed approach, especially when the length of the pipeline is of medium size, which makes the proposed scheme suitable for energy efficient buildings.

Using enhanced ant colony optimization, this study proposes an efficient heuristic scheduling technique for cloud infrastructure that addresses the issues with nonlinear loads, slow processing complexity, and incomplete shared memory asset knowledge that plagued earlier resource supply implementations. The cloud-based planning architecture has been tailored for dynamic planning. Therefore, to determine the best task allocation method, a contentment factor was developed by integrating these three objectives of the smallest waiting period, the extent of commodity congestion control, and the expense of goal accomplishment. Ultimately, the incentive and retribution component would be used to modify the ant colony calculation perfume-generating criteria that accelerate a solution time. In particular, they leverage an activity contributed of the instability component to enhance the capabilities of such a method, and they include a virtual desktop burden weight component in the operation of regional pheromone revamping to assure virtual computers’ immense. Experiences with the routing protocol should be used to explore or demonstrate the feasibility of our methodology. In comparison with traditional methods, the simulation results show that the proposed methodology has the most rapid generalization capability, and it has the shortest duration of the project, the most distributed demand, and the best utilization of the capabilities of the virtual computer. Consequently, their hypothetical technique of optimizing the supply of resources exceeds world competition.

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