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Summary In the ocean, huge number of sensor nodes (SNs) are located to transfer the information between other nodes using the Underwater Acoustic Sensor Network (UASN) framework. An underwater acoustic communication technique is utilized by this UASN to exchange the information. Because of environmental conditions and adverse channel, the SNs in UASN may have link breakages. Likewise, maximum target coverage rate for SN deployment is considered as another issue. So it is very essential to create a strong communication system in underwater together with the different kind of variations in ocean environment. As a result, the system will perform better data transmission with the severely fluctuating underwater communication conditions. In this paper, a latest optimization algorithm named as Sea Lion Optimization (SLO) procedure is proposed to discover the optimal location for SN in underwater communication. This algorithm optimally places the acoustic SNs based on the maximum connectivity rate by finding the targeted optimal position. The Matlab tool is utilized for implementation purpose, and the different kinds of parameters like connectivity rate, coverage rate, and delay are taken to evaluate the performance of proposed methodology. Moreover, the existing methods like deployment scheme, Connected Dominating set based depth computation Approach (CDA) approach, and distributive approach are taken to contrast the performance of proposed methodology. When compared to the previous algorithms, our proposed methodology achieves 95% connectivity ratio for varying number of acoustic SNs.

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Cloud computing is the dynamic delivery of information technology resources and capabilities as a service over the Internet. Cloud computing is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. It generally incorporates infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). [1] Load balancing is one of the biggest challenges in the cloud computing. The concept of load balancing is to equally distribute the workload, resources across all the nodes to guarantee that all the nodes have equal load i.e. no single node is over loaded. As we all know that cloud computing services are mainly product based so in this approach we are using different product based priority queues for different services.

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