The 5G is expected to revolutionize every sector of life by providing interconnectivity of everything everywhere at high speed. However, massively interconnected devices and fast data transmission will bring the challenge of privacy as well as energy deficiency. In today's fast-paced economy, almost every sector of the economy is dependent on energy resources. On the other hand, the energy sector is mainly dependent on fossil fuels and is constituting about 80% of energy globally. This massive extraction and combustion of fossil fuels lead to a lot of adverse impacts on health, environment, and economy. The newly emerging 5G technology has changed the existing phenomenon of life by connecting everything everywhere using IoT devices. 5G enabled IIoT devices has transformed everything from traditional to smart, e.g. smart city, smart healthcare, smart industry, smart manufacturing etc. However, massive I/O technologies for providing D2D connection has also created the issue of privacy that need to be addressed. Privacy is the fundamental right of every individual. 5G industries and organizations need to preserve it for their stability and competency. Therefore, privacy at all three levels (data, identity and location) need to be maintained. Further, energy optimization is a big challenge that needs to be addressed for leveraging the potential benefits of 5G and 5G aided IIoT. Billions of IIoT devices that are expected to communicate using the 5G network will consume a considerable amount of energy while energy resources are limited. Therefore, energy optimization is a future challenge faced by 5G industries that need to be addressed. To fill these gaps, we have provided a comprehensive framework that will help energy researchers and practitioners in better understanding of 5G aided industry 4.0 infrastructure and energy resource optimization by improving privacy. The proposed framework is evaluated using case studies and mathematical modelling.

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Software application is still a heavy dependence for most of the business operation today. Whenever software application encounters error that causes downtime in the production environment, the root cause of the error can be either within the software application layer or any other factor outside the software application layer. To accurately identify the root cause is difficult whenever more than one log file is required for the root cause analysis activity.Due to such complexity, it leads to the entire duration on the root cause analysis activity became prolong. This will increase the total time taken on restoring the software application service back to the users. In order to identify the root cause of software application error in a more accurate manner, and shorten the duration of root cause analysis activity conducting on software application error, a Prescriptive Analytical Logic Model incorporates with Analytic Hierarchy Process (AHP) is proposed. The proposed Logic Model along with the algorithm will contribute a new knowledge in the area of log file analysis to shorten the total time spent on root cause analysis activity.