Software Engineering Assignment: Improvising Performance Of Cloud Computing

Question

Task:
Select a research article related to enhancing the performance of cloud computing and prepare a report on software engineering assignment illustrating the key purpose, findings, issues and conclusion of the article.

Answer

Introduction
Cloud Computing is one of the popular technologies that are used on the automated systems and platforms in the present times. The software engineering assignment sheds light on several ways in which the performance of the cloud platforms can be improved.

Selected Article
[1]A. Jacob and C. Raj, “Performance Enhancement of Cloud Computing: Methodology & Tool,” International Journal of Innovative Technology and Exploring Engineering, vol. 9, no. 1, pp. 1400–1405, Nov. 2019.

Purpose
The purpose is to determine the ways in which the performance of cloud computing can be enhanced. The review and analysis of the selected article is done for this purpose [1].

Outline
The intention of the authors is aimed to be understood first which is then followed by the analysis of the article content. The research methods and findings are explored followed by the problems, results, and conclusion.

Intent & Content
There are different cloud models that are used by the users from all across the globe. The selection of these cloud models depend upon the business requirements and the specific cloud features. The authors intend to determine the ways in which the testing procedures can be conducted on the cloud platforms for the improvement of the performance of the cloud services.

The first section of the research paper includes the introduction section in which the background to the cloud models is presented along with the specific benefits associated with the cloud services. The cloud offerings are described next using the cloud models that are used by the users from all parts of the world [2]. The cloud stack components along with the information on virtual machine node and high performance computing are covered in the next sections. The features that shall be tested are included followed by the testing methods and tools. The conformity debugging along with the communication bottleneck detector is explained followed by the conclusion.

Methods & Findings
The use of qualitative and quantitative measures is done in parallel to carry out the research. The qualitative methods are used to provide the background to the research along with the overview of the cloud models and offerings using the research analysis. The use of the literature review is also done to present these findings. The testing and analysis is done using the qualitative measures to evaluate the performance of the cloud models and the bugs that are commonly present in cloud that impact the performance in an adverse way.

The authors have presented the findings throughout the research paper. These findings are based on the testing that is conducted and the performance evaluations. The use of PerfKit tool has been done to execute the performance test cases and the utilization of the in-house debugger is done for the purpose of debugging and for the visualization of the performance bottleneck. There are a number of bugs that have been identified along with the recommendations that can be used to avoid these bugs and defects. The cloud models are used for the transmission of the information over the network and from one software system to the other [3]. There is congestion that impacts the performance of these procedures and it can be treated through the automated detection of the factors that may lead to congestion. The use of the visualization and debugging tools can be done to understand the areas that may be involved in the congestion. The identification of the problematic regions will provide the mechanisms to implement the solutions. The patterns can also be visualized using the tools which can assist in better control and monitoring. The graphical diagrams can be used to understand the problem areas and the communication activities being executed in such regions. The collection and analysis of the event traces can also be done using the tools. The cloud models follow the distributed computing principles and it is possible that there are issues that appear in the parallel executions. It is essential that the identification and resolution of these issues is done so that the cloud performance can be maintained. The software systems rely supremely on the performance of the cloud networks and services. The issues around congestion in the communication or the inability to balance the load can impact the performance of the network connectivity and the overall software systems. The load balancing features need to be improved on the cloud platforms so that the performance does not vary with the increase in the load.

Problems & Issues
The use of cloud models and networks is increasing with each passing day. The software systems and networks make use of the cloud services for the passing of information. The cloud models are also used to keep the connectivity intact at all times. There are certain issues that the article discusses in terms of the cloud performance and load balancing. The use of PerfKit tool and the debugging tools is done to understand the major issues that are associated with the cloud platforms. There are various bugs that have been recognized alongside the suggestions that can be utilized to evade these bugs and imperfections. The cloud models are utilized for the transmission of the data over the network and from one programming system to the next. There is congestion that impacts the performance of these techniques and it tends to be treated through the automated detection of the components that may lead to congestion. The utilization of the visualization and debugging tools should be possible to comprehend the areas that might be engaged with the congestion. The distinguishing proof of the dangerous regions will give the components to execute the arrangements [4].

The patterns can likewise be imagined utilizing the tools which can aid better control and monitoring. The graphical diagrams can be utilized to comprehend the difficult areas and the correspondence exercises being executed in such regions. The assortment and analysis of the event traces should likewise be possible utilizing the tools. The cloud models follow the circulated figuring standards and it is conceivable that there are issues that show up in the equal executions. It is basic that the recognizable proof and goals of these issues is done with the goal that the cloud performance can be kept up. The product systems depend especially on the performance of the cloud networks and services. The issues around congestion in the correspondence or the failure to adjust the load can affect the performance of the network connectivity and the general programming systems. The load balancing features should be enhanced the cloud platforms so the performance doesn't shift with the expansion in the load.

Results & Discussion
The outcomes of the research work will assist the business users in the improvement of the cloud performance and services. There are different bugs that have been perceived close by the proposals that can be used to dodge these bugs and defects. The cloud models are used for the transmission of the information over the network and starting with one programming system then onto the next [5]. There is congestion that impacts the performance of these strategies and it will in general be treated through the automated detection of the segments that may lead to congestion. The use of the visualization and debugging tools should be conceivable to understand the areas that may be locked in with the congestion. The distinctive confirmation of the risky regions will give the segments to execute the courses of action. The patterns can in like manner be envisioned using the tools which can help better control and monitoring. The graphical diagrams can be used to appreciate the troublesome areas and the correspondence practices being executed in such regions. The variety and analysis of the event traces should similarly be conceivable using the tools. The cloud models adhere to the circled figuring principles and it is possible that there are issues that appear in the equivalent executions. It is essential that the unmistakable confirmation and objectives of these issues is finished with the objective that the cloud performance can be kept up. The item systems rely particularly upon the performance of the cloud networks and services. The issues around congestion in the correspondence or the inability to change the load can influence the performance of the network connectivity and the general programming systems. The load balancing features ought to be improving the cloud platforms so the performance doesn't move with the extension in the load [6].

Conclusion
The last is the conclusion section that gives a brief of the overall research work. The tools which are used to determine the performance lags in the cloud models have been used properly and the use has been justified. This is because the bugs that are identified need to be resolved and with the resolution of the identified bugs, it will be easier to improve the performance of the software systems, cloud networks, and models. The cloud services and platforms have become the integral part of the business processes and software industries in the current times. It is, therefore, essential that the management of the cloud platforms and software models is done effectively.

References
[1] A. Jacob and C. Raj, “Performance Enhancement of Cloud Computing: Methodology & Tool,” International Journal of Innovative Technology and Exploring Engineering, vol. 9, no. 1, pp. 1400–1405, Nov. 2019.

[2] D. S. Linthicum, “Software-Defined Networks Meet Cloud Computing,” IEEE Cloud Computing, vol. 3, no. 3, pp. 8–10, May 2016.

[3] D. S. Linthicum, “Approaching Cloud Computing Performance,” software engineering assignment IEEE Cloud Computing, vol. 5, no. 2, pp. 33–36, Mar. 2018.

[4] M. Kumar, “Combination of Cloud Computing and High Performance Computing,” International Journal Of Engineering And Computer Science, Dec. 2016.

[5] N. Zanoon, “Toward Cloud Computing: Security and Performance,” International Journal on Cloud Computing: Services and Architecture, vol. 5, no. 5/6, pp. 17–26, Dec. 2015.

[6] K. Bu, B. Xiao, and Y. Qian, “High performance and security in cloud computing,” Concurrency and Computation: Practice and Experience, vol. 29, no. 19, p. e4241, Jul. 2017.