Development Of A Cloud-Based System For Information Storage At Headspace

The Non-Functional Requirements of the System

The organization headspace works with the mental ill health patients of 12 to 25 who experience several problems due to depression and anxiety. The organization decided to develop an information system that would store the patients’ data and information in the very first time it is told. The primary aim of developing this system is the elimination of story retelling. A cloud based environment is would be effective for the system implementation (Steele, Min & Lo, 2012). The report highlights a proper cloud environment that will be appropriate for the system implementation along with the recommendation of a proper SDLC approach for project implementation.

Save Time On Research and Writing
Hire a Pro to Write You a 100% Plagiarism-Free Paper.
Get My Paper

The proper operation of the system is judged by specifying the non-functional requirements of the system. Therefore, along with the functional requirements it is essential to consider the non-functional requirements as well. The non-functional requirements identify the different system requirements, interfaces and system constraints (Chung, Nixon & Mylopoulos, 2012). The different non-functional requirements that are identified for this project are discussed in the section below-

The system’s functionality is one major non-functional requirement of the system. Maintaining a proper functionality of the system includes the non functional requirement of data availability and scalability of the system. This is therefore a major non-functional requirement of the system.

The system usability is another significant non-functional requirement of the system. The usability of the system can be increased by incorporation of simple easy and interactive interface of the system. Simple interface increases the usability and in turn enhances the performance of the system. Therefore, it can be considered as a major non-functional requirement of system implementation.

The project is undertaken to develop a system that would store the data of the mental ill patients. This data is very sensitive and therefore the system should be reliable enough to store such sensitive data. Reliability is therefore considered as a primary non-functional requirement of the system. The presence of a data recovery option will help in increasing the reliability of the system.

Save Time On Research and Writing
Hire a Pro to Write You a 100% Plagiarism-Free Paper.
Get My Paper

Effective system performance is another important non-functional requirement for the system. The performance of the system includes the data availability and flexibility as the major non-functional requirement of the system. Proper performance of this system will help in evaluating the system on basis of its objectives and effectiveness.

This is a primary non-functional requirement of the system considering the nature of the data that will be stored into the system. Maintaining the data confidentially is a primary aspect of this project and therefore proper security measures are needed to be taken (Kulkarni et al., 2012). Data encryption is therefore considered as a primary non-functional requirement in this case that will prevent the use and access to an unauthorized person.


Keeping in mind the sensitivity of the data to be stored and the objective of the project the functional requirement identified for the project includes authentication, which will help in limiting the access of the data only to the authorized person. Defining the authorization level of the system will further help in limiting the access to the system. This is related to the non-functional requirement of security and encryption. Encryption of data will definitely help in limiting the data access only to the candidates registered to use this system (Pearce & Bainbridge, 2014). The inclusion of summary statement and report button includes the functional requirement of the system, which corresponds, to the non-functional requirement of performance and usability. Therefore, it is essential to consider both the functional and non functional requirement of the system  in order to develop and implement a system for proper use and access.

Headspace is considering a cloud-based solution to implement this system. Therefore, the cloud environment that is recommended for the project is hybrid cloud. Hybrid cloud environment is chosen out of all the alternatives present because it is appropriate for implementing the project, “My Health record System”. The limitation of public cloud is that it is less secure and very vulnerable to attacks. This solution is therefore not considered in this case as the primary aim of the system is the storage and protection of the data confidentiality. The public cloud is however a very cost effective solution but cannot be considered in this case (AlZain et al., 2012).

The private cloud could have been considered in this case but is not used for this project due to its limitation of data access only in a particular network. This would therefore act as a problem if the patient visits some other professional.

Considering all these limitations, it is recommended for the organization to opt for the hybrid cloud solution for system implementation (Galibus & Vissia, 2015). The strength and weakness of the hybrid cloud environment are elaborated in the following section.

The advantages of the organization in employing a hybrid cloud environment for implementation of this project are listed below-

The major advantage of employing the system in a hybrid cloud environment is that it provides adequate security for safeguarding the confidential data of the system (Li et al., 2015).

The cost of implementation of hybrid cloud is less than that of the private cloud as the public zone of the hybrid cloud can be leveraged from a third party service provider. This therefore enables a cot effective solution (Li et al., 2013). The leveraging of the public cloud will however require adequate security measures


The weaknesses of the hybrid cloud environment are listed below-The presence of the public and the private cloud although offers increasing benefits, the data movement from public to private zone or vice versa can be targeted by an attacker. This may further lead to data theft and failure of maintenance of data confidentiality.

The initial cost of implementation of this system is generally high (Chen & Zhao, 2012).

Therefore, it is recommended for Headspace to use hybrid cloud solution for this project. This would help in providing a secure platform for data storage and access of data. It provides a cost effective solution for the organization as well.

Software development lifecycle or SDLC is required to analyze and plan the different phases and the timeline of the project. A project of software implementation generally consists of phases such as planning, feasibility study, and system testing and so on. The software development life cycle helps in estimating the course and requirements of a project. The two project development life cycle, predictive and adaptive SDLC are discussed in the following paragraphs.

Predictive SDLC approach follows the course of waterfall model of the project management. In this approach, the entire project starting from its initiation to the closure is determined and the beginning stages of the project. The major advantage of this approach is that the entire project undergoes a planned approach of project management. This approach is however, feasible only if the scope and the requirements of the project is clear (Tuteja & Dubey, 2012). This is because, these two criteria are required for project planning. The pros and cons of using a predictive SDLC approach in development of the system are discussed below-

The major advantages of using a predictive approach for system implementation are as follows –

  1. The project follows a planned approach and therefore there is very little or negligible chances of project failure.
  2. The chances of budget or schedule revision are very less in this project and therefore this would be beneficial for the organization to implement this project.
  3. The project is completed in the scheduled time.

The disadvantages of using the predictive SDLC approach in the system implementation are discussed below-

  1. The project modification is impossible in this approach. This is because the entire project is planned at the project initiation.
  2. Feedback path is absent in predictive SDLC approach.

The adaptive SDLC approach is very different from the predictive approach. This is because in this approach, there is no need of planning the entire project at the beginning, instead the project deliverables of each phase is determined (Balaji & Murugaiyan, 2012). The pro and cons of using SDLC approach are discussed below-

The presence of thorough testing procedure and feedback path helps in development of a perfect product.

The possibility of project modification according to customer’s feedback is another advantage of this system.

Maintaining a proper project schedule is impossible.


Cost of implementation is high.

Therefore it is recommended for headspace to use the predictive approach of SDLC as the size of the project is small and the project is urgent (Mahalakshmi & Sundararajan, 2013).


Therefore from the above discussion, it can be concluded that the organization headspace can implement this project in a hybrid cloud environment, keeping in mind the non-functional requirements identified for the project. The report discusses the different SDLC approaches and suggests one approach for this project. v 


AlZain, M. A., Pardede, E., Soh, B., & Thom, J. A. (2012, January). Cloud computing security: from single to multi-clouds. In System Science (HICSS), 2012 45th Hawaii International Conference on (pp. 5490-5499). IEEE.

Balaji, S., & Murugaiyan, M. S. (2012). Waterfall vs. V-Model vs. Agile: A comparative study on SDLC. International Journal of Information Technology and Business Management, 2(1), 26-30.

Chen, D., & Zhao, H. (2012, March). Data security and privacy protection issues in cloud computing. In Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on (Vol. 1, pp. 647-651). IEEE.

Chung, L., Nixon, B. A., Yu, E., & Mylopoulos, J. (2012). Non-functional requirements in software engineering (Vol. 5). Springer Science & Business Media.

Galibus, T., & Vissia, H. E. R. M. (2015). Cloud storage security. Proc NSCE, 2014, 123-127.

Jain, A. K., & Nandakumar, K. (2012). Biometric Authentication: System Security and User Privacy. IEEE Computer, 45(11), 87-92.

Kulkarni, G., Gambhir, J., Patil, T., & Dongare, A. (2012, June). A security aspects in cloud computing. In Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on (pp. 547-550). IEEE.

Li, J., Li, Y. K., Chen, X., Lee, P. P., & Lou, W. (2015). A hybrid cloud approach for secure authorized deduplication. IEEE Transactions on Parallel and Distributed Systems, 26(5), 1206-1216.

Li, Q., Wang, Z. Y., Li, W. H., Li, J., Wang, C., & Du, R. Y. (2013). Applications integration in a hybrid cloud computing environment: Modelling and platform. Enterprise Information Systems, 7(3), 237-271.

Mahalakshmi, M., & Sundararajan, M. (2013). Traditional SDLC Vs Scrum Methodology–A Comparative Study. International Journal of Emerging Technology and Advanced Engineering, 3(6), 192-196.

Pearce, C., & Bainbridge, M. (2014). A personally controlled electronic health record for Australia. Journal of the American Medical Informatics Association, 21(4), 707-713.

Rittinghouse, J. W., & Ransome, J. F. (2016). Cloud computing: implementation, management, and security. CRC press.

Steele, R., Min, K., & Lo, A. (2012). Personal health record architectures: technology infrastructure implications and dependencies. Journal of the Association for Information Science and Technology, 63(6), 1079-1091.

Tuteja, M., & Dubey, G. (2012). A research study on importance of testing and quality assurance in software development life cycle (SDLC) models. International Journal of Soft Computing and Engineering (IJSCE), 2(3), 251-257