Non-Functional Requirements

The organization of Headspace is one of the most popular and significant medical organizations in New South Wales that treat mental patients. They have noticed that the young people, who have age difference within 18 to 25, are the major victims of mental illness, depression and many others. They require regular treatment due to this type of problems. However, whenever they are being asked about their problems repeatedly, they feel irritated and do not want to communicate. The following report explains about a new project of Headspace, called, New Access for mitigating such issues. Relevant details like non-functional requirements, cloud based solution and SDLC approach would be described here.

Non Functional Requirements

Functionality

It is the most important and noteworthy factor for the FURPS within the project of New Access in Headspace. The treatment process is improved by implementing a better system for their young patients by providing storage for the medical data (Yang et al., 2013). The easy accessibility of the data is the next significant functionality of this system.

Usability

This is the second factor of FURPS for the New Access project. Major uses of the project would be to store the data, when the first time these stories are being narrated as well as the periodical up gradation of the system (Sadiku, Musa & Momoh, 2014). The next important usability is reducing complexity of project or the consumption of time.

Reliability

The third significant and important factor of the FURPS for this project of New Access in Headspace organization is the checking of reliability. This particular factor is being measured by taking into consideration about the reliability of the sources, from which these data are being collected for using them. Moreover, a checking is also required that whether the data is used for treatment purpose or not (Xia et al., 2016). However, there is no chance of lack of reliability in New Access project, since the data is being collected from the patients as well as their family members. Therefore, reliability is highly maintained here.

Performance

This particular factor of FURPS provides the assurance that the respective information system of New Access can provide a better performance to the users. Moreover, a distinct data management is possible here. The lower response time is the important measure of performance as well as various emergency services are provided here.

Security

This is the final non functional requirement of FURPS. The data security is enhanced here and provides a major assurance that the data will not be lost at any cost (Rahimi et al., 2014). New Access project of Headspace would provide such a system, which has no chance of data loss. Moreover, data up gradation is also done here easily and promptly.

Three types of cloud based solutions are possible for New Access project. They are provided below:

1. i) Private Cloud: This is most secured cloud service that allows data access only in a restricted private group of people and hence data loss is avoided (Pearson, 2013).
2. ii) Public Cloud: Here, the data access is done publicly and in an open network. Hence, there exists a high chance of data theft and data loss.

iii) Hybrid Cloud: This specific cloud is the proper combination of both private cloud and public cloud and hence the advantages of both of these cloud services are present here.

Cloud-Based Solutions for New Access Project

Strengths of Hybrid Cloud

The major strengths of the hybrid cloud for New Access project are provided below:

1. i) Higher Flexibility: Hybrid cloud is extremely flexible and scalable in comparison to the other clouds (Moreno-Vozmediano, Montero & Llorente, 2013).
2. ii) Less Consumption of Time: Another important and significant advantage of the hybrid cloud for this project of New Access is that the total consumption of time is extremely less and thus the effectiveness as well as efficiency is increased.

Weaknesses of Hybrid Cloud

The major weaknesses of the hybrid cloud for New Access project are provided below:

1. i) Lack of Strong Network: Hybrid cloud does not provide stronger network to the users and hence data transfer becomes problematic (Botta et al., 2014).
2. ii) High Costs: The hybrid cloud is extremely costly and hence often it becomes a problem for affording this cloud.

Predictive SDLC Approach

The predictive approach of SDLC helps to monitor the overall project life cycle by providing a proper project plan, before project initiation. This specific predictive approach could only be applied, when the respective schedule as well as scope of the project is absolutely clear (Aazam & Huh, 2014). The pros and cons of predictive approach are provided below:

Pros:

1. i) Project Plan Accuracy: The most significant pro of this predictive approach of SDLC is that it helps in providing accuracy within the plan of the project. Hence, errors are avoided.
2. ii) Clear Project Scope as well as Schedule: This approach even ensures that the scope as well as the schedule of the project is clear and accurate.

Cons:

1. i) No Modifications: The first con of a predictive SDLC approach is that there is no scope of modifications in the project (Chen et al., 2016).
2. ii) No Consideration of Client’s Feedback: Predictive approach does not allow any type of feedback of clients to be considered, since the project plan is made beforehand.

Adaptive SDLC Approach

Adaptive approach is majorly responsible for allowing several types of modifications within the project stages as per the requirements of the clients. Project deliverables are sent to the client in each and every project stage and hence the client gets an idea of the project progress. Moreover, they can even the project deliverables as per choice. The pros and cons of adaptive approach are provided below:

Pros:

1. i) Better Project Progress: As the project deliverables are sent to the client in each stage of the project, the client gets a better idea about the overall progress of this project (Ali, Khan & Vasilakos, 2015).
2. ii) Successful Modifications in Project: Another important pro of this particular approach is that there are constant modifications within the project result.

Cons:

1. i) High Consumption of Time: Due to the constant and several modifications in the project, the overall consumption of time is quite high and the schedule is always indefinite in adaptive approach.
2. ii) High Costs: The total cost is extremely high in this particular SDLC approach and often it becomes an issue to afford this approach.

Recommended SDLC Approach

The most relevant and suitable approach of SDLC for the project of New Access in Headspace would be the predictive approach. This is the major because this predictive SDLC approach is responsible for making a perfect project plan for the project that is to be executed. The cost effectiveness and high efficiency are the other important advantages of this predictive SDLC approach. The entire project of New Access hence would be highly benefitted with this particular approach.

Conclusion

Hence, it is concluded that the project of New Access is the most relevant solution for the treatment of young mental patients in New South Wales, started by Headspace. The most significant purpose of the deployment of New Access project would be that the confidential data or information management is extremely easier. Moreover, the questions faced by them could also be avoided easily and promptly. The young patients will not be disturbed anymore and they would feel secured and the treatment would be completed easily. The above report has provided the description regarding with project with some recommendations for the betterment of the project such as SDLC approach, cloud solution and non-functional requirement.

References

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Ali, M., Khan, S. U., & Vasilakos, A. V. (2015). Security in cloud computing: Opportunities and challenges. Information sciences, 305, 357-383.

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Chen, X., Jiao, L., Li, W., & Fu, X. (2016). Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Transactions on Networking, (5), 2795-2808.

Moreno-Vozmediano, R., Montero, R. S., & Llorente, I. M. (2013). Key challenges in cloud computing: Enabling the future internet of services. IEEE Internet Computing, 17(4), 18-25.

Pearson, S. (2013). Privacy, security and trust in cloud computing. In Privacy and Security for Cloud Computing (pp. 3-42). Springer, London.

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Sadiku, M. N., Musa, S. M., & Momoh, O. D. (2014). Cloud computing: opportunities and challenges. IEEE potentials, 33(1), 34-36.

Xia, Z., Wang, X., Zhang, L., Qin, Z., Sun, X., & Ren, K. (2016). A privacy-preserving and copy-deterrence content-based image retrieval scheme in cloud computing. IEEE Transactions on Information Forensics and Security, 11(11), 2594-2608.

Yang, L., Cao, J., Yuan, Y., Li, T., Han, A., & Chan, A. (2013). A framework for partitioning and execution of data stream applications in mobile cloud computing. ACM SIGMETRICS Performance Evaluation Review, 40(4), 23-32.