COIT20260 Cloud Computing for Smart Applications
Enabling objectives
- Analyse a case study and identify issues associated with the business;
- Develop and deploy the application in IBM Bluemix;
- Evaluate existing and new functionalities to address business problems;
- Prepare a document to report your activities using text and multimedia (for example screenshots, videos).
The assignment requires you to do the following -
- Choose a case study out of given two below and analyse the case study to understand the business problem and design a solution for those problems.
- Deploy the starter source code in your Bluemix account and modify it to address all required milestones mentioned in your chosen case study.
- Finally prepare a report according to given format and specifications below and submit it in Moodle.
Anser:
Introduction
AB Pty. Ltd is taken as a case study in this report. Its business is analyzed to identify the present issues faced by the business. This is a product delivery service business which delivers products to concerned customers. It has totally three trucks to perform the product delivery, for its third parties. In the United States, Austin downtown, Texas is the place where the trucks cover its deliveries. The analysis results in a set of recommendations for the business to improve its delivery business. The problem has sparked from mismanagement of the deliveries and resulting in completing least number of deliveries in a day. This is believed to increase the pending deliveries and causing delayed product deliveries for the customers. The sudden demand for the trucks is considered as the root cause, for all the problems.
This project’s objective is to solve the root cause and help the business grow with the existing resources. To help the business manage its functions a smart application will be proposed, designed and deployed.
IBM Bluemix
Bluemix helps to develop web applications. To access this go to the following URL:
Then, log in and create a dashboard, for the application, in the cloud foundry runtimes.
Select SDK, as mentioned in the figure. Next, open it to give a host name for the application. Thus, the application is created successfully (IEEE Cloud Computing Call for Papers Connecting Fog and Cloud Computing, 2016).
Creation of database must next be the concern.
In DB MySQL, a new Database must be created. This is to establish a connection with the database. After the establishment of the connection the application deployment takes place.
After establishing a successful connection, for both the database and the application, the instances of the application start. This can be viewed from the view tab. Then, proceed to configuration part, by clicking on the right side of the navigation pane or the option edit code. Using the edit code, the modification will be carried out according to the requirements of the users (IEEE Cloud Computing Call for Papers, 2016).
Bluemix devops screen will display the configuration file.
When the editing complete, deploy the files and choose the red button on the screen’s center. As it is pressed, a pop-up window appears to question about redeployment of the file. Just select “Cancel” option.
Further, opt for, “OK” option. As, this will open the window of GIT Repository. In any case, the file could be edited. The configuration files is displayed at the window’s bottom right side. After this, use “Commit” option to commit the files (IEEE Cloud Computing Call for Papers, 2014).
The changed details will be seen on the left side of the window.
After some time, the build and deploy stage is created successfully. Then, successful acknowledgement message is displayed for confirming the creation of the application.
As a final step of execution result, the message which states the success of the application will be displayed.
Issue in the Case Study
As mentioned earlier, this case study is identified to have mismanagement issues in the product deliveries, which has resulted in the current following and interconnected issues of delayed product deliveries and customer dissatisfaction from AB Pty Ltd. The initial deliveries completed by the trucks used to be 5 per day, but gradually the count has decreased to 3 now. The Customers are main part of any business and making the customers unhappy will lead the company nowhere. Hence, the suggestions of the business analyst must be considered as an ICT professional (IEEE Cloud Computing Call for Papers, 2015).
Proposed Solution
The proposed solution is determined to develop a smart application for the Company AB Pty. Ltd., to manage its delivery business effectively. This application is expected to increase the productivity and help the business to grow, with the available trucks. The main benefit is that, the application ensures to track the trucks and keep in contact with the truck drivers. The drivers are accountable for completing their allotted deliveries of the day, where at the end of the day they are supposed to enter the details of their completed deliveries. The IBM Blue mix services are used for developing a dashboard for the application and to help in integrating with cloud and IoT, for increased benefits. For tracking the truck’s location, Geospatial Analytics service is utilized.
The added features for the application will be:
- Effective management of the total number of product deliveries, in a specified location.
- The map will help to interact with the delivery goals, in the location divided as north, south, east and west.
- The truck drivers are communicated with the application, in case of any need.
- The encountered problems in the truck while on delivery process can be shared to he admin, to arrange for the other alternative.
- Alert messages and notification of important details throughout the process will be shared between the drivers and the administrator (IEEE Cloud Computing Call for Papers: Intelligence in the Cloud, 2016).
Design Plan
The design plan of a smart application is mentioned below:
Step 1:Check the website of IBM Bluemix and log in to use it.
Step 2:Integrate both Internet of Things (IoT) and Bluemix, for more benefits.
Step 3:In the dashboard, create an instance of IoT using Internet platform services.
Step 3:Then, configure IoT’s foundation.
Step 4:Make selection of the required device type and enter ID and device.
Step 5:In the dashboard, opt the option of, “Add API” to generate the Keys of new API.
Organization ID: rl79j3
Device Type: Vehicle
Device ID: XYZ
Authentication Method: token
Authentication Token: [email protected]
Organization ID: rl79j3
Device Type: Vehicle
Device ID: XY
Authentication Method: token
Authentication Token: @Rk0&LQ+Vx8+4n&I2J
Step 6:Download, starter kit as the configuration deploys the kit.
Step 7:Clone the project, using the fork project with its repository where:
- Choose edit code option for modifying the present file name to manifest.yml.
- To store the device related information, open config or settings.jsr file and enter the below listed details:
Type of the vehicle for iot_deviceType.
Organization’s ID (six-characters) for iot_deviceOrg.
For all the 3 devices, enter the token with Registered ID for iot_deviceSet
Created API keyfor iot_apiKey.
API key token for iot_apiToken.
Finally, save the entered information.
Step 8:Geospatial Analytics must be created. Then, Geospatial Analytics must be configured. Because it is used as a means to identifythe truck’s location.
Step 9: InBluemix application of the dashboard, select the option,“Add services” and go to “Free.”
Step 10:Go to select the option, “Create”, it helps to activate the application.
Step 11:Next process is to bind the starter kit with geospatial analytics, using the help of IoT application.
Step 12:At the end, opt for, “Alert” option.
https://api.ng.bluemix.net, can be checked to view the developed application.
Deployment Plan
The deployment plan starts with testing the developed application. The Set Property command is considered for checking the sending of commands to the corresponding vehicles. Thus, it allows binding with the map application, where the other properties of the application, for instance speed are considered to be modified (IEEE Cloud Computing Special Issue on Cloud Security, 2015).
Conclusion
This project concludes that the business case study of the selected company, AB Pty. Ltd is completed. The business analysts have helped the ICT professional to decide the right solution, for the present situation of the company. The business is about to drown and it needs immediate assistance to stand strong in the market. To help the business, a smart application using IBM Bluemix is designed and deployed. It has provided various features to support the business, like managing the deliveries, dividing the total number of deliveries among the three trucks and monitoring all its movements. This is expected to resolve the problem of delay. The truck drivers are asked to maintain a specific speed to complete the assigned deliveries without getting into any traffic violations. Therefore, the objective is met and cloud computing solution is provided. Hence, the application aims to resolve the root cause of the problems in AB Pty. Ltd., and helps to smoothly function its product delivery process.
References
Gheith, A., Rajamony, R., Bohrer, P., Agarwal, K., Kistler, M., White Eagle, B., Hambridge, C., Carter, J. and Kaplinger, T. (2016). IBM Bluemix Mobile Cloud Services. IBM Journal of Research and Development, 60(2-3), pp.7:1-7:12.
IBM Blue Gene team (2013). Design of the IBM Blue Gene/Q Compute chip. IBM Journal of Research and Development, 57(1/2), pp.1:1-1:13.
IBM Blue Gene team (2013). The IBM Blue Gene project. IBM Journal of Research and Development, 57(1/2), pp.0:1-0:6.
IEEE Cloud Computing Call for Papers Connecting Fog and Cloud Computing. (2016). IEEE Cloud Computing, 3(4), pp.c2-c2.
IEEE Cloud Computing Call for Papers. (2014). IEEE Cloud Computing, 1(2), pp.41-41.
IEEE Cloud Computing Call for Papers. (2015). IEEE Cloud Computing, 2(5), pp.19-19.
IEEE Cloud Computing Call for Papers. (2016). IEEE Cloud Computing, 3(5), pp.63-63.
IEEE Cloud Computing Call for Papers: Intelligence in the Cloud. (2016). IEEE Cloud Computing, 3(5), pp.25-25.
IEEE Cloud Computing Special Issue on Cloud Security. (2015). IEEE Cloud Computing, 2(5), pp.c2-c2.
Zhang, X., Hu, G., Duan, N., Gao, P., Dong, W., Zhu, J. and Chang, R. (2015). LEARNING-BASED HIGH-THROUGHPUT DISPATCHING FOR TRAJECTORY STREAMS. Services Transactions on Cloud Computing, 3(1), pp.16-29.
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