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Case Study: Distributed Systems in Ride-Sharing Platforms DUE 11:55pm Friday, 11th April This assessment item accounts for 20% of the total marks (100) of the unit.This case study is set to individual. The marking will be conducted

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Assignment1(REVISEDon20thMarch)

Case Study: Distributed Systems in Ride-Sharing Platforms DUE 11:55pm Friday, 11th April

This assessment item accounts for 20% of the total marks (100) of the unit.This case study is set to individual. The marking will be conducted in two steps: (1) offline marking on the report, and (2) assessing understanding of the case study through a viva during your allocated workshop class in Week 8.

Yourtaskis to analyze how ride-sharing platforms design distributed systems (e.g.,Uber,DiDi) to match riders and drivers efficiently and reliably.

  • Real-Time Data Processing: Explain how ride requests and driver locations are processed in real-time across distributed servers.
  • Scalability: Describe how the system scales during high-demand events (e.g., New Years Eve) and manages surge pricing.
  • Fault Tolerance: Investigate how the platform handles server failures and ensures uninterrupted ride- matching services.
  • Data Consistency: Discuss how the platform manages data consistency for dynamic pricing and driver availability across regions.

Your submissionshall be ONLY your5-pagereport. You are required to use LATEX (e.g., Overleaf) for your report.The template LATEX will be provided for your report.You submit only the PDF file of your report.

Suggestedheadingsofthereportareasfollows(STRICTLY5pagesmaxexcludingreferences):

  1. Introduction (1/2 page1):Whatthisreportisabout,includingthepurposeofthecasestudyandthe system overview (e.g., client-server model and microservices architecture).
  2. Real-Time Data Processing (1 page):Real-Time Communication Systems including Pub/Sub Messaging Systems and WebSockets.
  3. Scalability(1page):Dynamicscalingtoautomaticallyadjustservercapacitybasedon
  4. Fault Tolerance (1 page): Description of how Uber ensures reliable services with respect to load balancing and redundancy.
  5. Data Consistency (1 page): How Uber makes use of distributed databases to store and manage data, including replication and partitioning of data storage.
  6. Summary (1/2 page):Summary of your case study including challenges in Ubers Distributed SystemsArchitecture and any thoughts on improvements.
  7. References.

Ifyouwouldliketoaddafigureotherthanyourown,youshouldeithergetawrittenpermissionfromtheauthor(s) or redraw it yourself and cite the source.

Markingrubric(inpercentage)

85to100

Work presents a full and comprehensive account of all requirements. Report is genuine, accurate, detailed and concise.

Cleardemonstrationofunderstandinginviva.

1Thenumberofpagesforeachsectionisonlyindicative.

2Note: If you have used Generative AI, you must acknowledge HOW you have used it in your assessments by including a reference (citation) or acknowledgment.

75to84

Work presents a very good account of most requirements, with minor omissions. Report is genuine and accurate, with good detail and generally concise.

Strong demonstration of understanding in viva, though may lack some nuance. May have small gaps or areas that could be developed further.

65to74

Work presents a good account of key requirements, though some aspects may be underdeveloped. Report is genuine and mostly accurate, with adequate detail but may occasionally lack concision. Satisfactory demonstration of understanding in viva, though some concepts may need clarification. Shows competence but lacks the depth and comprehensiveness of higher bands.

50to64

Work presents a basic account of main requirements, with notable omissions or superficial coverage. Report is genuine but may have some inaccuracies, with inconsistent detail and concision.

Basic demonstration of understanding in viva, with significant areas needing clarification. Meets minimum requirements but lacks depth, detail, or thorough understanding

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