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EEC-681/781 Distributed Computing Systems

Learn about distribution transparency, failures recovery, scalability techniques, and communication services in distributed computing systems. Understand the benefits of an open distributed system.

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EEC-681/781 Distributed Computing Systems

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  1. EEC-681/781Distributed Computing Systems Discussion#1 (Chapter 1&2) Wenbing Zhao wenbing@ieee.org

  2. Q1: What is the role of middleware in a distributed system? EEC-681: Distributed Computing Systems

  3. Q2: Explain what is meant by (distribution) transparency, and give examples of different types of transparency. EEC-681: Distributed Computing Systems

  4. Q3: Why is it sometimes so hard to hide the occurrence and recovery from failures in a distributed system? EEC-681: Distributed Computing Systems

  5. Q4: Why is it not always a good idea to aim at implementing the highest degree of transparency possible? EEC-681: Distributed Computing Systems

  6. Q5: What is an open distributed system and what benefits does openness provide? EEC-681: Distributed Computing Systems

  7. Q6: Describe precisely what is meant by a scalable system. EEC-681: Distributed Computing Systems

  8. Q7: Scalability can be achieved by applying different techniques. What are these techniques? EEC-681: Distributed Computing Systems

  9. Q8: What is the difference between a vertical distribution and a horizontal distribution? EEC-681: Distributed Computing Systems

  10. Q9: Why are transport-level communication services often inappropriate for building distributed applications? EEC-681: Distributed Computing Systems

  11. Q10: Suppose you could make use of only transient synchronous communication primitives. How would you implement primitives for transient asynchronous communication? EEC-681: Distributed Computing Systems

  12. Q11: Explain why transient synchronous communication has inherent scalability problems, and how these could be solved. EEC-681: Distributed Computing Systems

  13. Q12. The most prominent benefit of the publish/subscribe model is the increased scalability if the number of consumers per message (created by a producer) is large. Understand this benefit by comparing the number of transport-level messages needed to propagate an application-level message to, say, 3 consumers, using the two different messaging models (queue-based and publish/subscribe). EEC-681: Distributed Computing Systems

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