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Distributed Systems and Security: An Introduction

Distributed Systems and Security: An Introduction. Brad Karp and Steve Hailes UCL Computer Science. CS Z03 / 4030 2 nd October, 2006. Today’s Lecture. Logistics Course Communication Overview of Distributed Systems What are they? Why build them? Why are they hard to build well?

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Distributed Systems and Security: An Introduction

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  1. Distributed Systems and Security:An Introduction Brad Karp and Steve Hailes UCL Computer Science CS Z03 / 4030 2nd October, 2006

  2. Today’s Lecture • Logistics • Course Communication • Overview of Distributed Systems • What are they? • Why build them? • Why are they hard to build well? • Detailed Syllabus: Distributed Systems • Assessment regime • Questionnaire

  3. Logistics • Meeting Times/Locations • Monday: 9 AM – 10 AM , MPEB 1.20 • Monday: 1 PM – 2 PM, MPEB 1.03 • Tuesday: 1 PM – 2 PM, MPEB 1.20 • Schedule • 2nd October – 31st October: Distributed Systems • 6th November – 10th November: Reading Week (no lecture) • 13th November – 12th December: Security

  4. Course Communication • Course web page • http://www.cs.ucl.ac.uk/staff/B.Karp/z03/ • Detailed calendar: readings, lecture topics, coursework, announcements/corrections • Your responsibility: check page daily! • Course mailing lists • {gz03,4030}@<department’s domain> • Verify you’re a member using mlist • Used for course announcements • Your responsibility: check email daily!

  5. What Is a Distributed System? • Multiple computers (“machines,” “hosts,” “boxes,” &c.) • Each with CPU, memory, disk, network interface • Interconnected by LAN or WAN (e.g., Internet) • Application runsacross this dispersed collection of networked hardware • Butuser sees single, unified system

  6. What Is a Distributed System?(Alternate Take) “A distributed system is a system in which I can’t do my work because some computer that I’ve never even heard of has failed.” • Leslie Lamport, Microsoft Research (ex DEC)

  7. What are shortcomings of this design? Start Simple: Centralized System • Suppose you run Gmail • Workload: • Inbound email arrives; store on disk • Users retrieve, delete their email • You run Gmail on one server with disk Email Sender Email Reader Email Sender Gmail Server (PC) Email Reader Email Sender Email Reader

  8. Why Distribute? For Availability • Suppose Gmail server goes down, or network between client and it goes down • No incoming mail delivered, no users can read their inboxes • Fix: replicate the data on several servers • Increased chance some server will be reachable • Consistency? One server down when delete message, then comes back up; message returns in inbox • Latency? Replicas should be far apart, so they fail independently • Partition resilience? e.g., airline seat database splits, one seat remains, bought twice, once in each half!

  9. Why Distribute?For Scalable Capacity • What if Gmail a huge success? • Workload exceeds capacity of one server • Fix: spread users across several servers • Best case: linear scaling—if U users per box, N boxes support NU users • Bottlenecks? If each user’s inbox on one server, how to route inbound mail to right server? • Scaling? How close to linear? • Load balance? Some users get more mail than others!

  10. Performance Can Be Subtle • Goal: predictable performance under high load • 2 employees run a Starbucks • Employee 1: takes orders from customers, calls them out to Employee 2 • Employee 2: • writes down drink orders (5 seconds per order) • makes drinks (10 seconds per order) • What is throughput under increasing load?

  11. What would preferable curve be? What design achieves that goal? Starbucks Throughput • Peak system performance: 4 drinks / min • What happens when load > 4 orders / min? • What happens to efficiency as load increases?

  12. Why Are Distributed SystemsHard to Design? • Failure: of hosts, of network • Remember Lamport’s lament • Heterogeneity • Hosts may have different data representations • Need consistency (many specific definitions) • Users expect familiar “centralized” behavior • Need concurrency for performance • Avoid waiting synchronously, leaving resources idle • Overlap requests concurrently whenever possible

  13. Security • Before Internet: • Encryption and authentication using cryptography • Between parties known to each other (e.g., diplomatic wire) • Today: • Entire Internet of potential attackers • Legitimate correspondents often have no prior relationship • Online shopping: how do you know you gave credit card number to amazon.com? How does amazon.com know you are authorized credit card user? • Software download: backdoor in your new browser? • Crypto not enough alone to solve these problems!

  14. Detailed Syllabus:Distributed Systems • No textbook • Readings: research papers on real, built distributed systems that illustrate concepts • You must read papers by day assigned! • Lectures will assume you have. • Lectures: (some) background for papers; review system from paper; discuss system • See schedule on course web page

  15. How Will You Be Evaluated? • 15% coursework • 2 courseworks, 7.5% each • At least one will involve significant programming • Z03 (DCNDS, SSE): Must score 40% mean on coursework • 85% final exam • 2.5 hours; rubric: 3 of 5 questions • 4030 (4th-years): must have 40% to pass • Overall: • 4030 (4th-years): must have 40% mean to pass • Z03 (DCNDS, SSE): must have 50% mean to pass

  16. Questionnaire • Please fill out completely and honestly! • Not assessed, kept confidential • Important to help me tailor lectures to class’ experience level

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