UNIT-I

CSE 380 211/14/00

UNIT-IDistributed Systems

ECS-701Lecture Note

NEERAJ KUMAR

3

What is a Distributed System? Tanenbaum and van Renesse: A distributed system

is one that looks to its users like an ordinary, centralized, system but runs on multiple independent CPUs

Symptoms? Shroeder: Multiple, independent processing units Processors communicate via a hardware

interconnect Processing unit failures are independent Manage resource sharing State is shared among processors

Distributed Systems

4

Design Issues

Scaling Communication Coordination Transparency Naming Load sharing

Consistency Failures Security Heterogeneity Mobility

Distributed Systems, cont.

CSE 380 511/14/00

Advantages of Distributed Systems over Centralized Systems

• Economics: a collection of microprocessors offer a better price/performance than mainframes. Low price/performance ratio: cost effective way to increase computing power.

• Speed: a distributed system may have more total computing power than a mainframe. Ex. 10,000 CPU chips, each running at 50 MIPS. Not possible to build 500,000 MIPS single processor since it would require 0.002 nsec instruction cycle. Enhanced performance through load distributing.

• Inherent distribution: Some applications are inherently distributed. Ex. a supermarket chain.• Reliability: If one machine crashes, the system as a whole can still survive. Higher availability

and improved reliability.• Incremental growth: Computing power can be added in small increments. Modular

expandability• Another deriving force: the existence of large number of personal computers, the need for

people to collaborate and share information.

CSE 380 611/14/00

Advantages of Distributed Systems over Independent PCs

– Data sharing: allow many users to access to a common data base

– Resource Sharing: expensive peripherals like color printers– Communication: enhance human-to-human

communication, e.g., email, chat– Flexibility: spread the workload over the available

machines

CSE 380 711/14/00

Disadvantages of Distributed Systems

– Software: difficult to develop software for distributed systems

– Network: saturation, lossy transmissions– Security: easy access also applies to secrete data

Algorithms

• One processor– Reliable (no faults)– No communication

• Sequential: – One step at a time

• Complexity:– Step complexity

• Examples:– Sorting (Quicksort, Mergesort,

Heapsort)– Searching (Binary search)– Matrix mult. (Strassen’s)– Primality testing

Distributed kdAlgorithms Many processors

– Faulty (crash, byzantine, etc.)– Communication over network

Concurrent: – One step at a time

Complexity:– Message complexity– Latency analysis

Examples:– Leader election– Consensus (Agreement)– Mutual exclusion (Dining

Philosophers)– Atomic objects