EEDC Distributed Systems

Execution Environments for Distributed Computing

Distributed Systems

EEDC

343

30

Master in Computer Architecture, Networks and Systems - CANS

Homework number: 1Group number: EEDC-30

Group members:

Javier Álvarez javicid@gmail.com

Francesc Lordan francesc.lordan@gmail.com

Roger Rafanell rogerrafanell@gmail.com

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Content

Distributed Systems

– Part 1: Definition

– Part 2: Evolution

– Part 3: Fields of application

– Part 4: Questions

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Execution Environments for Distributed Computing

Part 1

Definition

EEDC

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Master in Computer Architecture, Networks and Systems - CANS

4

Definition

“A distributed system is a set of autonomous computational resources,

communicated through a computer network, that cooperate to achieve a

common goal.”

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Key Concepts

Cooperation– Nodes work together to achieve a common goal.

Autonomous– Each node has a limited knowledge of the whole system.

Communication– Nodes communicate by passing messages.

Homogeneity/Heterogeneity– Many types of computers.

– Many network scopes (LAN/WAN).

– Many networks topologies.

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Advantages

Reliability– Fault tolerance mechanisms, replication of processes, …

Resource sharing– Many users interacting with the same resource at the same time.

Resource aggregation – computing power, disk space, network bandwidth, …

Scalability– Ease to modify the amount of computing resources.

Openness– Easy integration of a part of another system.

Price– No need to purchase resources if remote ones are used.

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Disadvantages

Security– Data, processes and computational resources are exposed

through the network.

Relies on network latencies– Message passing is slower than just reading from local memory.

Complexity– Access, configuration and programming.

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Execution Environments for Distributed Computing Part 2

Evolution and Architectures

EEDC

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30

Master in Computer Architecture, Networks and Systems - CANS

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Evolution

1951UNIVAC

Internet1995

Packet Switching&

First WAN1965

1969ARPANET

1973TCP/IP

ENIAC1945

First conferencein distributed computing

1982

Utility Computing

1961

1996Volunteer Computing

Cloud Computing2007

1964First Supercomputer

(CDC 6600)

MPI1992

P2P Systems1999

1998SOAP

GridComputing

1990

1991WWW

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Architectures

Master-worker– A master node orchestrates the execution of an application

among a set of workers.

Client-server– Simple clients contacts the server asking for data / process.

3-tier– A new node between the client and the server is added to the

previous architecture. This middle layer contents the complex logic to interpret the result obtained from the server. The client logic is simplified.

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Architectures

N-tier– 3-tier but with many levels. The request is forwarded through n-

layers and the response is treated by each one.

Tightly coupled– Resources that closely work together (Clusters).

Peer-to-Peer – There is no special machine. The responsibility is uniformly divided

through all the nodes.

Space based– Create the illusion of a single address-space even it is distributed.

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Execution Environments for Distributed Computing

Part 3

Fields of application

EEDC

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Master in Computer Architecture, Networks and Systems - CANS

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Fields of application

Everywhere!

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Applications

Computer science– Distributed Databases (Hbase, Cassandra, …)– Distributed file systems (GlusterFS, HDFS, Lustre, … )– Ad-hoc networks– Sensor networks– Mobile apps

Transport– Aeronautics– VANET: Vehicular ad-hoc networks

Entertainment: – Multiplayer Online Games– Gaming/Media-On-Demand

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Applications Science & Engineering

– Forecasting models– Simulators– Data Analysis

Medics– Electronic medical history– Remote exploration, therapy

Business– Business Intelligence– Accounting– Virtual shops

Public administration– Services based on OpenData

…

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Execution Environments for Distributed Computing

Part 4

Questions

EEDC

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Master in Computer Architecture, Networks and Systems - CANS

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Questions