Distributed Computing
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Transcript of Distributed Computing
Distributed Computing
Rik Sarkar
Distributed Computing
•Old style: Use a computer for computation
Distributed Computing
•New style: Use many computers for computation
Examples:
•Computing clusters (data analysis and storage, hadoop etc)•Networks of sensors •Mobile systems
Why Study Distributed Computing?
Important Applications–Networks, Internet, power grids,
social networks, data mining….
Interesting Ideas–Algorithms, graphs, probability,
geometry, machine learning…
•The computers know only the edges, they can’t see the graph
Example: large network analysis
•The computers know only the edges, they can’t see the graph
•Problem: find the real shape of the graph.
Example: large network analysis
Spectral Analysis Algorithm
Network from the graph
Find the structure behind a network.
Use that to design better algorithms
Network from the graph
Many uses:
Routing in networks.
What are the important links?
What are the important web pages? (distributed spectral analysis is Google’s secret)
Social Networks
•Who are influential people or groups?•What are the important topics?•What causes communities to form?•How do epidemics spread?
Mobile networks
•Can we analyze the location data of people?•How do they move? •Where do they go?
Computation in Sensor Networks
•Process the sensor data•Find sums, averages, max, min, distribution etc.•Do computations using the sensors themselves •Use distributed algorithms•Has to be very efficient, very fast
Summary: Distributed Computing
•Important applications in many areas–Large scale data analysis, Sensing and understanding
the environment, Energy systems, Mobile systems, robotics…
•Interesting (fun) techniques–Algorithms, Graph Theory, Learning, Signal
processing…