Centralized vs. Decentralized Design for Internet Applications

Adriana Iamnitchi

Department of Computer Science

The University of Chicago

I

04/18/23

TWIST 2000

Internet Applications

Components that build the Internet itself (DNS …)

Tools that connect the user to Internet resources (browsers, applets, CGIs, ...)

Services that can be accessed through Internet (e-commerce, e-banking, newspapers, e-libraries, …)

Applications that run on a collection of Internet-connected resources (SETI@home, …)Tools that create new environments over the Internet (middleware services)

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Internet-Connected Resources

Unreliable communication

Unreliable resources

Highly heterogeneous environment

Potentially very large number of resources

Potentially highly variable number of resources

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Centralized or Decentralized?

1. Applications

2. Middleware services

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Internet-Connected Resources

Unreliable communication

Unreliable resources Fault-tolerance mechanisms

Highly heterogeneous environment Asynchronous algorithms

Potentially very large number of resources

Potentially highly variable number of resources Scalability

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Application Design: Decentralized!

What about:

Distributed management control?

Fault tolerance in distributed, asynchronous systems?

Termination detection?

Communication costs?

Security?

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Experience with MetaNEOS

Solving very large optimization problems on metacomputing platforms

Branch-and-bound search algorithms: Search for optimal solution Successive decomposition of the original problem Elimination of unpromising subproblems based on

the best known solution

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Fully decentralized B&B: Solution

Process management: group membership based on epidemic communicationFault-tolerance: tree-based encoding of the problem space. Report completed problems Unsolved problems detected/restored based on

completed problems Price: redundant work

Termination detection: tree contraction Dynamic load balancing

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Decentralized B&B: Performance

Processors Execution time (h)

B&B time Contraction time

Communication (MB/h/p)

10 7.93 98.1% 0.3% 1.0

30 2.91 90.4% 5.2% 1.4

50 2.00 81.2% 11.7% 2.3

70 1.37 87.3% 2.3% 3.1

100 1.04 84.4% 1.1% 4.5

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Decentralized B&B: Fault Tolerance

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Decentralized B&B: Fault Tolerance

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Experience with MetaNEOS

Decentralized design is wonderful

Meantime, the centralized implementation produces results, because: Centralized code already exists (master-worker) Available resources: hundreds resources

working simultaneously (Condor testbed) Centralized code still efficient on relatively

small collections of resources

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Centralized or Decentralized?

1. Applications

2. Middleware services

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Middleware Services for Computational Grids

Computational Grids: hardware and software infrastructure that provides access to computational capabilities.Middleware services: responsible for application performance Information Services Service Location Services (Resource Discovery) Resource Management Security Fault tolerance/detection

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Information Service & Resource Discovery

Information Service Resources (networks, computers, applications, …) Users

Resource Discovery: “Give me n resources with attribute X” Input: set of resource attributes Output: set of resources Attributes: hardware characteristics, current load,

network connection, existent/available software, data, etc.

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Resource Discovery: Requirements

Scalable Increasing number of resources Increasing number of users

Reliable

Flexible (heterogeneity support) Heterogeneity:

Administrative level (policies) Technical level (hardware and software)

Support for changing environment

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Resource Discovery: Requirements

Efficient

Accurate

Secure

No global hierarchy Politically difficult for wide area (impossible?) Hierarchical structures are resistant to change

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Globus

Toolkit that builds computational grids

Components: Metacomputing Directory Service Heartbeat Monitor Grid Security Infrastructure Globus Resource Allocation Manager Global Access to Secondary Storage Nexus …

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Globus’ MDS – Step 1

C=US, o=Globus, o=ANL, ou=MCS

C=US, o=Globus, o=USC, ou=ISI

C=US, o=Globus, o=UC, ou=CS

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Globus’ MDS: Step 2

C=US, o=Globus, o=UC, ou=CS

C=US, o=Globus, o=ANL, ou=MCS

C=US, o=Globus, o=USC, ou=ISI

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Globus’ MDS: Step 3

Organizational Server

Organizational Server

Organizational Server

o=Grid, dc=mcs, dc=anl, dc=gov

o=Grid, dc=isi, dc=edu

o=Grid, dc=cs, dc=uchicago, dc=edu

Index Server A1

Index Server A2

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Decentralized Information Service

More difficult than the centralized design: Resource discovery based on attributes:

Rich set of queries to support Compound queries Static and dynamic data Access policies

Necessary

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Conclusions

Applications running on collections of Internet-connected resources: may be centralized or decentralized.

Middleware services must be decentralized.