Mobility in distributed computing
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Mobility in Distributed Computing. With Special Emphasis on Data Mobility. Computing Culture. Culture - The predominating attitudes and behavior that characterize the functioning of a group or organization. 1 Computing Culture MUST align with social culture to be effective.

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Mobility in Distributed Computing

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Mobility in distributed computing

Mobility in Distributed Computing

With Special Emphasis on Data Mobility


Computing culture

Computing Culture

Culture - The predominating attitudes and behavior that characterize the functioning of a group or organization.1

Computing Culture MUST align with social culture to be effective


Culture and mobility

Culture and Mobility

“People want to be together; but at the same time they want the opportunity for some small amount of privacy, without giving up community”2


What is mobility

What is Mobility?

  • Access to shared resources through multiple “hard points”

  • Access to shared resources through dynamic “soft points”

  • Ability to easily move in and out of a network

  • Access to computing resources regardless of physical location


Mobility through the ages 1945 1990

Mobility “through the ages” (1945-1990)

  • ENIAC

  • Computer Time Sharing System

  • ARPANET

  • PC’s

  • Laptops

  • Ethernet


Contemporary mobility 1990 present

Contemporary Mobility(1990 – Present)

  • Data

    • Example: Files

  • Computing

    • Example: Specialized Processing

  • Code

    • Example: Downloadable GUI


Presentation emphasis

Presentation Emphasis

  • Mobility of Data

  • Two Examples

    • Coda File System

    • Bayou Anti-Entropy Protocol


Challenges of data mobility

Challenges of Data Mobility

  • Designing the following characteristics of data mobility is not trivial:

    • Outside Availability

    • Outside Semantics

    • Consistency

    • Concurrency

  • Even different systems may have different mobility goals (For example….)


Goal comparison

Transparency (looks like UNIX)

Scalability

Push Functionality to Clients

Avoid System-wide Rapid Change

Balance Availability and Consistency

Support for devices w/ limited resources

High Availability

Application-specific resolution of conflicts

Application awareness of underlying system (NOT transparent)

Goal Comparison

Coda

Bayou


General comparison

Coda supports disconnected operations on “cached” versions of shared files

Upon reconnection, clients and servers “synch” their file variants.

The Bayou AEP allows updates to propagate between participants sharing replicas

Write operations are stored and propagated pair-wise (even possibly between clients*)

General Comparison

Coda

Bayou


Critical common concern

Critical Common Concern

  • Optimistic vrs Pessimistic Replication

    • Pessimistic avoids conflicts by restriction

    • Optimistic detects and resolves conflicts if, and when, necessary

  • It should be noted that data mobility all but requires optimistic replication


Coda disconnected operation simplified view

Coda Disconnected Operation(simplified view)

* User explicitly specifies files he/she

wants available offline

* Coda makes a best-effort attempt

to keep those files in cache

* On disconnect, user can access files

in cache normally

* On reconnect, client and server

update one another and resolve

any conflicts (write-write only)


And now for something completely different

And Now, For Something Completely Different…

  • The Bayou Anti-Entropy Protocol attempts to solve a more complex problem

  • Not accidentally, the Bayou AEP is also more complex than Coda

  • It doesn’t help that the paper “Flexible Update Propagation for Weakly Consistent Replication” is hard to understand


Helpful bayou papers http www2 parc com csl projects bayou

Helpful Bayou Papers http://www2.parc.com/csl/projects/bayou/

  • The Bayou Architecture: Support for Data Sharing among Mobile Users

  • Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System

  • Dealing with Tentative Data Values in Disconnected Work Groups


Let s start at the very beginning

Let’s Start at the Very Beginning

  • Bayou is designed to run in a mobile computing environment with less than ideal network connectivity

  • Bayou assumes that mobile users want to share their data despite intermittent network connectivity


Supporting devices with limited resources

Supporting Devices with Limited Resources

Serversstore data (replicas) in database

Clientsread/write data

PDA are generally

only clients

Laptops often

operate in both roles


Achieving high availability with significant concurrency

Achieving High Availability with Significant Concurrency

  • Any user can read from or write toany copy of the “database”

  • Because Bayou assumes that partitions can and do happen, it offers no guarantee of timeliness of write propagation

  • This means that replicated databases are only weakly consistent


What is a write

What is a “write”?

Write

<timestamp, s_id>

Merge

Proc.

Dependency

Check

Updates


What is the database

What is the Database?

D0 = Null

D1 = W1(D0)

D2 = W2(D1)

:

Dn = Wn(Dn-1)

Where Di represents the data after

Applying write W0 – Wi in order


Getting the right write propagation

Getting the Right Write Propagation

<96, 3>

<100,2>

<92, 1>

<92, 1>

<95, 2>

<95, 2>

<96, 3>

<100,2>

<100,2>

<96, 3>


A few notes

A Few Notes…

  • The only requirement for timestamps is that they be monotonically increasing at each server

  • If timestamps are based on rt-clocks, keeping server’s clocks close is best

  • Bayou servers maintain a logical clocks to timestamp new writes (initially synched with rt-clock, then updated during AEP)


Stabilizing aep

Stabilizing AEP

  • A write is stable when it’s order will never change

  • Bayou uses “primary commit protocol”

  • “Primary” server commits a write

  • Tentative writes always come after committed writes

  • NOTE: This is somewhat arbitrary


Bayou s propagation of committed writes

Bayou’s Propagation of Committed Writes

  • Since committed writes are totally ordered by their CSNs, the highest CSN represents the committed portion of the write-log

  • In an update, committed writes are transmitted (or a commitment notice sent) before uncommitted writes


Stabilizing images

Stabilizing Images

Primary

Secondary

Secondary

Secondary


More bayou light reading

More Bayou “Light Reading”

  • Session Guarantees

  • Transportable Media Modifications

  • Write Log Truncation

  • Server creation/retirement


Mobility in distributed computing

But…

  • Throughout our discussion of Bayou, we’ve covered conflict resolution only lightly

  • How does Bayou conflict resolution work?

  • How does it compare to Coda conflict resolution?


Conflict resolution

In Coda, conflicts are assumed to be small. When they occur, the user is expected to resolve the conflict (once).

In Bayou, each write is assumed to have its own conflict resolution suite (the dependency check and merge procedure)

Conflict Resolution


Now wait a minute

Now Wait a Minute…

“one crucial assumption is that reordering of concurrent updates, either conflicting or non-conflicting, will result in the same updates to the database. This mandates ‘perfect’ conflict-resolving methods, which seems hard to find for a lot of applications.”3


Unanswered questions

Unanswered Questions

  • Do these solutions solve the “real” problem? Or, are they solutions looking for a problem? Would YOU use either one?

  • Do they solve problems best left to applications? (The end-to-end question)


Beyond data mobility

Beyond Data Mobility

  • “Agile Application-Aware Adaptation for Mobility”, Satyanarayanan, et al

  • “Rover: A Toolkit for Mobile Information Access”, Joseph, et al


References

References

  • http://www.dictionary.com

  • C. Alexander, “A Pattern Language”, Oxford University Press, New York, NY, 1977, page 831

  • http://www.cs.berkeley.edu/~zf/cs262b/bayou.htm


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