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
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?
1. Access to shared resources through
multiple “hard points”
2. Access to shared resources through
dynamic “soft points”
3. Ability to easily move in and out of a
network
4. Access to computing resources
regardless of physical location
Mobility “through the ages”
(1945-1990)
ENIAC
Computer Time Sharing System
ARPANET
PC’s
Laptops
Ethernet
Contemporary Mobility
(1990 – Present)
Data
– Example: Files
Computing
– Example: Specialized Processing
Code
– Example: Downloadable GUI
Presentation Emphasis
Mobility of Data
Two Examples
– Coda File System
– Bayou Anti-Entropy Protocol
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
Coda
Transparency (looks
like UNIX)
Scalability
– Push Functionality to
Clients
– Avoid System-wide
Rapid Change
Balance Availability
and Consistency
Bayou
Support for devices
w/ limited resources
High Availability
Application-specific
resolution of conflicts
Application
awareness of
underlying system
(NOT transparent)
Coda
General Comparison
Coda supports
disconnected
operations on
“cached” versions of
shared files
Upon reconnection,
clients and servers
“synch” their file
variants.
Bayou
The Bayou AEP
allows updates to
propagate between
participants sharing
replicas
Write operations are
stored and
propagated pair-wise
(even possibly
between clients*)
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)
* 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…
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/
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
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
Servers store data (replicas) in database
Clients read/write data
PDA are generally
only clients
Laptops often
operate in both roles
Achieving High Availability with
Significant Concurrency
Any user can read from or write to any
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”?
<timestamp, s_id>
Write
Updates
Dependency
Check
Merge
Proc.
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
<100,2>
<92, 1>
<95, 2>
<100,2>
<96, 3>
<92, 1>
<96, 3>
<96, 3>
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
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
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
Primary
Secondary
Secondary
Secondary
More Bayou “Light Reading”
Session Guarantees
Transportable Media Modifications
Write Log Truncation
Server creation/retirement
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)
Now Wait a Minute…
“one crucial assumption is that reordering of
concurrent updates, either conflicting or nonconflicting, will result in the same updates to the
database. This mandates ‘perfect’ conflictresolving methods, which seems hard to find for
a lot of applications.”3
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
“Agile Application-Aware Adaptation for
Mobility”, Satyanarayanan, et al
“Rover: A Toolkit for Mobile Information
Access”, Joseph, et al
References
1. http://www.dictionary.com
2. C. Alexander, “A Pattern Language”,
Oxford University Press, New York, NY,
1977, page 831
3. http://www.cs.berkeley.edu/~zf/cs262b/b
ayou.htm