(Georgia Institute of Technology, 2009)
Wu, Qinyi; Pu, Calton
In real-time collaborative editing systems, users create a
shared document by issuing insert, delete, and undo operations
on their local replica anytime and anywhere. Data
consistency issues arise due to concurrent editing conflicts.
Traditional consistency models put restrictions on editing
operations updating different portions of a shared document,
which is unnecessary for many editing scenarios, and
cause their view synchronization strategies to become less
efficient. To address these problems, we propose a new data
consistency model that preserves convergence and synchronizes
editing operations only when they access overlapped
or contiguous characters. Our view synchronization strategy
is implemented by a novel data structure–partial persistent
sequence. A partial persistent sequence is an ordered set of
items indexed by persistent and unique position identifiers.
It captures data dependencies of editing operations and encodes
them in a way that they can be correctly executed on
any document replica. As a result, a simple and efficient
view synchronization strategy can be implemented.
(Georgia Institute of Technology, 2009)
Wu, Qinyi; Pu, Calton; Irani, Danesh
Wiki applications are becoming increasingly important for
knowledge sharing between large numbers of users. To prevent
against vandalism and recover from destructive edits,
wiki applications need to maintain the revision histories of
all documents. Due to the large amounts of data and traffic,
a Wiki application needs to store the data economically
and retrieve documents efficiently. Current Wiki Data
Management Systems (WDMS) make a trade-off between
storage requirement and access time for document update
and retrieval. We introduce a new data management system,
Cosmos, to balance this trade-off. To compare Cosmos
with the other WDMSs, we use a 68GB data sample
from English Wikipedia. Our experiments show that Cosmos
uses one-fifth of the disk space when compared to MediaWiki
(Wikipedia’s backend) and performs faster than other
WDMSs at document retrieval.