In groupware systems a broad range of requirements for user coordination and data consistency need to be supported. The notions of event causality and user awareness are central in such requirements. Traditional transaction models supported in general purpose database management systems with strong consistency guarantees have been found to be unsuitable for groupware systems. Weaker models for data consistency are needed for user awareness and cooperative activities. Objects in the shared workspace need to be managed with different consistency guarantees. Towards such requirements, we examine here the applicability of a distributed transaction management model which supports multilevel consistency. The consistency levels supported in this model include serializable transactions for strong consistency and weaker consistency models such as Causal Snapshot Isolation (CSI), CSI with commutative updates, and CSI with asynchronous updates. We review the coordination and data consistency requirements in groupware systems. We show using two examples how replicated shared data in distributed groupware systems can be managed with multiple consistency levels using this model.
|Original language||English (US)|
|Title of host publication||Proceedings - 2016 IEEE 2nd International Conference on Collaboration and Internet Computing, IEEE CIC 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||10|
|State||Published - Jan 6 2017|
|Event||2nd IEEE International Conference on Collaboration and Internet Computing, IEEE CIC 2016 - Pittsburgh, United States|
Duration: Nov 1 2016 → Nov 3 2016
|Name||Proceedings - 2016 IEEE 2nd International Conference on Collaboration and Internet Computing, IEEE CIC 2016|
|Other||2nd IEEE International Conference on Collaboration and Internet Computing, IEEE CIC 2016|
|Period||11/1/16 → 11/3/16|
Bibliographical noteFunding Information:
This work was supported by the National Science Foundation award 1319333. Computing resources for this work were provided by the Minnesota Supercomputing Institute.
© 2016 IEEE.