Coarse-grained information flow control on hybrid clouds
Chien-An Lai, Asser Tantawi, et al.
CLOUD 2016
This paper presents distributed divergence control algorithms for epsilon serializability for both homogeneous and heterogeneous distributed databases. Epsilon serializability allows for more concurrency by permitting non-serializable interleavings of database operations among epsilon transactions. We first present a strict 2-phase locking divergence control algorithm and an optimistic divergence control algorithm for a homogeneous distributed database system, where the local orderings of all the sub-transactions of a distributed epsilon transaction are the same. In such an environment, the total inconsistency of a distributed epsilon transaction is simply the sum of those of all its sub-transactions. We then describe a divergence control algorithm for a heterogeneous distributed database system, where the local orderings of all the sub-transactions of a distributed epsilon transaction may not be the same and the total inconsistency of a distributed epsilon transaction may be greater than the sum of those of all its sub-transactions. As a result, in addition to executing a local divergence control algorithm in each site to maintain the local inconsistency, a global mechanism is needed to take into account the additional inconsistency © 1995 Kluwer Academic Publishers.
Chien-An Lai, Asser Tantawi, et al.
CLOUD 2016
Qi Zhang, Ling Liu, et al.
ICDCS 2018
Kun-Lung Wu, Philip S. Yu, et al.
IEEE Transactions on Knowledge and Data Engineering
Lei Yu, Qi Zhang, et al.
CogMI 2019