  Ensuring data correctness over partitioned distributed database systems is a
classical problem. Classical solutions proposed to solve this problem are
mainly adopting locking or blocking techniques. These techniques are not
suitable for cloud environments as they produce terrible response times; due to
the long latency and faultiness of wide area network connections among cloud
datacenters. One way to improve performance is to restrict access of
users-bases to specific datacenters and avoid data sharing between datacenters.
However, conflicts might appear when data is replicated between datacenters;
nevertheless change propagation timeliness is not guaranteed. Such problems
created data uncertainty on cloud environments. Managing data uncertainty is
one of the main obstacles for supporting global distributed transactions on the
clouds. To overcome this problem, this paper proposes an quota-based approach
for managing data uncertainty on the clouds that guarantees global data
correctness without global locking or blocking. To decouple service developers
from the hassles of managing data uncertainty, we propose to use a new platform
service (i.e. Data Consistency as a Service (DCaaS)) to encapsulate the
proposed approach. DCaaS service also ensures SaaS services cloud portability,
as it works as a cloud adapter between SaaS service instances. Experiments show
that proposed approach realized by the DCaaS service provides much better
response time when compared with classical locking and blocking techniques.
