3 research outputs found
Benefits of Stabilization versus Rollback in Eventually Consistent Key-Value Stores
In this paper, we evaluate and compare the performance of two approaches,
namely self-stabilization and rollback, to handling consistency violation
faults (cvf) that occurred when a distributed program is executed on eventually
consistent key-value store. We observe that self-stabilization is usually
better than rollbacks in our experiments. Moreover, when we aggressively allow
more cvf in exchange of eliminating mechanisms for guaranteeing atomicity
requirements of actions, we observe the programs in our case studies achieve a
speedup between 2--15 times compared with the standard implementation. We also
analyze different factors that contribute to the results. Our results and
analysis are useful in helping a system designer choose proper design options
for their program
Using Weaker Consistency Models with Monitoring and Recovery for Improving Performance of Key-Value Stores
Consistency properties provided by most key-value stores can be classified
into sequential consistency and eventual consistency. The former is easier to
program with but suffers from lower performance whereas the latter suffers from
potential anomalies while providing higher performance. We focus on the problem
of what a designer should do if he/she has an algorithm that works correctly
with sequential consistency but is faced with an underlying key-value store
that provides a weaker consistency. We propose a detect-rollback based
approach: The designer identifies a correctness predicate, say , and
continues to run the protocol, as our system monitors . If is violated
(because of weaker consistency), the system rolls back and resumes the
computation at a state where holds.
We evaluate this approach with graph-based applications running on the
Voldemort key-value store. Our experiments with deployment on Amazon AWS EC2
instances shows that using eventual consistency with monitoring can provide a
-- increase in throughput when compared with sequential
consistency. We also observe that the overhead of the monitoring itself was low
(typically less than ) and the latency of detecting violations was small.
In particular, in a scenario designed to intentionally cause a large number of
violations, more than of violations were detected in less than 50
milliseconds in regional networks, and in less than 3 seconds in global
networks.
We find that for some applications, frequent rollback can cause the program
using eventual consistency to effectively \textit{stall}. We propose alternate
mechanisms for dealing with re-occurring rollbacks. Overall, for applications
considered in this paper, we find that even with rollback, eventual consistency
provides better performance than using sequential consistency.Comment: arXiv admin note: substantial text overlap with arXiv:1805.11453,
arXiv:1801.0731
A Distributed Algorithm for Computing Voronoi Diagram in the Unit Disk Graph Model
We study the problem of computing Voronoi diagrams distributedly for a set of nodes of a network modeled as a Unit Disk Graph (UDG). We present an algorithm to solve this problem efficiently, which has direct applications in wireless networks. Comparing with some existing algorithms, our algorithm correctly computes the complete Voronoi diagram and uses a significantly smaller number of transmissions. Furthermore, useful geometric structures such as the Delaunay triangulation and the convex hull can be obtained through our algorithm.