38,183 research outputs found
Optimistic Parallel State-Machine Replication
State-machine replication, a fundamental approach to fault tolerance,
requires replicas to execute commands deterministically, which usually results
in sequential execution of commands. Sequential execution limits performance
and underuses servers, which are increasingly parallel (i.e., multicore). To
narrow the gap between state-machine replication requirements and the
characteristics of modern servers, researchers have recently come up with
alternative execution models. This paper surveys existing approaches to
parallel state-machine replication and proposes a novel optimistic protocol
that inherits the scalable features of previous techniques. Using a replicated
B+-tree service, we demonstrate in the paper that our protocol outperforms the
most efficient techniques by a factor of 2.4 times
Development of Grid e-Infrastructure in South-Eastern Europe
Over the period of 6 years and three phases, the SEE-GRID programme has
established a strong regional human network in the area of distributed
scientific computing and has set up a powerful regional Grid infrastructure. It
attracted a number of user communities and applications from diverse fields
from countries throughout the South-Eastern Europe. From the infrastructure
point view, the first project phase has established a pilot Grid infrastructure
with more than 20 resource centers in 11 countries. During the subsequent two
phases of the project, the infrastructure has grown to currently 55 resource
centers with more than 6600 CPUs and 750 TBs of disk storage, distributed in 16
participating countries. Inclusion of new resource centers to the existing
infrastructure, as well as a support to new user communities, has demanded
setup of regionally distributed core services, development of new monitoring
and operational tools, and close collaboration of all partner institution in
managing such a complex infrastructure. In this paper we give an overview of
the development and current status of SEE-GRID regional infrastructure and
describe its transition to the NGI-based Grid model in EGI, with the strong SEE
regional collaboration.Comment: 22 pages, 12 figures, 4 table
Parallel Deferred Update Replication
Deferred update replication (DUR) is an established approach to implementing
highly efficient and available storage. While the throughput of read-only
transactions scales linearly with the number of deployed replicas in DUR, the
throughput of update transactions experiences limited improvements as replicas
are added. This paper presents Parallel Deferred Update Replication (P-DUR), a
variation of classical DUR that scales both read-only and update transactions
with the number of cores available in a replica. In addition to introducing the
new approach, we describe its full implementation and compare its performance
to classical DUR and to Berkeley DB, a well-known standalone database
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
Low latency via redundancy
Low latency is critical for interactive networked applications. But while we
know how to scale systems to increase capacity, reducing latency --- especially
the tail of the latency distribution --- can be much more difficult. In this
paper, we argue that the use of redundancy is an effective way to convert extra
capacity into reduced latency. By initiating redundant operations across
diverse resources and using the first result which completes, redundancy
improves a system's latency even under exceptional conditions. We study the
tradeoff with added system utilization, characterizing the situations in which
replicating all tasks reduces mean latency. We then demonstrate empirically
that replicating all operations can result in significant mean and tail latency
reduction in real-world systems including DNS queries, database servers, and
packet forwarding within networks
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