2,981 research outputs found
BaseFs - Basically Acailable, Soft State, Eventually Consistent Filesystem for Cluster Management
A peer-to-peer distributed filesystem for community cloud management. https://github.com/glic3rinu/basef
Exploring heterogeneity of unreliable machines for p2p backup
P2P architecture is a viable option for enterprise backup. In contrast to
dedicated backup servers, nowadays a standard solution, making backups directly
on organization's workstations should be cheaper (as existing hardware is
used), more efficient (as there is no single bottleneck server) and more
reliable (as the machines are geographically dispersed).
We present the architecture of a p2p backup system that uses pairwise
replication contracts between a data owner and a replicator. In contrast to
standard p2p storage systems using directly a DHT, the contracts allow our
system to optimize replicas' placement depending on a specific optimization
strategy, and so to take advantage of the heterogeneity of the machines and the
network. Such optimization is particularly appealing in the context of backup:
replicas can be geographically dispersed, the load sent over the network can be
minimized, or the optimization goal can be to minimize the backup/restore time.
However, managing the contracts, keeping them consistent and adjusting them in
response to dynamically changing environment is challenging.
We built a scientific prototype and ran the experiments on 150 workstations
in the university's computer laboratories and, separately, on 50 PlanetLab
nodes. We found out that the main factor affecting the quality of the system is
the availability of the machines. Yet, our main conclusion is that it is
possible to build an efficient and reliable backup system on highly unreliable
machines (our computers had just 13% average availability)
State of The Art and Hot Aspects in Cloud Data Storage Security
Along with the evolution of cloud computing and cloud storage towards matu-
rity, researchers have analyzed an increasing range of cloud computing security
aspects, data security being an important topic in this area. In this paper, we
examine the state of the art in cloud storage security through an overview of
selected peer reviewed publications. We address the question of defining cloud
storage security and its different aspects, as well as enumerate the main vec-
tors of attack on cloud storage. The reviewed papers present techniques for key
management and controlled disclosure of encrypted data in cloud storage, while
novel ideas regarding secure operations on encrypted data and methods for pro-
tection of data in fully virtualized environments provide a glimpse of the toolbox
available for securing cloud storage. Finally, new challenges such as emergent
government regulation call for solutions to problems that did not receive enough
attention in earlier stages of cloud computing, such as for example geographical
location of data. The methods presented in the papers selected for this review
represent only a small fraction of the wide research effort within cloud storage
security. Nevertheless, they serve as an indication of the diversity of problems
that are being addressed
Fault Tolerant Adaptive Parallel and Distributed Simulation through Functional Replication
This paper presents FT-GAIA, a software-based fault-tolerant parallel and
distributed simulation middleware. FT-GAIA has being designed to reliably
handle Parallel And Distributed Simulation (PADS) models, which are needed to
properly simulate and analyze complex systems arising in any kind of scientific
or engineering field. PADS takes advantage of multiple execution units run in
multicore processors, cluster of workstations or HPC systems. However, large
computing systems, such as HPC systems that include hundreds of thousands of
computing nodes, have to handle frequent failures of some components. To cope
with this issue, FT-GAIA transparently replicates simulation entities and
distributes them on multiple execution nodes. This allows the simulation to
tolerate crash-failures of computing nodes. Moreover, FT-GAIA offers some
protection against Byzantine failures, since interaction messages among the
simulated entities are replicated as well, so that the receiving entity can
identify and discard corrupted messages. Results from an analytical model and
from an experimental evaluation show that FT-GAIA provides a high degree of
fault tolerance, at the cost of a moderate increase in the computational load
of the execution units.Comment: arXiv admin note: substantial text overlap with arXiv:1606.0731
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