5,802 research outputs found
CATS: linearizability and partition tolerance in scalable and self-organizing key-value stores
Distributed key-value stores provide scalable, fault-tolerant, and self-organizing
storage services, but fall short of guaranteeing linearizable consistency
in partially synchronous, lossy, partitionable, and dynamic networks, when data
is distributed and replicated automatically by the principle of consistent hashing.
This paper introduces consistent quorums as a solution for achieving atomic
consistency. We present the design and implementation of CATS, a distributed
key-value store which uses consistent quorums to guarantee linearizability and partition tolerance in such adverse and dynamic network conditions. CATS is
scalable, elastic, and self-organizing; key properties for modern cloud storage
middleware. Our system shows that consistency can be achieved with practical
performance and modest throughput overhead (5%) for read-intensive workloads
Atomic commitment in transactional DHTs
We investigate the problem of atomic commit in transactional database systems
built on top of Distributed Hash Tables. DHTs provide a decentralized way to
store and look up data. To solve the atomic commit problem we propose to
use an adaption of Paxos commit as a non-blocking algorithm. We exploit the
symmetric replication technique existing in the DKS DHT to determine which
nodes are necessary to execute the commit algorithm. By doing so we achieve a
lower number of communication rounds and a reduction of meta-data in contrast
to traditional Three-Phase-Commit protocols. We also show how the proposed
solution can cope with dynamism due to churn in DHTs. Our solution works
correctly relying only on an inaccurate failure detection of node failure which is
necessary for systems running over the Internet
Peer to Peer Information Retrieval: An Overview
Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom
Alpha Entanglement Codes: Practical Erasure Codes to Archive Data in Unreliable Environments
Data centres that use consumer-grade disks drives and distributed
peer-to-peer systems are unreliable environments to archive data without enough
redundancy. Most redundancy schemes are not completely effective for providing
high availability, durability and integrity in the long-term. We propose alpha
entanglement codes, a mechanism that creates a virtual layer of highly
interconnected storage devices to propagate redundant information across a
large scale storage system. Our motivation is to design flexible and practical
erasure codes with high fault-tolerance to improve data durability and
availability even in catastrophic scenarios. By flexible and practical, we mean
code settings that can be adapted to future requirements and practical
implementations with reasonable trade-offs between security, resource usage and
performance. The codes have three parameters. Alpha increases storage overhead
linearly but increases the possible paths to recover data exponentially. Two
other parameters increase fault-tolerance even further without the need of
additional storage. As a result, an entangled storage system can provide high
availability, durability and offer additional integrity: it is more difficult
to modify data undetectably. We evaluate how several redundancy schemes perform
in unreliable environments and show that alpha entanglement codes are flexible
and practical codes. Remarkably, they excel at code locality, hence, they
reduce repair costs and become less dependent on storage locations with poor
availability. Our solution outperforms Reed-Solomon codes in many disaster
recovery scenarios.Comment: The publication has 12 pages and 13 figures. This work was partially
supported by Swiss National Science Foundation SNSF Doc.Mobility 162014, 2018
48th Annual IEEE/IFIP International Conference on Dependable Systems and
Networks (DSN
Symmetric Replication for Structured Peer-to-Peer Systems
Structured peer-to-peer systems rely on replication as a basic means to provide fault-tolerance in presence of high churn. Most select replicas using either multiple hash functions, successor-lists, or leaf-sets. We show that all three alternatives have limitations. We present and provide full algorithmic speci¯cation for a generic replication scheme called symmetric replication which only needs O(1) message for every join and leave operation to maintain any replication degree. The scheme is applicable to all existing structured peer-to-peer systems, and can be implemented on-top of any DHT. The scheme has been implemented in our DKS system, and is used to do load-balancing, end-to-end fault-tolerance, and to increase the security by using distributed voting. We outline an extension to the scheme, implemented in DKS, which adds routing proximity to reduce latencies. The scheme is particularly suitable for use with erasure codes, as it can be used to fetch a random subset of
the replicas for decoding
On the Evaluation of RDF Distribution Algorithms Implemented over Apache Spark
Querying very large RDF data sets in an efficient manner requires a
sophisticated distribution strategy. Several innovative solutions have recently
been proposed for optimizing data distribution with predefined query workloads.
This paper presents an in-depth analysis and experimental comparison of five
representative and complementary distribution approaches. For achieving fair
experimental results, we are using Apache Spark as a common parallel computing
framework by rewriting the concerned algorithms using the Spark API. Spark
provides guarantees in terms of fault tolerance, high availability and
scalability which are essential in such systems. Our different implementations
aim to highlight the fundamental implementation-independent characteristics of
each approach in terms of data preparation, load balancing, data replication
and to some extent to query answering cost and performance. The presented
measures are obtained by testing each system on one synthetic and one
real-world data set over query workloads with differing characteristics and
different partitioning constraints.Comment: 16 pages, 3 figure
- …