8,572 research outputs found
Scalable service-oriented replication with flexible consistency guarantee in the cloud
Replication techniques are widely applied in and for cloud to improve scalability and availability. In such context, the well-understood problem is how to guarantee consistency amongst different replicas and govern the trade-off between consistency and scalability requirements. Such requirements are often related to specific services and can vary considerably in the cloud. However, a major drawback of existing service-oriented replication approaches is that they only allow either restricted consistency or none at all. Consequently, service-oriented systems based on such replication techniques may violate consistency requirements or not scale well. In this paper, we present a Scalable Service Oriented Replication (SSOR) solution, a middleware that is capable of satisfying applications’ consistency requirements when replicating cloud-based services. We introduce new formalism for describing services in service-oriented replication. We propose the notion of consistency regions and relevant service oriented requirements policies, by which trading between consistency and scalability requirements can be handled within regions. We solve the associated sub-problem of atomic broadcasting by introducing a Multi-fixed Sequencers Protocol (MSP), which is a requirements aware variation of the traditional fixed sequencer approach. We also present a Region-based Election Protocol (REP) that elastically balances the workload amongst sequencers. Finally, we experimentally evaluate our approach under different loads, to show that the proposed approach achieves better scalability with more flexible consistency constraints when compared with the state-of-the-art replication technique
A comparison between google cloud service and icloud
© 2019 IEEE. The availability of high speed networks and low cost storage devices and computer in addition to the adoption of Service-Oriented-Architecture has opened the door to Cloud Storage Services by many providers. During the recent couple of years, more companies are moving towards cloud storage due to the many reasons such as: scalable on demand disk storage space, backup and data replication and the ability to share and access data from anywhere and anytime. The main objective of the paper is to compare different kinds of Cloud storage service providers. It starts by offering a brief introduction to cloud storage followed by an outline of the general history of cloud services and then moves on to the specific history of two major cloud services: iCloud and Google cloud platform. Furthermore, the various features of the two cloud services are explored and a comparison is made between them
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed
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