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Software as a service

About: Software as a service is a research topic. Over the lifetime, 8514 publications have been published within this topic receiving 136177 citations. The topic is also known as: Service as a Software Substitute & SaaSS.


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TL;DR: This survey investigates how cloud computing paradigm impacted the field of ML, and introduces the most prominent industrial and academic outcomes, such as Apache Mahout, GraphLab or Jubatus.
Abstract: Applying popular machine learning algorithms to large amounts of data raised new challenges for the ML practitioners. Traditional ML libraries does not support well processing of huge datasets, so that new approaches were needed. Parallelization using modern parallel computing frameworks, such as MapReduce, CUDA, or Dryad gained in popularity and acceptance, resulting in new ML libraries developed on top of these frameworks. We will briefly introduce the most prominent industrial and academic outcomes, such as Apache Mahout, GraphLab or Jubatus. We will investigate how cloud computing paradigm impacted the field of ML. First direction is of popular statistics tools and libraries (R system, Python) deployed in the cloud. A second line of products is augmenting existing tools with plugins that allow users to create a Hadoop cluster in the cloud and run jobs on it. Next on the list are libraries of distributed implementations for ML algorithms, and on-premise deployments of complex systems for data analytics and data mining. Last approach on the radar of this survey is ML as Software-as-a-Service, several BigData start-ups (and large companies as well) already opening their solutions to the market.

43 citations

Proceedings Article
21 Nov 2010
TL;DR: CloudMIG as mentioned in this paper is a model-based approach that supports SaaS providers to semi-automatically migrate existing enterprise software systems to scalable and resource-efficient PaaS and IaaS-based applications.
Abstract: The paper describes the model-based approach CloudMIG Cloud computing supplies software, platforms, and infrastructures as a service (SaaS, PaaS, and IaaS, respectively) over a network connection Cloud providers frequently offer the services according to the utility computing paradigm Therefore, cloud computing provides means for reducing over- and under-provisioning through enabling a highly flexible resource allocation Running an existing software system on a cloud computing basis usually involves extensive reengineering activities during the migration Current migration approaches suffer from several shortcomings For example, they are often limited to specific cloud environments or do not provide automated support for the alignment with a cloud environment We present our model-based approach CloudMIG which addresses these shortcomings It aims at supporting SaaS providers to semi-automatically migrate existing enterprise software systems to scalable and resource-efficient PaaS and IaaS-based applications

43 citations

Proceedings ArticleDOI
13 Sep 2011
TL;DR: A generic scheme to enable fine-grained data sharing over the cloud, which does not require key-redistribution and data re-encryption whatsoever and has a number of advantages over other similar proposals in the literature.
Abstract: Working in various service models ranging from SaaS, PaaS, to IaaS, cloud computing is a new revolution in IT, and could reshape the business model of how the IT industry works today. Storage services are a fundamental component of the cloud computing paradigm. By exploiting the storage services, users outsource their data to the cloud so as to enjoy the reduced upfront maintenance and capital costs. However, a security challenge associated with data outsourcing is how to prevent data abuses by the cloud. It has been commonly accepted that data encryption offers a good solution to this problem. With data encryption, an issue arises when the data owner who outsourced the data wants to revoke some data consumers' access privileges, which normally involves key re-distribution and data re-encryption. In this work, we propose a generic scheme to enable fine-grained data sharing over the cloud, which does not require key-redistribution and data re-encryption whatsoever. The main primitives we make use of are attribute-based/predicate encryption and proxy re-encryption, but our construction is not restricted to any specific scheme of its kind. Our scheme has a number of advantages over other similar proposals in the literature.

43 citations

Journal ArticleDOI
TL;DR: The intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-win logistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.
Abstract: Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer (SaaS), platform layer (PaaS) and infrastructure (IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-win logistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.

43 citations

Patent
03 May 2001
TL;DR: In this paper, the authors present a software platform that is for use in connection with an enterprise computing system having a plurality of back-end software applications, and the software platform includes a data modeling program allowing creation of a data model associated with at least one of the plurality of Back-end applications.
Abstract: Various methods for distributing, integrating, and hosting a software platform that may be used to extend an enterprise network to mobile devices are provided. A particular embodiment of the method includes distributing a software platform to a first enterprise and distributing the software platform to a second enterprise. The software platform is for use in connection with an enterprise computing system having a plurality of back-end software applications. The software platform includes a data modeling program allowing creation of a data model associated with at least one of the plurality of back-end applications. The software platform further includes a deployment feature allowing deployment of at least a portion of the data model to a plurality of mobile computing devices.

43 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202375
2022226
2021192
2020306
2019327
2018424