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Showing papers on "Software as a service published in 2016"


Patent
23 Mar 2016
TL;DR: In this paper, a model-driven architecture and derivative IoT SaaS applications are described, including a data services component to extract, transform, and load aggregate data into a multi-dimensional data store; implement a type layer over a plurality of data stores.
Abstract: Systems, methods, and devices for a cyberphysical (IoT) software application development platform based upon a model driven architecture and derivative IoT SaaS applications are disclosed herein. The system may include a time-series data component to receive time-series data from time-series data sources. The system may include a relational data component to receive relational data from relational data sources. The system may include a persistence component to store the time-series data in a key-value store and store the relational data in a relational database. The system may include a data services component to extract, transform, and load aggregate data into a multi-dimensional data store; implement a type layer over a plurality of data stores comprising the key-value store, the relational database, and the multi-dimensional data store. The data services component may include definitions for a plurality of types based on the plurality of data stores.

349 citations


Journal ArticleDOI
TL;DR: The concept of hierarchical NSaaS is introduced, helping operators to offer customized end-to-end cellular networks as a service and enabling operators to build network slices for vertical industries more agilely.
Abstract: With the blossoming of network functions virtualization and software-defined networks, networks are becoming more and more agile with features like resilience, programmability, and open interfaces, which help operators to launch a network or service with more flexibility and shorter time to market. Recently, the concept of network slicing has been proposed to facilitate the building of a dedicated and customized logical network with virtualized resources. In this article, we introduce the concept of hierarchical NSaaS, helping operators to offer customized end-to-end cellular networks as a service. Moreover, the service orchestration and service level agreement mapping for quality assurance are introduced to illustrate the architecture of service management across different levels of service models. Finally, we illustrate the process of network slicing as a service within operators by typical examples. With network slicing as a service, we believe that the supporting system will transform itself to a production system by merging the operation and business domains, and enabling operators to build network slices for vertical industries more agilely.

223 citations


Proceedings ArticleDOI
14 Jun 2016
TL;DR: The paper highlights some of the key features of Snowflake: extreme elasticity and availability, semi-structured and schema-less data, time travel, and end-to-end security.
Abstract: We live in the golden age of distributed computing. Public cloud platforms now offer virtually unlimited compute and storage resources on demand. At the same time, the Software-as-a-Service (SaaS) model brings enterprise-class systems to users who previously could not afford such systems due to their cost and complexity. Alas, traditional data warehousing systems are struggling to fit into this new environment. For one thing, they have been designed for fixed resources and are thus unable to leverage the cloud's elasticity. For another thing, their dependence on complex ETL pipelines and physical tuning is at odds with the flexibility and freshness requirements of the cloud's new types of semi-structured data and rapidly evolving workloads. We decided a fundamental redesign was in order. Our mission was to build an enterprise-ready data warehousing solution for the cloud. The result is the Snowflake Elastic Data Warehouse, or "Snowflake" for short. Snowflake is a multi-tenant, transactional, secure, highly scalable and elastic system with full SQL support and built-in extensions for semi-structured and schema-less data. The system is offered as a pay-as-you-go service in the Amazon cloud. Users upload their data to the cloud and can immediately manage and query it using familiar tools and interfaces. Implementation began in late 2012 and Snowflake has been generally available since June 2015. Today, Snowflake is used in production by a growing number of small and large organizations alike. The system runs several million queries per day over multiple petabytes of data. In this paper, we describe the design of Snowflake and its novel multi-cluster, shared-data architecture. The paper highlights some of the key features of Snowflake: extreme elasticity and availability, semi-structured and schema-less data, time travel, and end-to-end security. It concludes with lessons learned and an outlook on ongoing work.

201 citations


Proceedings ArticleDOI
14 May 2016
TL;DR: Five distinct working styles of data scientists are identified: Insight Providers, who work with engineers to collect the data needed to inform decisions that managers make; Modeling Specialists, who use their machine learning expertise to build predictive models; Platform Builders, who create data platforms, balancing both engineering and data analysis concerns; and Team Leaders, who run teams of data Scientists and spread best practices.
Abstract: Creating and running software produces large amounts of raw data about the development process and the customer usage, which can be turned into actionable insight with the help of skilled data scientists. Unfortunately, data scientists with the analytical and software engineering skills to analyze these large data sets have been hard to come by; only recently have software companies started to develop competencies in software-oriented data analytics. To understand this emerging role, we interviewed data scientists across several product groups at Microsoft. In this paper, we describe their education and training background, their missions in software engineering contexts, and the type of problems on which they work. We identify five distinct working styles of data scientists: (1) Insight Providers, who work with engineers to collect the data needed to inform decisions that managers make; (2) Modeling Specialists, who use their machine learning expertise to build predictive models; (3) Platform Builders, who create data platforms, balancing both engineering and data analysis concerns; (4) Polymaths, who do all data science activities themselves; and (5) Team Leaders, who run teams of data scientists and spread best practices. We further describe a set of strategies that they employ to increase the impact and actionability of their work.

190 citations


Journal ArticleDOI
TL;DR: This research work presents taxonomy of cloud security attacks and potential mitigation strategies with the aim of providing an in-depth understanding of security requirements in the cloud environment and highlights the importance of intrusion detection and prevention as a service.

167 citations


Journal ArticleDOI
TL;DR: The authors of this article have endeavored to develop software tools to serve the clinical research community with a stand-alone executable, hybrid local computation model for today's modern architecture of cloud services, which they call MRICloud.
Abstract: Image analysis tools for brain magnetic resonance imaging (MRI) have become increasingly important for computer-aided diagnosis that involves large amounts of medical image data. The authors of this article have endeavored to develop software tools to serve the clinical research community, starting with a stand-alone executable, hybrid local computation model for today's modern architecture of cloud services, which they call MRICloud. MRICloud provides a high-throughput neuroinformatics platform for automated brain MRI segmentation and analytical tools for quantification via distributed remote computation and Web-based user interfaces. There are several key, inherent advantages to a cloud-based software as a service--in particular, how it improves the efficiency of software implementation, upgrades, and maintenance. The client-server model is also ideal for high-performance computing, allowing for distribution of computational servers across the world. This article introduces the basic functions and utilities of MRICloud, its developmental history and future perspectives, its infrastructures, and the benefits of this cloud service framework.

129 citations


Journal ArticleDOI
TL;DR: It is demonstrated that the proposed cloud performance models are applicable to evaluate PaaS, SaaS and hybrid clouds as well and found that auto-scaling is easy to implement but tends to over provision the resources.
Abstract: In this paper, we present generic cloud performance models for evaluating Iaas, PaaS, SaaS, and mashup or hybrid clouds. We test clouds with real-life benchmark programs and propose some new performance metrics. Our benchmark experiments are conducted mainly on IaaS cloud platforms over scale-out and scale-up workloads. Cloud benchmarking results are analyzed with the efficiency, elasticity, QoS, productivity, and scalability of cloud performance. Five cloud benchmarks were tested on Amazon IaaS EC2 cloud: namely YCSB, CloudSuite, HiBench, BenchClouds, and TPC-W. To satisfy production services, the choice of scale-up or scale-out solutions should be made primarily by the workload patterns and resources utilization rates required. Scaling-out machine instances have much lower overhead than those experienced in scale-up experiments. However, scaling up is found more cost-effective in sustaining heavier workload. The cloud productivity is greatly attributed to system elasticity, efficiency, QoS and scalability. We find that auto-scaling is easy to implement but tends to over provision the resources. Lower resource utilization rate may result from auto-scaling, compared with using scale-out or scale-up strategies. We also demonstrate that the proposed cloud performance models are applicable to evaluate PaaS, SaaS and hybrid clouds as well.

128 citations


Journal ArticleDOI
TL;DR: It is found that the programmers had limited knowledge of energy efficiency, lacked knowledge of the best practices to reduce software energy consumption, and were often unsure about how software consumes energy.
Abstract: Traditionally, programmers received a range of training on programming languages and methodologies, but they rarely receive training on software energy consumption. Yet, the popularity of mobile devices and cloud computing requires increased awareness of software energy consumption. On mobile devices, battery life often limits computation. Under the demands of cloud computing, datacenters struggle to reduce energy consumption through virtualization and datacenter-infrastructure-management systems. Efficient software energy consumption is increasingly becoming an important nonfunctional requirement for programmers. However, are programmers knowledgeable enough about software energy consumption? Do they base their implementation decision on popular beliefs? Researchers surveyed more than 100 programmers regarding their knowledge of software energy consumption. They found that the programmers had limited knowledge of energy efficiency, lacked knowledge of the best practices to reduce software energy consumption, and were often unsure about how software consumes energy. These results highlight the need for better training and education on energy consumption and efficiency.

117 citations


Journal ArticleDOI
01 Jun 2016
TL;DR: This paper classifies the solutions, maps them to requirements from a case study and identifies gaps and integration requirements, resulting in the currently most complete management suite.
Abstract: Docker provides a good basis to run composite applications in the cloud, especially if those are not cloud-aware, or cloud-native. However, Docker concentrates on managing containers on one host, but SaaS providers need a container management solution for multiple hosts. Therefore, a number of tools emerged that claim to solve the problem. This paper classifies the solutions, maps them to requirements from a case study and identifies gaps and integration requirements. We close some of these gaps with our own integration components and tool enhancements, resulting in the currently most complete management suite.

111 citations


Journal ArticleDOI
TL;DR: Software Defined Cloud (SDCloud) is introduced, a novel software defined cloud management framework that integrates different software define cloud components to handle complexities associated with cloud computing systems.

101 citations


Proceedings ArticleDOI
05 Jan 2016
TL;DR: The contribution of this paper is to introduce the concept of DevOps adoption in the embedded systems domain and then to identify key challenges for the Dev Ops adoption.
Abstract: DevOps is a predominant phenomenon in the web domain. Its two core principles emphasize collaboration between software development and operations, and the use of agile principles to manage deployment environments and their configurations. DevOps techniques, such as collaboration and behaviour-driven monitoring, have been used by web companies to facilitate continuous deployment of new functionality to customers. The techniques may also offer opportunities for continuous product improvement when adopted in the embedded systems domain. However, certain characteristics of embedded software development present obstacles for DevOps adoption, and as yet, there is no empirical evidence of its adoption in the embedded systems domain. In this study, we present the challenges for DevOps adoption in embedded systems using a multiple-case study approach with four companies. The contribution of this paper is to introduce the concept of DevOps adoption in the embedded systems domain and then to identify key challenges for the DevOps adoption.

Journal ArticleDOI
TL;DR: This paper presents a new cloud model called SLAaaS - SLA?aware Service, which considers QoS levels and SLA as first class citizens of cloud-based services and presents a general control-theoretic approach for managing cloud service SLA.

Journal ArticleDOI
TL;DR: This study investigated the influence of organizational factors that influenced Indonesian companies in their decision to adopt software as a service (SaaS) and identified three patterns: Top management support is an enabler for SaaS adoption; small to medium-sized enterprises (SMEs) are more likely to adopt SAAS than large companies; and organizational readiness is not an enabilizer.

Journal ArticleDOI
TL;DR: The benefits of reinforcement-learning-based techniques for resource provisioning in the vehicular cloud are shown and the learning techniques can perceive long-term benefits and are ideal for minimizing the overhead of resource Provisioning for vehicular clouds.
Abstract: This article presents a concise view of vehicular clouds that incorporates various vehicular cloud models that have been proposed to date. Essentially, they all extend the traditional cloud and its utility computing functionalities across the entities in the vehicular ad hoc network. These entities include fixed roadside units, onboard units embedded in the vehicle, and personal smart devices of drivers and passengers. Cumulatively, these entities yield abundant processing, storage, sensing, and communication resources. However, vehicular clouds require novel resource provisioning techniques that can address the intrinsic challenges of dynamic demands for the resources and stringent QoS requirements. In this article, we show the benefits of reinforcement-learning-based techniques for resource provisioning in the vehicular cloud. The learning techniques can perceive long-term benefits and are ideal for minimizing the overhead of resource provisioning for vehicular clouds.

Journal ArticleDOI
TL;DR: A theoretical model is proposed that refines prior literature on absorptive capacity and organisational ambidexterity in the process of business model change owing to the emergence of a disruptive innovation and provides in‐depth insights on the technological trajectory of enterprise resource‐planning software switching from on‐premise to on‐demand software services.
Abstract: The increasing popularity of Software as a Service has strongly affected the established business model of on-premise enterprise software. Software as a Service has distinctive characteristics of disruptive innovations that typically create several difficulties for incumbent firms, in particular with regard to adapting business models. To date, however, little empirical understanding exists regarding the dynamics of business model change - a topic of special importance to the highly dynamic software industry, which is characterised by rapid and regular emergence of disruptive innovations. As disruptive innovations require gathering distant knowledge and experimenting with new ideas, this study addresses theoretical gaps regarding the role of absorptive capacity and organisational ambidexterity in the process of business model change owing to the emergence of a disruptive innovation. Drawing on evidence from multiple case studies of six incumbent vendors of enterprise resource-planning software and informed by a thorough review of related secondary data, we investigate the pace and path of incumbents' business model adaptations. We propose a theoretical model that refines prior literature on absorptive capacity and organisational ambidexterity, particularly with regard to the process of business model change. This study identifies further technological factors that determine how and why incumbents change business models. In addition, our study provides in-depth insights on the technological trajectory of enterprise resource-planning software switching from on-premise to on-demand software services. © 2016 Blackwell Publishing Ltd

Journal ArticleDOI
TL;DR: A novel framework is designed for the Cloud to manage the realtime IoT data and scientific non-IoT data and in order to demonstrate the services in Cloud, real experimental result of implementing Docker container for virtualization is introduced to provide Software as a Service (SaaS) in a hybrid cloud environment.

Patent
15 Apr 2016
TL;DR: In this paper, a cloud-based services exchange (or "cloud exchange") for interconnecting multiple cloud service providers with multiple Cloud service customers is described, which may enable cloud customers to bypass the public Internet to directly connect to cloud services providers so as to improve performance, reduce costs, increase the security and privacy of the connections, and leverage cloud computing for additional applications.
Abstract: In general, a cloud-based services exchange (or “cloud exchange”) for interconnecting multiple cloud service providers with multiple cloud service customers is described. The cloud exchange may enable cloud customers to bypass the public Internet to directly connect to cloud services providers so as to improve performance, reduce costs, increase the security and privacy of the connections, and leverage cloud computing for additional applications. In this way, enterprises, network carriers, and SaaS customers, for instance, can integrate cloud services with their internal applications as if such services are part of or otherwise directly coupled to their own data center network.

Proceedings ArticleDOI
14 Mar 2016
TL;DR: This work explores how the use of GitHub influences the R ecosystem, both for the distribution of R packages and for inter-repository package dependency management.
Abstract: When developing software packages in a software ecosystem, an important and well-known challenge is how to deal with dependencies to other packages. In presence of multiple package repositories, dependency management tends to become even more problematic. For the R ecosystem of statistical computing, dependency management is currently insufficient to deal with multiple package versions and inter-repository package dependencies. We explore how the use of GitHub influences the R ecosystem, both for the distribution of R packages and for inter-repository package dependency management. We also discuss how these problems could be addressed.


Journal ArticleDOI
TL;DR: This study presents a framework for software gamified in e-banking, taking a users' groups and a qualitative research approach, to check the users' design preferences in five cases of banking software gamification (Futebank, Dreams, Galaxy, Olympics, and Warrants).

Journal ArticleDOI
TL;DR: Experimental results show that the proposed heuristics can reduce 24 percent of the service renting cost than the compared algorithms on the test benchmarks at most for non-shareable services.
Abstract: In XaaS clouds, resources as services (e.g., infrastructure, platform and software as a service) are sold to applications such as scientific and big data analysis workflows. Candidate services with various configurations (CPU type, memory size, number of machines and so on) for the same task may have different execution time and cost. Further, some services are priced rented by intervals that be shared among tasks of the same workflow to save service rental cost. Establishing a task-mode (service) mapping (to get a balance between time and cost) and tabling tasks on rented service instances are crucial for minimizing the client-oriented cost to rent services for the whole workflow. In this paper, a multiple complete critical-path based heuristic (CPIS) is developed for the task-mode mapping problem. A list based heuristic (LHCM) concerning the task processing cost and task-slot matching is developed for tabling tasks on service instances based on the result of task-mode mapping. Then, the effectiveness of the proposed CPIS is compared with that of the previously proposed CPIL, the existing state-of-the-art heuristics including PCP, SC-PCP (an extension to PCP), DET, and CPLEX. The effectiveness of the proposed LHCM is evaluated with its use with different task-mode mapping algorithms. Experimental results show that the proposed heuristics can reduce 24 percent of the service renting cost than the compared algorithms on the test benchmarks at most for non-shareable services. In addition, half of the service renting cost could be saved when LHCM is applied to consolidate tasks on rented service instances.

Patent
24 Jun 2016
TL;DR: In this paper, the authors present a system for allowing parents to view and track smart phone activities of their children, which can include one or more child software modules installed on each child's smart phone.
Abstract: Devices, systems, and methods for allowing parents to view and track smart phone activities of their children can include one or more child software modules. The module can be installed on each child's smart phone. The module can access and extract data from or about more than one of the smart phone's other software applications, including at least two of the following: a texting application, a social media application, an image application that facilitates transmission or reception of images, and a web browser application. The module can further send the extracted data to an analysis server. The module can also monitor location data. Moreover, the system can include an analysis server that can identify potentially harmful language, images, and websites. Further, the system can include a parent portal. The parent portal can receive results from the analysis server.

Proceedings ArticleDOI
01 Aug 2016
TL;DR: The paper will go in to details of data protection methods and approaches used throughout the world to ensure maximum data protection by reducing risks and threats to provide insight on data security aspects for Data-in-Transit and Data-at-Rest.
Abstract: This paper discusses the security of data in cloud computing. It is a study of data in the cloud and aspects related to it concerning security. The paper will go in to details of data protection methods and approaches used throughout the world to ensure maximum data protection by reducing risks and threats. Availability of data in the cloud is beneficial for many applications but it poses risks by exposing data to applications which might already have security loopholes in them. Similarly, use of virtualization for cloud computing might risk data when a guest OS is run over a hypervisor without knowing the reliability of the guest OS which might have a security loophole in it. The paper will also provide an insight on data security aspects for Data-in-Transit and Data-at-Rest. The study is based on all the levels of SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service).

Journal ArticleDOI
TL;DR: The purpose of this paper is to compare and discuss several models and pricing schemes from different Cloud Computing providers.
Abstract: Cloud Computing is one of the technologies with rapid development in recent years where there is increasing interest in industry and academia. This technology enables many services and resources for end users. With the rise of cloud services number of companies that offer various services in cloud infrastructure is increased, thus creating a competition on prices in the global market. Cloud Computing providers offer more services to their clients ranging from infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), storage as a service (STaaS), security as a service (SECaaS), test environment as a service (TEaaS). The purpose of providers is to maximize revenue by their price schemes, while the main goal of customers is to have quality of services (QoS) for a reasonable price. The purpose of this paper is to compare and discuss several models and pricing schemes from different Cloud Computing providers.

Journal ArticleDOI
TL;DR: This paper introduces the work using a modeling framework – ROAR (Resource Optimization, Allocation and Recommendation System) to simplify, optimize, and automate cloud resource allocation decisions to meet QoS goals for web applications, including complex multi-tier application distributed in different server groups.

Journal ArticleDOI
TL;DR: In this paper, the authors provide a large-scale analysis of the relation between size and productivity of software development teams, showing that the magnitude of the decrease in productivity is likely to be related to the growth dynamics of co-editing networks which can be interpreted as a first-order approximation of coordination requirements.
Abstract: Complex software development projects rely on the contribution of teams of developers, who are required to collaborate and coordinate their efforts. The productivity of such development teams, i.e., how their size is related to the produced output, is an important consideration for project and schedule management as well as for cost estimation. The majority of studies in empirical software engineering suggest that - due to coordination overhead - teams of collaborating developers become less productive as they grow in size. This phenomenon is commonly paraphrased as Brooks' law of software project management, which states that "adding manpower to a software project makes it later". Outside software engineering, the non-additive scaling of productivity in teams is often referred to as the Ringelmann effect, which is studied extensively in social psychology and organizational theory. Conversely, a recent study suggested that in Open Source Software (OSS) projects, the productivity of developers increases as the team grows in size. Attributing it to collective synergetic effects, this surprising finding was linked to the Aristotelian quote that "the whole is more than the sum of its parts". Using a data set of 58 OSS projects with more than 580,000 commits contributed by more than 30,000 developers, in this article we provide a large-scale analysis of the relation between size and productivity of software development teams. Our findings confirm the negative relation between team size and productivity previously suggested by empirical software engineering research, thus providing quantitative evidence for the presence of a strong Ringelmann effect. Using fine-grained data on the association between developers and source code files, we investigate possible explanations for the observed relations between team size and productivity. In particular, we take a network perspective on developer-code associations in software development teams and show that the magnitude of the decrease in productivity is likely to be related to the growth dynamics of co-editing networks which can be interpreted as a first-order approximation of coordination requirements.

Journal ArticleDOI
TL;DR: This paper summarizes the challenges that the Software Engineering for Services and Applications (SE4SA) cluster is considering as relevant and proposes a strategy to consolidate the software engineering discipline.

Journal ArticleDOI
TL;DR: This paper proposes an autonomic resource provisioning approach that is based on the concept of the control monitor-analyze-plan-execute (MAPE) loop, and designs a resource Provisioning framework for cloud environments.
Abstract: Recently, there has been a significant increase in the use of cloud-based services that are offered in software as a service (SaaS) models by SaaS providers, and irregular access of different users to these cloud services leads to fluctuations in the demand workload. It is difficult to determine the suitable amount of resources required to run cloud services in response to the varying workloads, and this may lead to undesirable states of over-provisioning and under-provisioning. In this paper, we address improvements to resource provisioning for cloud services by proposing an autonomic resource provisioning approach that is based on the concept of the control monitor-analyze-plan-execute (MAPE) loop, and we design a resource provisioning framework for cloud environments. The experimental results show that the proposed approach reduces the total cost by up to 35 %, the number of service level agreement (SLA) violations by up to 40 %, and increases the resource utilization by up to 25 % compared with the other approaches.

Journal ArticleDOI
TL;DR: It is stated that not only a large fraction of the value creation goes to the platform provider but also that the software service ecosystem can collapse, if no mutually beneficial pricing of services is implemented.

Journal ArticleDOI
TL;DR: It is argued that SDN and NFV, together with cloud and edge-fog computing, can be seen as different facets of a systemic transformation of telecommunications and ICT, called softwarization.
Abstract: This article argues that SDN and NFV, together with cloud and edge-fog computing, can be seen as different facets of a systemic transformation of telecommunications and ICT, called softwarization. The first impact will be at the edge of current telecommunications infrastructures, which are becoming powerful network and service platforms. The edge operating system (EOS) software architecture is proposed as the means to get there. In fact, the main feature of EOS is to bring several service domains, such as cloud robotics, Internet of Things, and Tactile Internet, into convergence at the edge. The development of EOS leverages available open source software. A use case is described to validate the EOS with a proof-of-concept.