Showing papers on "Database-centric architecture published in 2014"

Defining architecture components of the Big Data Ecosystem

Abstract: Big Data are becoming a new technology focus both in science and in industry and motivate technology shift to data centric architecture and operational models. There is a vital need to define the basic information/semantic models, architecture components and operational models that together comprise a so-called Big Data Ecosystem. This paper discusses a nature of Big Data that may originate from different scientific, industry and social activity domains and proposes improved Big Data definition that includes the following parts: Big Data properties (also called Big Data 5V: Volume, Velocity, Variety, Value and Veracity), data models and structures, data analytics, infrastructure and security. The paper discusses paradigm change from traditional host or service based to data centric architecture and operational models in Big Data. The Big Data Architecture Framework (BDAF) is proposed to address all aspects of the Big Data Ecosystem and includes the following components: Big Data Infrastructure, Big Data Analytics, Data structures and models, Big Data Lifecycle Management, Big Data Security. The paper analyses requirements to and provides suggestions how the mentioned above components can address the main Big Data challenges. The presented work intends to provide a consolidated view of the Big Data phenomena and related challenges to modern technologies, and initiate wide discussion.

Titan: a toolset that connects software architecture with quality analysis

Abstract: In this tool demo, we will illustrate our tool---Titan---that supports a new architecture model: design rule spaces (DRSpaces). We will show how Titan can capture both architecture and evolutionary structure and help to bridge the gap between architecture and defect prediction. We will demo how to use our toolset to capture hundreds of buggy files into just a few architecturally related groups, and to reveal architecture issues that contribute to the error-proneness and change-proneness of these groups. Our tool has been used to analyze dozens of large-scale industrial projects, and has demonstrated its ability to provide valuable direction on which parts of the architecture are problematic, and on why, when, and how to refactor. The video demo of Titan can be found at https://art.cs.drexel.edu/~lx52/titan.mp4

Modeling and Reusing Robotic Software Architectures: the HyperFlex toolchain

Abstract: During the last years robotic researchers have been able of developing extremely complex applications. The complexity of these applications is reflected by the variety of functionalities involved, which are provided by a significant number of components. Although the reuse of software components is becoming a best-practice, the reuse of reference architectures, which model sub-systems providing functionalities common to a great number of applications, is still uncommon. This paper provides two contributions to this topic: (a) a development process that defines how reference architectures can be exploited for building robotic applications, (b) the HyperFlex software toolchain, which has been developed for supporting the design and the reuse of reference architectures. The idea presented in this paper is simple yet powerful: instead of building complex applications by reusing single components, even more complex applications can be developed by reusing reference architectures of mature sub-systems.

Consolidating a Process for the Design, Representation, and Evaluation of Reference Architectures

Abstract: Reference architectures have emerged as a special type of software architecture that achieves well-recognized understanding of specific domains, promoting reuse of design expertise and facilitating the development, standardization, and evolution of software systems. Because of their advantages, several reference architectures have been proposed and have been also successfully used, including in the industry. However, the most of these architectures are still built using an ad-hoc approach, lacking of a systematization to their construction. If existing, these approaches could motivate and promote the building of new architectures and also support evolution of existing ones. In this scenario, the main contribution of this paper is to present the evolution of ProSA-RA, a process that systematizes the design, representation, and evaluation of reference architectures. ProSA-RA has been already applied in the establishment of reference architectures for different domains and this experience was used to evolve our process. In this paper, we illustrate an application of ProSA-RA in the robotics domain. Results achieved through the use of ProSA-RA have showed us that it is a viable, efficient process and, as a consequence, it could contribute to the reuse of knowledge in several applications domains, by promoting the establishment of new reference architectures.

PEARs: Privacy Enhancing ARchitectures

Abstract: This paper points out the importance of architecture in designing a privacy-by-design system. It provides an overview on how architectures are designed, analysed and evaluated, through quality attributes, tactics and architecture patterns. It then specifies a straw man architecture design methodology for privacy. The resulting PEAR (Privacy Enhancing ARchitecture) methodology is then illustrated through an Intelligent Transport systems (ITS) example application. The integration of the resulting methodology in a Privacy-by-Design process is then explained. Suggestions for future work that will lead to an agreed engineering practice are finally provided.

Modeling Space System Architectures with Graph Theory

Abstract: Current space system architecture modeling frameworks use a variety of methods to generate their architecture definitions and system models but are either too manual or too limited in scope to effectively explore the architecture-level design space exploration This paper outlines a method to mathematically model space system architectures using graph theory, which provides a simple mathematical framework that is flexible enough to model many different system architecture options, such as lunar, asteroid, and Mars missions Multiple lunar system architectures were considered in NASA’s Exploration System Architecture Study mission modes comparison These system architectures are modeled within this framework to demonstrate the ability to rapidly compare the performance of different system architectures within a single framework This capability is crucial in order to explore the system architecture-level design space and make informed decisions on the future of a human space exploration program

Agent Architecture: An Overviews

Abstract: Agent architecture has been one of the core components in building an agent application. Agent architecture is considered as the functional brain of an agent in making decision and reasoning to solve problem and achieving goals. This paper reviews some of the existing agent architectures such as logic-based architecture, reactive architecture, BDI architecture, hybrid architecture, cognitive architecture, and semantic architecture. The purpose of this study is to identify distinctive features of the different types of agent architectures and how they are implemented to solve real world problems.

Provenance as a Service: A Data-centric Approach for Real-Time Monitoring

Abstract: Provenance of electronic data is an important piece of the metadata of a data object. Making systems provenance-aware can greatly benefit all parties involved. This paper discusses the importance of data provenance and presents an open cloud architecture named CloudProv, a framework to integrate, model, and monitor the provenance data. Our elastic cloud architecture will provide an open APIs which allows independent organizations to develop applications that can share and integrate provenance data across internal and external organizational boundaries. We propose a method to model the collected provenance information in such a way that can be used for continuous compliance monitoring and for root cause analysis. We have implemented a prototype of our framework, and used it to verify how we can generate a service model for provenance data using a small, but interesting set of data. We present a design of our proposed framework and its components along with a prototype implementation.

Empirical resilience evaluation of an architecture-based self-adaptive software system

Abstract: Architecture-based self-adaptation is considered as a promising approach to drive down the development and operation costs of complex software systems operating in ever changing environments. However, there is still a lack of evidence supporting the arguments for the beneficial impact of architecture-based self-adaptation on resilience with respect to other customary approaches, such as embedded code-based adaptation. In this paper, we report on an empirical study about the impact on resilience of incorporating architecture-based self-adaptation in an industrial middleware used to collect data in highly populated networks of devices. To this end, we compare the results of resilience evaluation between the original version of the middleware, in which adaptation mechanisms are embedded at the code-level, and a modified version of that middleware in which the adaptation mechanisms are implemented using Rainbow, a framework for architecture-based self-adaptation. Our results show improved levels of resilience in architecture-based compared to embedded code-based self-adaptation.

A Modeling Framework for Software Architecture Specification and Validation

Abstract: Integrating robotic systems into our everyday life needs that we prove that they will not endanger people, i.e. that they will behave correctly with respect to some safety rules. In this paper, we propose a validation toolchain based on a Domain Specific Language. This DSL allows to model the software architecture of a robot using a component-based approach. From these models, we provide tools to generate deployable components, as well as a two-step validation phase. This validation first performs a real-time analysis of the component architecture, leading to an evaluation of the software architecture schedulability. Then we can check the validity of some behavioral property on the components.

An Incrementally Deployable Network Architecture to Support Both Data-Centric and Host-Centric Services

Abstract: Most Internet traffic is associated with applications where users are interested in the data and not in the source where the data resides. On the other hand, the current Internet architecture is host-centric rather than data-centric, and it is not practical to deploy a pure data-centric architecture overnight. This motivates an incrementally deployable network architecture that can efficiently support both data-centric and host-centric services. In this article we describe such an architecture called DCNA for the Internet. DCNA is based on the inclusion of a shim layer between the application layer and the transport layer along with appropriate interfaces to connect these layers. In addition to being data-centric and incrementally deployable, DCNA can also effectively support mobility and multi-homing.

A Cluster-Based Data-Centric Model for Network-Aware Task Scheduling in Distributed Systems

Abstract: Big Data processing architectures are now widely recognized as one of the most significant innovations in Computing in the last decade. Their enormous potential in collecting and processing huge volumes of data scattered throughout the Internet is opening the door to a new generation of fully distributed applications that, by leveraging the large amount of resources available on the network will be able to cope with very complex problems achieving performances never seen before. However, the Internet is known to have severe scalability limitations in moving very large quantities of data, and such limitations introduce the challenge of making efficient use of the computing and storage resources available on the network, in order to enable data-intensive applications to be executed effectively in such a complex distributed environment. This implies resource scheduling decisions which drive the execution of task towards the data by taking network load and capacity into consideration to maximize data access performance and reduce queueing and processing delays as possible. Accordingly, this work presents a data-centric meta-scheduling scheme for fully distributed Big Data processing architectures based on clustering techniques whose goal is aggregating tasks around storage repositories and driven by a new concept of "gravitational" attraction between the tasks and their data of interest. This scheme will benefit from heuristic criteria based on network awareness and advance resource reservation in order to suppress long delays in data transfer operations and result into an optimized use of data storage and runtime resources at the expense of a limited (polynomial) computational complexity.

Introduction of NDN with Comparison to Current Internet Architecture based on TCP/IP

Abstract: the years number of people using Internet has escalated. The primary motive of the Internet has been revised. To deal with this drastic change, network architecture has to be redesigned considering future trends. The future architecture of Internet can be developed only after scrutinizing various aspects of current Internet architecture. Thus study of strengths and weaknesses of existing architecture will guide the learners to build a robust future architecture of Internet. This paper represents comparative study of TCP/IP model of existing architecture and Name Data Networking approach of Content Centric Networking of proposed model. This paper discusses fundamental factors such as approaches to current and future architectural model, Packet formats and differences in security mechanisms of these models. once a video goes viral, it receives large number of requests from different parts of the world simultaneously. To be able to satisfy such high number of requests simultaneously, implementation of latest multicast algorithms is required. NDN architecture handles such situations effectively as it is multipoint to multipoint protocol unlike TCP/IP. Internet model of TCP/IP is based on the conversation between two machines. This conversation requires addresses of source and destination machine. Today"s internet model is not best suited for information dissemination. The proposed model of NDN is implemented using Content Centric Networking approach. In this architecture the content is named. The objective of NDN architecture is to efficiently handle the issues that current internet architecture faces. This future architecture promises better utilization of bandwidth, aims to improve throughput and decrease the network traffic generated during the transfer of popular web content. In this paper detail comparison of existing TCP/IP model and proposed NDN model is given. This paper will aid the reader to comprehend fundamental differences between current internet architecture and future internet architecture. This Paper represents a comparison of two architectures in a simplified manner. It includes basic functioning approach and architectural components of both the systems. It emphasizes on distinguishing factors between TCP/IP and NDN model. Packet formats and Security implementations are also discussed in this paper. By the end of this paper reader will have a clear understanding of how these architectures differ.

Architecture-Based Code Generation: From π-ADL Architecture Descriptions to Implementations in the Go Language

Abstract: Architecture description languages (ADLs) should consider both structural and runtime perspectives of software architectures, an important requirement for current software systems. However, most existing ADLs are disconnected from the runtime level, thus entailing architectural mismatches and inconsistencies between architecture and implementation. With the emergence of the new generation programming languages for large-scale, dynamic, and distributed systems, this problem becomes worse since most existing ADLs do not capture the features of this type of language. In this context, we investigate the generation of source code in the Go programming language from architecture descriptions in the π-ADL language as they are both based on the π-calculus process algebra. We define the correspondences between π-ADL and Go elements and present how architecture descriptions in π-ADL can be automatically translated to their respective implementations in Go through a real-world flood monitoring system.

Architecture Solutions to E-Learning Systems Using Service-Oriented Cloud Computing Reference Architecture

Abstract: E-learning systems are moving away from monolithic applications towards more open, flexible components, capable of interoperating with other learning components. In spite of the diversity of learning environments, there is a lack of uniformity regarding their basic functionalities. Thus, the establishment of core functionalities represents an issue to the development of learning environments. In a different but related perspective, reference architectures have emerged as an alternative for promoting reuse of design expertise and facilitating the development of E-learning systems. Reference architecture increases the scalability, flexibility and availability of e-learning systems. The objective of this paper is to provide an architecture solutions to personalized e-learning systems using Service-Oriented Cloud Computing Architecture (SOCCA). SOCCA proposes high level designs to better support multi-tenancy feature of cloud computing The proposed architecture is called namely SOCCAPES, is designed to support maximum scalability and high service levels through virtualization and an optimized management environment. It enables new levels of scalability while providing a very cost-effective modular solution.

Automatic Reference Architecture Conformance Checking for SOA-Based Software Systems

Abstract: Company-wide reference architectures are an important means for standardization and reuse. Standardization is enforced through reference architecture conformance checking. Manual conformance checking is too time- and resource-intensive to be performed continuously for the various systems that are part of a SOA. We present an approach for automatic reference architecture conformance checking of SOA-based software systems. Reference architectures are defined based on rules consisting of roles and of constraints on roles and role relationships. By mapping the roles to the elements of a software architecture representation, reference architecture specifications are reusable for different software systems. Through automating the whole checking process, including architecture extraction, role mapping, and rule evaluation, the approach can be applied continuously for the different systems that are part of a SOA. The approach has been developed and refined by applying it to a SOA in the banking domain. During its evolution from semi-automatic to a fully automatic approach it has also changed the way of how architecture information is provided as part of the system implementation in this domain.

A service-oriented reference architecture for mobile learning environments

Abstract: Even providing several benefits and facilities with regard to teaching and learning, the development of mobile learning environments present problems and challenges that must be investigated, especially with respect to the definition and adoption of architectural patterns. Indeed, most of these environments are built in an isolated way, having their own architectures and structures, which can negatively affect the capacity to standardization and support of architectural definition. Motivated by this scenario, in this paper we propose a service-oriented reference architecture for mobile learning environments. This architecture, named Ref-mLearning, aims at contributing to the development, reuse and interoperability of such environments, also allowing an increase in quality and cost reduction during their development. Ref-mLearning was developed according to a systematic process for the definition of reference architectures, and has been evaluated by means of a reference model for reference architectures. The preliminary results obtained suggest that Ref-mLearning is complete, presenting most of the relevant elements with respect to a reference architecture.

A General Framework for Architecture Composability

Abstract: Architectures depict design principles: paradigms that can be understood by all, allow thinking on a higher plane and avoiding low-level mistakes. They provide means for ensuring correctness by construction by enforcing global properties characterizing the coordination between components. An architecture can be considered as an operator A that, applied to a set of components \(\mathcal{B}\), builds a composite component \(A({\mathcal{B}})\) meeting a characteristic property Φ. Architecture composability is a basic and common problem faced by system designers. In this paper, we propose a formal and general framework for architecture composability based on an associative, commutative and idempotent architecture composition operator ‘⊕’. The main result is that if two architectures A 1 and A 2 enforce respectively safety properties Φ1 and Φ2, the architecture A 1 ⊕ A 2 enforces the property \(\Phi_1 \land \Phi_2\), that is both properties are preserved by architecture composition. We also establish preservation of liveness properties by architecture composition. The presented results are illustrated by a running example and a case study.

Experience on applying software architecture recovery to automotive embedded systems

Abstract: The importance and potential advantages with a comprehensive product architecture description are well described in the literature. However, developing such a description takes additional resources, and it is difficult to maintain consistency with evolving implementations. This paper presents an approach and industrial experience which is based on architecture recovery from source code at truck manufacturer Scania CV AB. The extracted representation of the architecture is presented in several views and verified on CAN signal level. Lessons learned are discussed.

Flexibility in Ecosystem Architectures

Abstract: Quality attributes are important to creating, understanding, and evaluating software architectures. The architectural attributes and challenges for ecosystem architectures are different from one-off systems. The study of those aspects that influence quality attributes in this new environment can help to understand these architectures. In previous work, we hypothesized that the architecture for an ecosystem should be extensible, scalable, and flexible and reported initial investigations into extensibility and scalability. In this paper, we report on our investigation into flexibility. We analyze various features that impact how to design flexible architectures. We highlight that flexibility for ecosystems is not only a technical issue, but a business issue as well. We classified features that affect flexibility into business and technical dimensions. We adapted a software system metric for flexibility to measure the flexibility of an ecosystem's architecture.

Architecting Software as a Service for Data Centric Cloud Applications

Abstract: Software as a service (SaaS) is a new software development and deployment paradigm over the cloud. It offers Information Technology services dynamically as "on-demand" basis. The related application data are stored in the data centers managed by the Cloud Service Providers. Many enterprises are facing a major research challenge due to the unavailability of generic cloud architecture for designing, developing and deploying of cloud services. In this paper a flexible architecture for SaaS has been proposed, specifically for data centric cloud applications which may have access to heterogeneous types of databases. The architecture is composed of several layers, which are interacting with each other through the dynamically selected access points of the corresponding layers interfaces. The paper also enlisted the crucial features for SaaS architectural model. Moreover, a detailed comparative study has been done among the proposed SaaS architectural framework and other existing similar proposals based on the listed features.

Privacy by Design: On the Conformance Between Protocols and Architectures

Abstract: In systems design, we generally distinguish the architecture and the protocol levels. In the context of privacy by design, in the first case, we talk about privacy architectures, which define the privacy goals and the main features of the system at high level. In the latter case, we consider the underlying concrete protocols and privacy enhancing technologies that implement the architectures. In this paper, we address the question that whether a given protocol conforms to a privacy architecture and provide the answer based on formal methods. We propose a process algebra variant to define protocols and reason about privacy properties, as well as a mapping procedure from protocols to architectures that are defined in a high-level architecture language.

Data centric framework for large-scale high-performance parallel computation

Abstract: Supercomputer architectures are being upgraded using different level of parallelism to improve computing performance. This makes it difficult for scientists to develop high performance code in a short time. From the viewpoint of productivity and software life cycle, a concise yet effective infrastructure is required to achieve parallel processing. In this paper, we propose a usable building block framework to build parallel applications on large-scale Cartesian data structures. The proposed framework is designed such that each process in a simulation cycle can easily access the generated data files with usable functions. This framework enables us to describe parallel applications with fewer lines of source code, and hence, it contributes to the productivity of the software. Further, this framework was considered for improving performance, and it was confirmed that the developed flow simulator based on this framework demonstrated considerably excellent weak scaling performance on the K computer.

Run-Time Monitoring-Based Evaluation and Communication Integrity Validation of Software Architectures

Abstract: Architecture descriptions greatly contribute to the understanding, evaluation and evolution of software but despite this, up-to-date software architecture views are rarely available. Typically only initial descriptions of the static view are created but during the development and evolution process the software drifts away from its description. Methods and corresponding tool support for reconstructing and evaluating the current architecture views have been developed and proposed, but they usually address the reconstruction of static and dynamic views separately. Especially the dynamic views are usually bloated with low-level information (e.g., Object interactions) making the understanding and evaluation of the behavior very intricate. To overcome this, we presented ARAMIS, a general architecture for building tool-based approaches that support the architecture-centric evolution and evaluation of software systems with a strong focus on their behavior. This work presents ARAMIS-CICE, an instantiation of ARAMIS. Its goal is to automatically test if the run-time interactions between architecture units match the architecture description. Furthermore, ARAMIS-CICE characterizes the intercepted behavior using two newly-defined architecture metrics. We present the fundamental concepts of ARAMIS-CICE: its meta-model, metrics and implementation. We then discuss the results of a two-folded evaluation. The evaluation shows very promising results.

Behavior Models for Software Architecture

Abstract: : Monterey Phoenix (MP) is an approach to formal software system architecture specification based on behavior models. Architecture modeling focuses not only on the activities and interactions within the system, but also on the interactions between the system and its environment, providing an abstraction for interaction specification. The behavior of the system is defined as a set of events (event trace) with two basic relations: precedence and inclusion. The structure of possible event traces is specified using event grammars and other constraints organized into schemas. The separation of the interaction description from the components behavior is an essential MP feature. The schema framework is amenable to stepwise architecture refinement, reuse, composition, visualization, and multiple view extraction. The approach yields a basis for executable architecture specification supporting early testing and verification, systematic use case generation, and performance estimates with automated tools.

Do architectural design decisions improve the understanding of software architecture? two controlled experiments

Abstract: Architectural design decision (ADD) and its design rationale, as a paradigm shift on documenting and enriching architecture design description, is supposed to facilitate the understanding of architecture and the reasoning behind the design rationale, which consequently improves the architecting process and gets better architecture design results. But the lack of empirical evaluation that supports this statement is one of the major reasons that prevent industrial practitioners from using ADDs in their daily architecting activities. In this paper, we conducted two controlled experiments, as a family of experiments, to investigate how presence of ADDs can improve the understanding of architecture. The main results of our experiments are: (i) using ADDs and their rationale in architecture documentation does not affect the time needed for completing architecture design tasks; (ii) one experiment and the family of experiments achieved a significantly better understanding of architecture design when using ADDs; and (iii) with regard to the correctness of architecture understanding, more experienced participants benefited more from ADDs in comparison with less experienced ones.

Providing Transaction Class-Based QoS in In-Memory Data Grids via Machine Learning

Abstract: Elastic architectures and the "pay-as-you-go" resource pricing model offered by many cloud infrastructure providers may seem the right choice for companies dealing with data centric applications characterized by high variable workload. In such a context, in-memory transactional data grids have demonstrated to be particularly suited for exploiting advantages provided by elastic computing platforms, mainly thanks to their ability to be dynamically (re-)sized and tuned. Anyway, when specific QoS requirements have to be met, this kind of architectures have revealed to be complex to be managed by humans. Particularly, their management is a very complex task without the stand of mechanisms supporting run-time automatic sizing/tuning of the data platform and the underlying (virtual) hardware resources provided by the cloud. In this paper, we present a neural network-based architecture where the system is constantly and automatically re-configured, particularly in terms of computing resources, in order to achieve transaction class-based QoS while minimizing costs of the infrastructure. We also present some results showing the effectiveness of our architecture, which has been evaluated on top of Future Grid IaaS Cloud using Red Hat Infinispan in-memory data grid and the TPC-C benchmark.