Generic Architectural Framework Research Articles

Perencanaan Arsitektur Enterprise Menggunakan Framework TOGAF (The Open Group Architecture Framework)

PKU Muhammadiyah Mayong Hospital is a health institution that focuses on excellent service to patients. The increasing need for service functions is a driving factor for the application of information technology at PKU Muhammadiyah Mayong Hospital. To support the alignment of the application of information systems with the needs of the hospital, a paradigm called enterprise architecture is needed. This study aims to analyze the planning of enterprise architecture using the Open Group Architecture Framework (TOGAF) framework with the Architecture Development Method (ADM) method at PKU Muhammadiyah Mayong Hospital. TOGAF is a generic architectural framework designed to be used in various types and sizes of organizations. ADM is a method that contains a set of activities used in modeling the development of enterprise architecture. This research is expected to be useful for PKU Muhammadiyah Mayong Hospital to integrate business processes with information technology. At each stage of ADM what is done is the process of identifying problems, analyzing problems and solutions to these problems. In this study the stages used only up to the information system architecture. The results of this study are proposed business architecture, data architecture and application architecture.

A Trust Management System for the Nigerian Cyber-health Community

Trust is a basic requirement for the acceptance and adoption of new services related to health care, and therefore, vital in ensuring that the integrity of shared patient information among multi-care providers is preserved and that no one has tampered with it. The cyber-health community in Nigeria is in its infant stage with health care systems and services being mostly fragmented, disjointed, and heterogeneous with strong local autonomy and distributed among several healthcare givers platforms. There is the need for a trust management structure for guaranteed privacy and confidentiality to mitigate vulnerabilities to privacy thefts. In this paper, we developed an efficient Trust Management System that hybridized Real-Time Integrity Check (RTIC) and Dynamic Trust Negotiation (DTN) premised on the Confidentiality, Integrity, and Availability (CIA) model of information security. This was achieved through the design and implementation of an indigenous and generic architectural framework and model for a secured Trust Management System with the use of the advanced encryption standard (AES-256) algorithm for securing health records during transmission. The developed system achieved Reliabity score, Accuracy and Availability of 0.97, 91.30% and 96.52% respectively.

Adaptation and application of the IEEE 2413-2019 standard security mechanisms to IoMT systems

Healthcare information systems are evolving from traditional centralised architectures towards highly-mobile distributed environments within the connected health context. The IoMT paradigm is at the forefront of this technological revolution underlying the development of communication infrastructures connecting smart medical devices, healthcare information systems and services. The IEEE 2413 standard, a promising general architectural framework for the design and implementation of IoT systems, has recently been announced. This standard proposes a general description for different types of domains, including healthcare, but it does not contain an extension developed for the IoMT systems domain. This paper presents a first approach to adapt the IEEE 2413 standard to the design of IoMT systems from a security perspective, considering the most relevant aspects of the standard for the construction of this type of systems. The application to an IoMT system for monitoring patients with chronic obstructive pulmonary disease is presented as a use case.

An architectural framework for information integration using machine learning approaches for smart city security profiling

In the past few decades, the whole world has been badly affected by terrorism and other law-and-order situations. The newspapers have been covering terrorism and other law-and-order issues with relevant details. However, to the best of our knowledge, there is no existing information system that is capable of accumulating and analyzing these events to help in devising strategies to avoid and minimize such incidents in future. This research aims to provide a generic architectural framework to semi-automatically accumulate law-and-order-related news through different news portals and classify them using machine learning approaches. The proposed architectural framework discusses all the important components that include data ingestion, preprocessor, reporting and visualization, and pattern recognition. The information extractor and news classifier have been implemented, whereby the classification sub-component employs widely used text classifiers for a news data set comprising almost 5000 news manually compiled for this purpose. The results reveal that both support vector machine and multinomial Naïve Bayes classifiers exhibit almost 90% accuracy. Finally, a generic method for calculating security profile of a city or a region has been developed, which is augmented by visualization and reporting components that maps this information onto maps using geographical information system.

A secure n-secret based client authentication protocol for 802.11 WLANs

Authentication has strong impact on the overall security model of every information system. Various authentication techniques are available for restricting the access of unauthorized users to the enterprise scale networks. IEEE 802.1X defines a secure and reliable authentication framework for 802.11 WLANs, where Extensible Authentication Protocol (EAP) provides the base to this architecture. EAP is a generic architectural framework which supports extensibility by incorporating the new and improved authentication schemes, which are based on different types of credentials. Currently there exist a number of EAP and Non-EAP methods with varying level of security and complexity. In this work, we have designed a new n-secret based authentication scheme referred here as Personal Dialogue Based Authentication, for the client authentication to the network. It is a Transport Layer Security (TLS) protected authentication protocol, which will be executed inside the secure TLS tunnel for providing the privacy and credential security to the wireless client. The developed authentication protocol has a reasonable set of features like; strong security, user privacy, simplicity and extensibility. For the formal analysis of the protocol we have used SPAN–AVISAP model checker on Ubuntu platform for validating the realization of the specified security goals. The experimental results obtained by simulation performed with the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool shows that our protocol is efficient and secured.

Open RAN Deployment Using Advanced Radio Link Manager Framework to Support Mission Critical Services in 5G

Next generation networks or 5G will be “network of networks” that can support ultra-reliable and low latency communication, high data rate, huge connectivity and high security. Network transformation stirring towards virtualized Radio Access Network (v-RAN) and intelligent resource management are foreseen as key solutions to realise such varied 5G requirements. Effective Radio Resource Management (RRM) is crucial for Mission Critical (MC) services to underpin communication between smartphone, massive machines and tiny sensor devices. The paper explores pioneering research related to architecture and intelligent RRM that helps Service Providers (SPs) to design reference framework of an advanced Radio Link Manager (RLM) enabled by Machine Learning (ML). One example optimization for commercial network/Long Term Evolution (LTE) and some preliminary results are analysed to understand the reference framework. The paper addresses the general reference architecture framework of advanced Radio Link Manager to support Mission Critical services in 5G. The paper also discusses about the ongoing standardisation activities and open source initiatives in 5G RAN.

Reverse Cooperatively Routed Wi-Fi Direct in the Advent of 5G Driven Designs

In this article, the instantiation of the logic behind the so-called “Multi-Connect” mode of Wi-Fi Direct is advocated for and prescribed in order to make it possible to increase, if not multiply, the data throughput attainable by a given P2P Device thanks to traffic aggregation. In general, the described extension to the existing standard, defined by the Wi-Fi Peer-to-Peer (P2P) Technical Specification, enables the reversal of the logical roles of a P2P Group Owner (P2P GO) and its respective P2P Clients, while ensuring that the general architectural framework of Wi-Fi Direct should remain unchanged for backward compatibility reasons. This is achieved with the aid of a number of specifically tailored modifications including: new P2P Attribute allocation, extended Group Owner determination, modified P2P State Machine operation, enhanced Concurrent and Non-Concurrent operation, as well as expanded Reverse Operation Logic definition. The concept is illustrated with and verified through the analysis of cumulative virtual channel capacity and, therefore, the expected data throughput gain.

Models and Practices in Urban Data Science at Scale

Abstract Cities can be observed through a broad set of sensing technologies, spanning from physical sensors in the streets, to socio-economic reports, to other kinds of sources that are able to represent the behaviour of the citizens and visitors, such as mobile phone records, social media posts, and other digital traces. In this paper, we propose a conceptual framework for putting at use this variety of Big Data sources, with a unified approach that applies spatial and temporal analysis over heterogeneous streams of data. We define spatial analysis based on conceptual grids (made of cells) over the city space, and then we study: the time series of signals both at grid and cell level; the correlation across signals and across cells; the prediction of city dynamics based on multiple signals; and the identifications of anomalies based on the difference between the observed dynamics and their prediction. To implement this model we propose a general architectural framework that uses Big Data technologies (such as HDFS, YARN, HIVE, PIG, Cascalog, Spark, Spark SQL, Spark Streaming and SparkR) and can be deployed in different configurations based on different needs. By taking an inherent data science approach to the problem we are able to address at scale: technical problems such as heterogeneous time and space granularity of the data, as well as appropriate interpretation of the results through tools that enable intuitive and immediate visual perception of emerging patterns and dynamics. We demonstrate feasibility, generality and effectiveness of our Urban Data Science at scale approach through multiple use cases and examples taken from real-world requirements collected in various cities and accounting for diverse business and city needs.

Dynamic High Availability Architecture Framework for SOA Computing

In Software technology stackCloud services provides easy coupling implementation to enhance encapsulation data between multiple platform data exchanges. My finding towards introducing High Availability Architecture for cloud environment which covers Load Balancing, Failover, High Availability Resources. To achieve thisfeatures it’s identified framework architecture which is called as Dynamic High Availability Architecture Framework for SOA Computing which increase cloud services standard inhigh witheasy adaptable security. Even though cloud service supports loose coupling and isolation business logics. At current cloud service provide wants to launch new web service request on fly same service will notnotified into client in real-time scenario. To overcome this complicated situation we have introduced (GHAFC) Generic Architecture Framework in Cloud Computing. Which will support data exchanges between producer and consumer onthe fly with real time scenario.

Transactions in relaxed memory architectures

The integration of transactions into hardware relaxed memory architectures is a topic of current research both in industry and academia. In this paper, we provide a general architectural framework for the introduction of transactions into models of relaxed memory in hardware, including the SC, TSO, ARMv8 and PPC models. Our framework incorporates flexible and expressive forms of transaction aborts and execution that have hitherto been in the realm of software transactional memory. In contrast to software transactional memory, we account for the characteristics of relaxed memory as a restricted form of distributed system, without a notion of global time. We prove abstraction theorems to demonstrate that the programmer API matches the intuitions and expectations about transactions.

Wireless Network Virtualization With SDN and C-RAN for 5G Networks: Requirements, Opportunities, and Challenges

Wireless network virtualization (WNV) has drawn attention from the researchers ranging from academia to industry as one of the significant technologies in the cellular network communication. It is considered as a pioneer to achieve effective resource utilization with decreased operating expenses and capital expenses by decoupling the networks functionalities of coexisting virtual networks. It facilitates fast deployment of new services and novel technologies. WNV paradigm is in the early stages, and there is a large room for the research community to develop new architectures, systems, and applications. The availability of software-defined networking (SDN) and cloud/centralized radio access network (C-RAN) steers up the hope for the WNV realization. This paper surveys WNV along with the recent developments in SDN and C-RAN technologies. Based on these technologies and WNV concepts, we identify the requirements and opportunities of future cellular networks. We then propose a general architectural framework for the WNV based on SDN. In-depth discussion of challenges and research issues as well as promising approaches for future networks communication improvements are also proposed. Finally, we give several promising candidates of future network services for residential customers and business customers.

Generic framework for mining cellular automata models on protein-folding simulations.

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Information-centric networking for machine-to-machine data delivery: a case study in smart grid applications

Largely motivated by the proliferation of content-centric applications in the Internet, information-centric networking has attracted the attention of the research community. By tailoring network operations around named information objects instead of end hosts, ICN yields a series of desirable features such as the spatiotemporal decoupling of communicating entities and the support of in-network caching. In this article, we advocate the introduction of such ICN features in a new, rapidly transforming communication domain: the smart grid. With the rapid introduction of multiple new actors, such as distributed (renewable) energy resources and electric vehicles, smart grids present a new networking landscape where a diverse set of multi-party machine-to-machine applications are required to enhance the observability of the power grid, often in real time and on top of a diverse set of communication infrastructures. Presenting a generic architectural framework, we show how ICN can address the emerging smart grid communication challenges. Based on real power grid topologies from a power distribution network in the Netherlands, we further employ simulations to both demonstrate the feasibility of an ICN solution for the support of real-time smart grid applications and further quantify the performance benefits brought by ICN against the current host-centric paradigm. Specifically, we show how ICN can support real-time state estimation in the medium voltage power grid, where high volumes of synchrophasor measurement data from distributed vantage points must be delivered within a very stringent end-to-end delay constraint, while swiftly overcoming potential power grid component failures.

A Generic Reference Architecture for Collaboratory Scientific Virtual Laboratory

The paper presents a generic reference architecture framework for collaboratory experiment virtual laboratory. The model presented is open source driven, flexible and based on modern tools and tech...

A Generic Reference Architecture for Collaboratory Scientific Virtual Laboratory

The paper presents a generic reference architecture framework for collaboratory experiment virtual laboratory. The model presented is open source driven, flexible and based on modern tools and technologies. This in effect will allow geographically remote scientists with limited internal laboratory resources, access to wealth of experimental datasets, computing facilities, and distributed hard-to-duplicate laboratory devices. The key issues discussed are architectural design and choice of technology used for creating virtual laboratory. This architecture offers great levels of flexibility, simplicity, and interoperability that are needed to allow integration between heterogeneous distributed grid resources and its clients and executors. The framework, besides theoretical modelling, will provide a road map for future research and open questions.

Modelling and facilitating RFID-based collaborative logistics processes

Logistics processes, where RFID technologies are applied to improve process efficiency and flexible organisation of collaboration is required in the foreground, pose challenges to process modelling, analysis and design in business process management. To meet these challenges, we propose in this paper an integrated approach which bundles XSLT nets, a novel variant of high-level Petri nets to model RFID-based logistics processes and to enable their automatic execution, as well as social networking coordinated by community processes to support the interconnection and web-based collaboration of logistics partners. The utility of the approach is demonstrated in two modelling use cases. We also present a general architecture framework of process-oriented social information systems.

Hybrid bio-inspired techniques for land cover feature extraction: A remote sensing perspective

Recent advances in the theoretical and practical implementations of biogeography have led to the exploration of new bio-inspired techniques which can prove to be the building blocks of hybrid bio-inspired techniques. This aspect was discovered while considering the exploration of bio-inspired intelligence for developing generic optimization algorithms that can be adapted for performing the given land cover feature extraction task at hand. Certain bio-inspired techniques when integrated with the existing optimization techniques can drastically improve their optimization capability hence leading to better feature extraction. In this paper, we propose a generic architectural framework of a hybrid biologically inspired technique that is characterized by its capability to adapt according to the database of expert knowledge for a more efficient, focused and refined feature extraction. Since our hybrid feature extractor possesses intelligence for selective cluster identification for application of either of the constituent techniques which is in turn based on an inefficiency analysis, we term our classifier as the hybrid bio-inspired pattern analysis based intelligent classifier. Our hybrid classifier combines the strengths of the modified BBO Technique for land cover feature extraction with the Hybrid ACO2/PSO Technique for a more refined land cover feature extraction. The algorithm has been tested for for the remote sensing application of land cover feature extraction where we have applied it to the 7-Band carto-set satellite image of size 472 × 546 of the Alwar area in Rajasthan and gives far better feature extraction results than the original biogeography based land cover feature extractor [20] and the other soft computing techniques such as ACO, Hybrid PSO-ACO2, Hybrid ACO-BBO Classifier, Fuzzy sets, Rough-Fuzzy Tie up etc.. The 7-band Alwar Image is a benchmark image for testing the performance of a bio-inspired classifier on multi-spectral satellite images since this image is a complete image in the sense that it contains all the land cover features that we need to extract and hence land cover feature extraction results are demonstrated and compared using this image as the standard image.

In-field logistics processes management based on business activities monitoring systems paradigm

The objective of this paper is to propose a generic architecture framework for an activities monitoring system capable of providing real-time access to critical data and performance indicators for agricultural field operations. It is based on an innovative enhancement of the Business Activity Monitoring (BAM) systems used mainly in the industrial context. The proposed framework architecture has been tested with a specific and real-life harvesting example case. The premise is that agricultural field logistics operations are viewed as a challenging application and development target for emerging and innovative decision-support systems.

Agent-Oriented Captology for Anthropocentric Systems

Considering that anthropo centric systems are an adequate domain for captological approaches, and that interface agents are most natural interactants for the humans involved, the paper presents a broad-spectrum generic architectural framework to support developing flexible interfaces for industrial applications, based on synergetic correlation between persuasive technologies and polymorphic agents. The design space for agent-oriented captology is defined and several of its main dimensions are elaborated upon. The main mechanisms used are dynamic priorities, "flexible cloning" and fuzzy temporal windows. Some agent-oriented test-bench applications instantiating the generic architecture, arc described briefly.

An expert system architectural framework for engineering selection

A generic architectural framework for constructing flexible expert systems for engineering selection is proposed in this paper. A two-tiered framework is suggested to mirror the two steps of elimination and refinement in selection tasks. The top layer consists of reverse rules for implementing the elimination of inapplicable alternatives, and the bottom layer consists of multiple-criteria decision-making (MCDM) models for explicitly modeling the decision-making processes in selection. Some MCDM models which involve user preferences or weights are incorporated in the framework because the selection task involves user preferences or weights assigned to decision parameters. The framework has been applied to the domain of solvent selection for carbon dioxide removal processes, and a prototype advisory system based on the framework has been developed. The proposed framework contributes to the field of engineering selection because it enables the explicit representation of selection knowledge, and the formal modeling of user preferences.