Service-oriented Architecture Research Articles

Performance Evaluation of Load-Balancing Algorithms with Different Service Broker Policies for Cloud Computing

Cloud computing has seen a major boom during the past few years. Many people have switched to cloud computing because traditional systems require complex resource distribution and cloud solutions are less expensive. Load balancing (LB) is one of the essential challenges in cloud computing used to balance the workload of cloud services. This research paper presents a performance evaluation of the existing load-balancing algorithms which are particle swarm optimization (PSO), round robin (RR), equally spread current execution (ESCE), and throttled load balancing. This study offers a detailed performance evaluation of various load-balancing algorithms by employing a cloud analyst platform. Efficiency concerning various service broker policy configurations for load-balancing algorithms’ virtual machine load balance was also calculated using metrics such as optimized response time (ORT), data center processing time (DCPT), virtual machine costs, data transfer costs, and total cost for different workloads and user bases. Many of the past papers that were mentioned in the literature worked on round robin and equally spread current execution, and throttled load-balancing algorithms were based on efficiency and response time in virtual machines without recognizing the relation between the task and the virtual machines, and the practical significance of the application. A comparison of specific load-balancing algorithms has been investigated. Different service broker policy (SBP) tests have been conducted to illustrate the load-balancing algorithm capabilities.

Virtualization Airborne Trusted General Computing Technology

Aircraft information service systems, such as airborne information systems, airborne integrated maintenance management systems, and cabin management systems, have greatly improved the ease of use and maintenance of civil aircraft. The current computing platforms used for accommodating these systems are unable to satisfy the multifaceted requirements of future information-based aircraft, such as energy conservation, emission reduction, high-performance computing, and information security protection, due to their high computing capacity, weight, and power consumption. Based on multi-core multi-threaded processors, a security hardware unit with microkernel virtualization technology and a virtualization airborne trusted general computing service architecture is proposed, and key technologies, including a high-performance processing and high-security hardware unit, virtualization management software unit, and virtualization security protection architecture were designed. By building a verification environment, the proposed platform was verified in terms of its application accommodation function, platform performance, and network security protection, for comparison with the existing platforms. The results showed that our method can fulfill the requirements of these technical indicators and is applicable, not only to new-generation civil aircraft, but also to unmanned aerial vehicles (UAVs) and emergency rescue aircraft with high-performance safety-critical computing needs.

Cost optimization in cloud environment based on task deadline

The popularity of cloud and fog services has raised the number of users exponentially. Main advantage of Cloud/fog infrastructure and services are crucial specially for commercial users from diverse areas. The variety of service requests with different deadlines makes the task of a service broker challenging. The fog and cloud users always lookfor a suitable compromise between cost and quality of service in terms of response time therefore, the cost optimization is vital for the cloud/fog service providers to capture the market. In this paper an algorithm, Cost Optimization in the cloud/fog environment based on Task Deadline (COTD) is proposed that optimizes cost without compromising the response time. In this algorithm the task deadline is considered as a constraint and an appropriate data center for task processing is selected. The proposed algorithm is suitable for runtime decision making due to its low complexity. The proposed algorithm is evluated using a well-known simulation tool Cloud Analyst. Our comprehensive testbed simulations show that COTD outperforms the existing schemes, Service Proximity Based Routing and Performance-Optimized Routing. The proposed algorithm successfully minimizes the cost by 35% on average while maintaining the response time.

Multi-objective distributed Web service composition—A link-dominance driven evolutionary approach

Service-oriented architecture (SOA) encourages the creation of modular applications involving Web services as the reusable components. Data-intensive Web services manipulate and deal with the massive data that emerged by technological advances and their various applications. Distributed Data-intensive Web Service Composition (DWSC) includes the selection of data-intensive Web services from diverse locations on the network and composing them into a service to accomplish a complex task. Optimising Quality of Service (QoS) while satisfying the functional requirements is a fundamental challenge for service developers. The multi-objective and distributed nature of the DWSC problem demands satisfying algorithms to automatically produce the Pareto optimal set of composite services. In this paper, we propose a new Evolutionary Computation (EC) approach based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel local search technique to effectively solve the multi-objective distributed DWSC problems. Our local search technique employs an innovative concept, communication link dominance, to incorporate domain-specific knowledge. The performance of our proposed link-dominance driven EC approach is evaluated on benchmark datasets. The results show that our proposed method has the highest quality with acceptable execution time for most of the composition tasks among competing algorithms.

An Artificial Intelligence-as-a-Service Architecture for deep learning model embodiment on low-cost devices: A case study of COVID-19 diagnosis

Coronavirus Disease-2019 (COVID-19) causes Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2) and has opened several challenges for research concerning diagnosis and treatment. Chest X-rays and computed tomography (CT) scans are effective and fast alternatives to detect and assess the damage that COVID causes to the lungs at different stages of the disease. Although the CT scan is an accurate exam, the chest X-ray is still helpful due to the cheaper, faster, lower radiation exposure, and is available in low-incoming countries. Computer-aided diagnostic systems based on Artificial Intelligence (AI) and computer vision are an alternative to extract features from X-ray images, providing an accurate COVID-19 diagnosis. However, specialized and expensive computational resources come across as challenging. Also, it needs to be better understood how low-cost devices and smartphones can hold AI models to predict diseases timely. Even using deep learning to support image-based medical diagnosis, challenges still need to be addressed once the known techniques use centralized intelligence on high-performance servers, making it difficult to embed these models in low-cost devices. This paper sheds light on these questions by proposing the Artificial Intelligence as a Service Architecture (AIaaS), a hybrid AI support operation, both centralized and distributed, with the purpose of enabling the embedding of already-trained models on low-cost devices or smartphones. We demonstrated the suitability of our architecture through a case study of COVID-19 diagnosis using a low-cost device. Among the main findings of this paper, we point out the performance evaluation of low-cost devices to handle COVID-19 predicting tasks timely and accurately and the quantitative performance evaluation of CNN models embodiment on low-cost devices.

Deep Learning Approaches for Traffic Prediction Forecasting in Multi-Level Cloud Architecture for Autonomous Vehicle Services

Autonomous vehicle (AV) is one of the most new use cases and a technology for fifth-generation (5G) and next-generation mobile networks in numerous applications., the use of AVs has exponentially worldwide due to the rapidly growing awareness and use of artificial intelligence (AI) methods in various fields. Predicting data flows is essential for AVs to improve data transmission and decrease delays through more efficient use of appropriate capabilities, monitoring, management, and control of the traffic system. This paper proposes a deep learning approach (DL) with the bidirectional long-short-term memory model (BI-LSTM) for predicting the traffic rates of AVs with multi-cloud services. In terms of prediction accuracy, a comparison is conducted between the BI-LSTM and the unidirectional LSTM based on the number of batch sizes used. The prediction accuracy is computed using the root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), and processing time. The results show that the prediction accuracy with BI-LSTM outperforms the LSTM model. Besides, the prediction accuracy using 8 batch sizes outperforms the competitors and offers outstanding performance.

Efficient immediate-access dynamic indexing

In a dynamic retrieval system, documents must be ingested as they arrive, and be immediately findable by queries. Our purpose in this paper is to describe an index structure and processing regime that accommodates that requirement for immediate access, seeking to make the ingestion process as streamlined as possible, while at the same time seeking to make the growing index as small as possible, and seeking to make term-based querying via the index as efficient as possible. We describe a new compression operation and a novel approach to extensible lists which together facilitate that triple goal. In particular, the structure we describe provides incremental document-level indexing using as little as two bytes per posting and only a small amount more for word-level indexing; provides fast document insertion; supports immediate and continuous queryability; provides support for fast conjunctive queries and similarity score-based ranked queries; and facilitates fast conversion of the dynamic index to a “normal” static compressed inverted index structure. Measurement of our new mechanism confirms that in-memory dynamic document-level indexes for collections into the gigabyte range can be constructed at a rate of two gigabytes/minute using a typical server architecture, that multi-term conjunctive Boolean queries can be resolved in just a few milliseconds each on average even while new documents are being concurrently ingested, and that the net memory space required for all of the required data structures amounts to an average of as little as two bytes per stored posting, less than half the space required by the best previous mechanism.

Enhancing Blood Products Sharing Among Established Blood Banks and Health Facilities through the use of ICT

The gap between blood supply and blood demand is a widening everyday as the population increases and it needs to be bridged. Since the amount blood donated in Kenya is below the world Health Organization’s recommendation (WHO 2015), inter-facility sharing of information relating to blood availability should be enhanced to improve sharing of available donated blood between health facilities. The objective of the research study was to determine the current processes used when sharing blood between health facilities and there challenges and to propose coordination between blood supply and demand among health facilities and blood banks through the use of ICT .The study used descriptive research design and 22 participants (lab technicians and doctors) in different health facilities in Nairobi County participated in the study. Results from the study indicate that in most health facilities (72%) blood demand exceeds blood supply. During emergencies when blood stocks are inadequate, most health facilities (63.6%) source the blood by requesting it from other health facilities and blood banks and mostly making these blood requests through telephone calls. The main challenge faced when using the current mechanisms is the delay in blood supply (40.9%) followed by a challenge of getting the response/feedback on time Based on the findings it was evident that the proposed intervention will be of a great use to bridge the gap of between blood supply and demand and solving the challenges faced when sharing blood during emergencies. Rapid Application Development (RAD) system design AND Service Oriented Architecture (SOA) were applied in developing the ICT intervention. To evaluate the success of the ICT intervention, a survey was conducted in five health facilities (two level 4 and three level 3 health facilities) to evaluate the satisfaction of the health facilities when using the system.

Novel Ground-Up 3D Multicellular Simulators for Synthetic Biology CAD Integrating Stochastic Gillespie Simulations Benchmarked with Topologically Variable SBML Models.

The elevation of Synthetic Biology from single cells to multicellular simulations would be a significant scale-up. The spatiotemporal behavior of cellular populations has the potential to be prototyped in silico for computer assisted design through ergonomic interfaces. Such a platform would have great practical potential across medicine, industry, research, education and accessible archiving in bioinformatics. Existing Synthetic Biology CAD systems are considered limited regarding population level behavior, and this work explored the in silico challenges posed from biological and computational perspectives. Retaining the connection to Synthetic Biology CAD, an extension of the Infobiotics Workbench Suite was considered, with potential for the integration of genetic regulatory models and/or chemical reaction networks through Next Generation Stochastic Simulator (NGSS) Gillespie algorithms. These were executed using SBML models generated by in-house SBML-Constructor over numerous topologies and benchmarked in association with multicellular simulation layers. Regarding multicellularity, two ground-up multicellular solutions were developed, including the use of Unreal Engine 4 contrasted with CPU multithreading and Blender visualization, resulting in a comparison of real-time versus batch-processed simulations. In conclusion, high-performance computing and client-server architectures could be considered for future works, along with the inclusion of numerous biologically and physically informed features, whilst still pursuing ergonomic solutions.

Behavioural and Welfare Analysis of an Intermediary in Biodiversity Offset Markets

This paper provides a behavioural and welfare analysis of an intermediary in biodiversity offset markets. These markets are characterised by high information requirements and transaction costs, threatening economic efficiency and even biodiversity outcomes. Specialised intermediaries facilitate trading by providing information and brokering services. By buying, holding and selling offset credits from storage, the intermediary can decrease both financial and ecological risks in the market. As a drawback, the intermediary may exploit market power upstream or downstream due to ecological features of the offset market. Intermediaries decrease the trading parties’ transaction costs by offering specialised information, reduce uncertainty, and decrease the costs of offsetting by increasing liquidity in the market and offering certain offset credits. When the intermediary has market power, selling and buying prices deviate from the competitive equilibrium. This welfare loss may be lower than the loss from transaction costs and trade ratios in decentralised trade, even in the case of the intermediary having both monopoly and monopsony power. The intermediary is the most useful when trade ratios are high and when the intermediary stores mature credits, which eliminates ecological uncertainty and thereby offers cost savings for developers, and may result in a higher level of biodiversity.

Reentry support in Victoria, Australia: managing risk, or fostering agency?

More than half of Australia’s prison population have experienced prior incarceration. Factors such as homelessness, mental illness, and poverty compound the challenges of reentry. Reentry support in Victoria, Australia is state funded, yet delivered via three non-governmental organizations. In this article we explore practitioners’ experiences of working with people who were incarcerated in the liminal phase of reentry—where one is neither prisoner nor citizen but in-between. Practitioners reported trust and rapport are the central pillars of practice and choose to utilize strengths-based approaches instead of risk-based approaches, but felt that service brokerage is impeded by associated professionals’ concerns around risk.

Examining dynamic system integration capabilities in knowledge boundaries of convergent service architectures: two cases of a telecommunication company

This study examines the changes in a firm's system integration capabilities and knowledge boundaries. The notion of dynamic capability is found to be relevant to the creation and evolution of system integration capabilities required for innovation in complex product system (CoPS). A dynamic system integration capability enabled the creation of new service architecture, which can be seen as determining the knowledge boundary for the CoPS innovation. Two cases are examined, featuring the same firm. Here, shifts of knowledge boundaries were related to different service architectures (in both cases involving provision of music services over mobile networks). The dynamic capabilities are necessitated by the phenomena of digital convergence and hybridisation of different electronic service systems. An abnormal case of CoPS innovation is described, one which features less complexity of learning since the technological properties and systems of its service architecture and business strategy reduced requirements for the technological function of CoPS.

Fog computing-based public e-service application in service-oriented architecture

The fog computing framework provides the tools for handling public e-service resources through a real-world testbed in fog environment. The framework also facilitates communication between equipment, harmonies of fog tools and equipment, deployment of public e-services and the delivery of dynamic resources in fog landscape. In order to respond to various system events, such as device access, device failure, and device overload, the framework is also able to respond to these main functionalities. In the framework evaluation, the consequent event management and evaluation are performed of other significant measures, e.g., costs, deployment times and arrival service patterns. As a consequence, the architecture offers the tools needed to deal with the fog environment complexities and provides faster public e-service running times and significant cost benefits. The present paper outlines the present infrastructure and proposes a different model in public e-service infrastructure, which will be a coordinated effort of fog computing with an intelligent protocol of communication with a service-oriented architecture (SOA) incorporation and ultimately integration with the agent-based SOA. This proposed framework will be capable of interchanging data by decomposing the quality of service (QoS) reliable and methodological with low latency, less bandwidth, heterogeneity in less time.

Algorithm and Software Implementation of the Diagnostic System for the Technical Condition of Powerful Units

This article discusses the software implementation of the diagnostic system for auxiliary equipment of power plants (on the example of smoke exhausters). The developed program of diagnostics of auxiliary equipment of electric power plants is given on the example of condition diagnostics designed for early detection and localization of certain defects and providing recommendations for their elimination in smoke pumps, which should ensure the issuance of appropriate protocols and, upon request, protocols of the current state of smoke pumps, quality assessment of repairs and special tests, as well as graphs of retrospective parameter values for the time period selected by the user, where the users of the task - there are heads and deputy heads of workshops, senior foremen, repair engineers, as well as specialists of the planning and technical department. The problem is considered, which was solved within the framework of the software and hardware complex of the automated process control system) of the 800 MW power unit No.1 of Talimarjan TPP and is intended for operational specialists, where the task operates under the Windows operating system and the program is written in the C++ programming language Builder 6 for the development of application tasks with client -server architecture. And also the composition of the program and the program menu are given: “Task Launch”, “Daily statements”, “Input data”, “Output forms”, “Diagnostics” and “Special tests” allow you to implement the required task function at the moment. In addition, the article presents elements and components, processes and conditions of a pumping plant, pumping station and pumping station cascade, potentially dangerous and processes and conditions potentially dangerous for a pumping plant, pumping station and pumping station cascade.

An efficient clustering mechanism towards large scale service composition in IoT

Internet of things (IoT) applications hinder heterogeneity at different levels, such as device level, usage level, and communication level. In this context, service-oriented architecture (SOA) facilitates limited supports for handling heterogeneity in IoT-based applications. This article proposes a clustered hypergraph colouring (CHC) approach for designing large-scale SOA (LSS). Two noble approaches (service clustering and composition) are discussed in LSS for satisfying the service consumers (SCs) requirements. A service clustering approach is presented for the clustering of homogeneous services. This mechanism enables to reduce the search time for the service composition mechanism. A service composition approach is described with some parameters. Further, the proposed approach is validated through an experimental setup by considering the factors such as the number of services, execution time, and memory size. The execution time of LSS is minimised as compared to normal or medium-scale SOA (NSS) due to the service clustering mechanism. The novelty of this work is to minimise the execution time in the large service domain during service composition.

ПИТАННЯ ВИКОРИСТАННЯ РЕКОМЕНДАЦІЙНИХ СИСТЕМУ СКЛАДІ БРОКЕРА ОБ’ЄКТНИХ ЗАПИТАНЬВ АРХІТЕКТУРІ СЕРВІС-ОРІЄНТОВАНОЇ СИСТЕМИ

The paper examines the issue of improving the efficiency of service implementation in a service-oriented architecture (SOA) by integrating recommendation systems into the object request broker. The authors analyze the key problems that arise during the operation of two components of SOA: the service discovery pattern on the server side and the service registry usage pattern.For the service discovery pattern, the identified problems include the complexity of configuring the load balancer, the need for individual traffic balancing due to service heterogeneity, difficulties in balancing the load on the broker, the dynamic nature of request processing, as well as the complexity of monitoring and analyzing requests for anomaly detection and load forecasting.For the service registry usage pattern, the authors identified problems with unstructured data about services, lack of metadata about their functional capabilities, interfaces, availability, and quality, as well as limitations in service filtering mechanisms, which complicates the search and selection of services.As a solution, it is proposed to include a recommendation system in the load balancer and service registry. For the load balancer, it will provide traffic distribution optimization, automatic anomaly detection, load forecasting, resource utilization optimization, and adaptive management of request processing processes.For the service registry, the recommendation subsystem will allow dynamic updating of recommendations based on demand, grouping users by interests, providing context-sensitive recommendations, enriching user profiles, using collaborative filtering, and evaluating recommendation quality based on user feedback.The integration of recommendation systems can significantly improve the efficiency, performance, and user experience of SOA through personalized recommendations of relevant services that meet their specific needs. The authors consider this an important step in the development of service-oriented architecture.

Electricity System Built on Cyber-physical Enterprises: Architecture Analysis

Energy distribution systems can improve in adaptiveness by applying the concepts of cyber-physical systems (CPS), cyber-physical enterprise, and service-oriented architecture. With these paradigms, the information and communications technology (ICT) systems can respond to changes in the requirements and conditions of the environment, improving responsiveness to the fluctuation of electricity production from renewable energy sources (RES). This paper analyzes the suitability of a CPS architecture for the electricity distribution system. The novelty comes from a service-oriented model where customers and microgrids can sell services to one another and operators, building added value on existing energy resources. The architecture is analyzed with a coordinated voltage control (CVC) use case. The results suggest that the architecture can open new possibilities in utilizing energy resources and enables a customer-driven, distributed scheme instead of the strict operator-centric hierarchy of the contemporary systems.

Production management system in a modern coal and coke company based on the demand and quality of the exploited raw material in the aspect of building a service-oriented architecture

The paper deals with the implementation of the JSW Capital Group’s (Poland) Demand and Quality Driven Production Management System (SPPJ – System Zarządzania Produkcją oparty na Popycie i Jakości) using a service-oriented architecture (SOA). The main components of the SPPJ architecture have been characterized, and the scope of their integration has been defined. The individual parts in the first area, i.e. quality management, have been described in detail. Due to the extensive nature of the issue, components in other areas, i.e. planning and scheduling, coal extraction and processing, coke production, as well as sales and logistics, have only been signalled. Results of the analysis of the implementation of particular components of SPPJ areas have also been presented. The development of the system and the way of implementation in a mining environment is important from the perspective of achieving the superior objective of the JSW Capital Group’s Quality Programme, which is to increase the efficiency of management of the exploited deposit and the volume of commercial product supply.

Loose Coupling: An Invisible Thread in the History of Technology

We present an interdisciplinary survey of the history of loosely coupled systems. We apply the presented concepts in communication networks and suggest hybrid self-organizing networks (SONs) as a universal model for future networks. Self-organizing networks can fulfill the tight requirements of future networks but are challenging to use due to their complexity and immaturity. Moreover, the lack of an externally defined goal and centralized control has resulted in many distributed self-organizing systems failing. This is because the nonlinear relationships between the system parts result in emergence, i.e., we cannot predict the behavior of the whole from the behavior of the parts. Furthermore, a set of local optima does not produce a global optimum. Hybrid SONs tackle these challenges with loose or weak coupling of interacting agents that combine centralized control for global optimization with distributed control for local optimization. In the loose centralized control of almost autonomous agents, decisions are made mostly locally with small delays. This architecture has beneficial properties such as stability, obtained by decoupling the feedback loops: vertically with time-scale separation and horizontally with interference avoidance. Applications of loose coupling include modular electronics and computer design, structured software design, and service-oriented architectures, especially for microservices. Cross-layer design for network optimization is a new reason to use loose coupling in networks to improve stability. We also summarize some recent trends and present a roadmap to the future. We expect that loose coupling will be widely used in self-organizing networks of future wireless systems.

Blockchain-Based Service-Oriented Architecture for Consent Management, Access Control, and Auditing

Continuity of care requires the exchange of health information among organizations and care teams. The EU General Data Protection Regulation (GDPR) establishes that subject of care should give explicit consent to the treatment of her personal data, and organizations must obey the individual’s will. Nevertheless, few solutions focus on guaranteeing the proper execution of consents. We propose a service-oriented architecture, backed by blockchain technology, that enables: (1) tamper-proof and immutable storage of subject of care consents; (2) a fine-grained access control for protecting health data according to consents; and (3) auditing tasks for supervisory authorities (or subjects of care themselves) to assess that healthcare organizations comply with GDPR and granted consents. Standards for health information exchange and access control are adopted to guarantee interoperability. Access control events and the subject of care consents are maintained on a blockchain, providing a trusted collaboration between organizations, supervisory authorities, and individuals. A prototype of the architecture has been implemented as a proof of concept to evaluate the performance of critical components. The application of subject of care consent to control the treatment of personal health data in federated and distributed environments is a pressing concern. The experimental results show that blockchain can effectively support sharing consent and audit events among healthcare organizations, supervisory authorities, and individuals.