Service-oriented Architecture Research Articles

MSOA: A modular service-oriented architecture to integrate mobile manipulators as cyber-physical systems

MSOA: A modular service-oriented architecture to integrate mobile manipulators as cyber-physical systems

Load Balancing using Genetic Algorithm with Cloud SIM Simulator in Open Source

Clouds are highly configurable infrastructure that offer software and platforms as a service, enabling users to subscribe for the services they need using a pay-as-you-go model. The popularity of cloud computing is growing due to its straightforward, service-oriented architecture. Every day, more and more people are using the cloud. Cloud computing is typically built on data centres with the capacity to support huge numbers of users. The ability of clouds to manage loads determines how reliable they are in order to address this issue; clouds need to include a load balancing system. In cloud computing, load balancing will help clouds become more capable and reliable by boosting their capacity.

Migration of Model-based Software Components to Service-oriented Architectures

Migration of Model-based Software Components to Service-oriented Architectures

Harnessing Traditional Business Culture Resources: Scalable Parameter Server Architecture with Distributed Machine Learning

This paper explores the development and utilization of Traditional business culture resources, focusing on Yan'an's rich historical significance and its potential political, cultural, educational, and economic value. Leveraging distributed machine learning systems within a parameter server architecture, the research addresses challenges related to scalability and robustness, particularly in the face of random node downtime and network interruptions. Through intelligent simulation and experimentation, the study demonstrates the effectiveness of employing machine learning techniques to achieve high accuracy in modeling Traditional business culture's development and utilization.

An Analytical Model of IaaS Architecture for Determining Resource Utilization.

Cloud computing has become a major component of the modern IT ecosystem. A key contributor to this has been the development of Infrastructure as a Service (IaaS) architecture, in which users' virtual machines (VMs) are run on the service provider's physical infrastructure, making it possible to become independent of the need to purchase one's own physical machines (PMs). One of the main aspects to consider when designing such systems is achieving the optimal utilization of individual resources, such as processor, RAM, disk, and available bandwidth. In response to these challenges, the authors developed an analytical model (the ARU method) to determine the average utilization levels of the aforementioned resources. The effectiveness of the proposed analytical model was evaluated by comparing the results obtained by utilizing the model with those obtained by conducting a digital simulation of the operation of a cloud system according to the IaaS paradigm. The results show the effectiveness of the model regardless of the structure of the emerging requests, the variability of the capacity of individual resources, and the number of physical machines in the system. This translates into the applicability of the model in the design process of cloud systems.

The optimization of roll-bond cold plate based on Taguchi-grey theory for server chips thermal management

The roll-bond cold plate, an economical and straightforward electronics liquid cooling approach, is highly promising to address the increasing electronics chip thermal management challenges. However, the roll-bond cold plate with staggered cellular flow channels, while having a sizable solid-liquid contact area and high heat dissipation potential, suffers from inadequate temperature uniformity and fluidity. This study addresses flow and temperature uniformity issues in current roll-bond cold plates by proposing a design—Direct Liquid Cooling Roll-Bond Plates (DLCRBP) tailored for high-performance server architectures. To investigate how regional combination, cellular diameter, and longitudinal spacing affect both thermal and flow performance, orthogonal experiments with diverse flow channel structures were conducted using the Taguchi-grey theory. COMSOL-based numerical simulation were used to analyze these experiment conditions. Multi-objective optimization, considering pressure drop, heat source temperature uniformity, and coolant temperature difference, was then performed using the grey correlation method. The optimized DLCRBP (A3B5C1) was fabricated, and its performance was compared with the staggered cellular DLCRBP (SCS), which is the control group without optimization, under various inlet flow velocities, heat source powers, and coolant inlet temperatures. Experimental comparisons illustrate that the optimized structure ensures outstanding temperature uniformity even at low inlet flow velocities. Specifically, at an inlet flow velocity of 0.2 m/s, the average and maximum temperature differences on the heat source's upper surface are 36.5 % and 75.3 % lower, respectively, compared to pre-optimization levels. Furthermore, A3B5C1's temperature uniformity improves with higher coolant inlet flow velocity and lower coolant inlet temperatures. At a coolant inlet flow velocity of 0.5 m/s or higher, A3B5C1 sustains the surface temperature of a 600 W chip below the thermal design's safe temperature of 77.8 °C, highlighting its enhanced performance.

ПОРІВНЯННЯ МОЖЛИВОСТЕЙ СЕРВІСНО-ОРІЄНТОВНОЇ АРХІТЕКТУРИ ТА МІКРОСЕРВІСНОЮ АРХІТЕКТУРОЮ У СТВОРЕННІ ІНФОРМАЦІЙНИХ СИСТЕМ

The paper analyzes the capabilities of such architectures as service-oriented architecture and microservice architecture. The paper describes the advantages and disadvantages of these architectures, provides possible implementation schemes and differences. Amazon Web Service was chosen as a cloud service provider. As a result of the analysis, recommendations have been made on when it is appropriate to use one or the other approach. Microservices allow for flexible scaling of the system by adding or removing individual services depending on the needs. Service-oriented architecture promotes high modularity and convenient interaction between system components. In view of the rapidly growing technologies and requirements for information systems, the usage of microservice and service-oriented architectures will allow to create a dynamic and efficient system that can quickly adapt to changing conditions and user requirements.

Evolutionary Architectures in Web Applications: A Comparative Study of Client-Server, Multi-Tier, and Service-Oriented Approaches

This manuscript provides an in-depth comparative analysis of three core architectural models in web application development: client-server, multi-tier, and service-oriented architectures (SOA). Through a series of simulations, case studies, and empirical data, the study evaluates the efficiency, scalability, and adaptability of these architectures within commercial environments. The research highlights the evolving needs of modern web applications and offers insights into choosing the appropriate architectural strategy to enhance performance and maintainability in dynamic business settings.

A Lightweight Model of Underwater Object Detection Based on YOLOv8n for an Edge Computing Platform

The visual signal object detection technology of deep learning, as a high-precision perception technology, can be adopted in various image analysis applications, and it has important application prospects in the utilization and protection of marine biological resources. While the marine environment is generally far from cities where the rich computing power in cities cannot be utilized, deploying models on mobile edge devices is an efficient solution. However, because of computing resource limitations on edge devices, the workload of performing deep learning-based computationally intensive object detection on mobile edge devices is often insufficient in meeting high-precision and low-latency requirements. To address the problem of insufficient computing resources, this paper proposes a lightweight process based on a neural structure search and knowledge distillation using deep learning YOLOv8 as the baseline model. Firstly, the neural structure search algorithm was used to compress the YOLOv8 model and reduce its computational complexity. Secondly, a new knowledge distillation architecture was designed, which distills the detection head output layer and NECK feature layer to compensate for the accuracy loss caused by model reduction. When compared to YOLOv8n, the computational complexity of the lightweight model optimized in this study (in terms of floating point operations (FLOPs)) was 7.4 Gflops, which indicated a reduction of 1.3 Gflops. The multiply–accumulate operations (MACs) stood at 2.72 G, thereby illustrating a decrease of 32%; this saw an increase in the AP50, AP75, and mAP by 2.0%, 3.0%, and 1.9%, respectively. Finally, this paper designed an edge computing service architecture, and it deployed the model on the Jetson Xavier NX platform through TensorRT.

A model of recommendation service architecture for the formation of an individual educational trajectory for self-paced massive open online courses studying

A model of recommendation service architecture for the formation of an individual educational trajectory for self-paced massive open online courses studying

A Mobile Application Based Optimized Out-Patient Emergency Request Model

This paper developed a mobile APP called Health Emergency Request APP (HER-APP). The App sends out-patients‘ emergency request to any closest health personnel within a particular location and matches a patient to a particular health personnel for immediate attention. We observed that the process of responding to out-of-hospital emergencies after a crisis have faced a lot of communication challenges between patients and the nearest healthcare personnel especially in Nigeria. There is also a problem of assigning a patient to the most qualified health personal for better care. This has resulted in increased mortality even when such emergency could better be handled. It becomes compelling to develop a mobile APP that allows a seamless communication between patient under emergency and the nearest medical expert with medical facility to save lives prior to the full engagement of the attention of a medical doctor or ambulance. This emergency request service-oriented mobile application helps patients contact any closest health personnel within a particular location using a location tracking service. The mobile application implements a matching algorithm between patients and responders, and assists people in emergency to get quick pre-clinical treatment. It uses an optimized service-oriented architecture which reduces the communication process between a patient in an emergency and the doctor or responder using a Google global positioning system as a location tracking service to helps track a patient requesting for assistance as well as all available responders. The APP uses location factor to determine a model to enhance the system on a large scale basis to provide a dispatch method to allocate patients to responders. This paper enhanced the Hungarian model and determines the best patient-responder match. The mobile APP is available at www.github.com/magnifikuc.

The communication and measurement architecture of BDS-3 global operations and services

This study introduces the third-generation BeiDou Navigation Satellite System (BDS-3) system’s creative global operation and service architecture based on regional stations and Ka-band inter-satellite links (ISLs). The architecture’s contributions to BDS-3 include not only combined orbit determination and time synchronization but also autonomous orbit determination and time synchronization, global operations and services. The BDS-3 on-orbit operation results are being presented in the paper to verify the designed capabilities. Compared with BDS-2, the orbit determination accuracy is improving from 0.6 m to 0.15 m, and the time synchronization accuracy is improving from 6.67 ns to 1.16 ns. Under autonomous orbit determination and time synchronization, the 30-day orbit maintenance accuracy reaches 16 m, and the time synchronization accuracy reaches 3.74 ns. The success rate of data transmission reaches 99%, and the delay is better than 12.9 s. In the future, laser ISLs will be used to enhance the system structure and further improve global operation and service capabilities.

Efficient criticality oriented service brokering policy in cloud datacenters

Cloud service provider (CSP) offers a huge number of datacenters and virtual servers to the users for processing their workloads in an infrastructure as a service (IaaS) cloud computing environment. Due to the heterogeneous volume of these resources and the immense number of user workloads arriving simultaneously in the cloud, it is necessary to use an effective load distribution technique for scheduling the resources to achieve high performance and high user satisfaction. Service brokering policy and load balancing techniques are the two crucial areas to be focused on while selecting the datacenters and virtual machines, respectively. In this study, we have proposed a dynamic efficient criticality-oriented service brokering policy for load allocations among datacenters by considering task criticality, datacenter proximity, and traffic, the size of the datacenter, its present load and makespan value. The proposed methodology is examined against the current policies in the CloudAnalyst simulation tool and the analysis report confirms that our proposed policy gives priority to processing the urgent loads and chooses the optimum datacenter to diminish the load response time, datacenter processing time, minimizes the cost, achieves optimum resource utilization and workload balancing among resources.

대형마트의 발전 방향

Due to a combination of sales regulations and lack of innovation, the growth of large marts is stagnating and profitability is deteriorating. Accordingly, this study examined the impact of large smarks on the national economy, especially on production, added value, employment, sales of suppliers, and tax revenues, through industry correlation analysis and other algebraic calculations. As a result of inter-industry analysis, large marts increase the annual production, added value, and employment by KRW 10 trillion, KRW 11 trillion, and 210,000 people in the wholesale/retail and product brokerage service industries, respectively, and by KRW 43 trillion, KRW 38 trillion, and 320,000 people, respectively, in the industry as a whole. In addition, large marts increase supplier sales by KRW 14 trillion per year and tax revenues by KRW 917.3 billion per year (corporate tax KRW 264.5 billion + value-added tax KRW 652.8 billion). Therefore, it can be said that the impact of large marts on the national economy is truly enormous. Therefore, the government needs to help large marts become competitive by reevaluating populist regulations on large marts that are not helpful to the national economy and open the way for large marts to provide better products and services. In addition large marts need to demonstrate its entrepreneurial spirit and innovate in products and services so that people continue to visit the large marts.

Eclipse web service application programming interface

Objective. Low-coupling seamless integration of multiple systems is the core foundation of smart radiotherapy. Following Service-Oriented Architecture style, a set of named operations (Eclipse Web Service API, EWSAPI) was developed for realizing network call of Eclipse. Approach. Under the guidance of Vertical Slice Architecture, EWSAPI was implemented in the C# language and based on ASP .Net Core 6.0. Each operation consists of three components: Request, Endpoint and Response. Depending on the function, the exchanged data for each operation, as input or output parameters, is the empty or a predefined JSON data. These operations were realized and enriched gradually, layer by layer, with reference to the clinical business classification. The business logic of each operation was developed and maintained independently. In situations where Eclipse Scripting API(ESAPI) was required, constraints of ESAPI were followed. Main results. Selected features of Eclipse TPS were encapsulated as standard web services, which can be invocated by other software through network. Several processes for data quality control and planning were encapsulated into interfaces, thereby extending the functionality of Eclipse. Currently, EWSAPI already covers testing of service interface, quality control of radiotherapy data, automation tasks for plan designing and DICOM RT files’ transmission. All the interfaces support asynchronous invocation. A separate Eclipse context will be created for each invocation, and is released in the end. Significance. EWSAPI which is a set of standard web services for calling Eclipse features through network is flexible and extensible. It is an efficient way to integration of Eclipse and other systems and will be gradually enriched with the deepening of clinical applications.

Managing Household Food Waste with the FoodSaveShare Mobile Application

It is estimated that European households are responsible for 55% of food waste generation. Key factors contributing to household food waste generation include food spoilage, confusion over expiration dates, overbuying, and inadequate shopping planning. Thus, food waste prevention at the household level depends heavily on food supplies monitoring and management. To this end, during the last decade, several consumer-oriented digital tools have been designed and launched. A literature review showed that currently accessible digital tools are scarce and cover a narrow range of functionalities. Here, we address these issues by designing and launching a decision support tool implemented in a smart mobile phone application (app), the FoodSaveShare Mobile App. The application development followed a traditional client–server architecture using state-of-the-art software and hardware technologies. Additionally, a survey of 340 individuals was conducted to better understand end-user motivation for and barriers against adopting this and similar apps. The developed application combines user-provided data with a retailer loyalty program to leverage the integrated features for tracking shopping activities. The app features a household shopping list populated by product barcode scanning and manual entry. Based on food and packaging type, food products are assigned approximate expiration dates to issue product expiration reminders. For products about to expire, suggestions for their utilization are provided, drawing from a list of over 7000 recipes. Additional functionality allows users to identify products that have either been consumed in time or that need to be discarded. Analytical tools, such as past purchase and resources discarded versus resources saved statistics, offer comprehensive insight and encourage improved shopping and consumption practices. The FoodSaveShare App was launched during the A2UFood Project, which allowed an organised campaign for its use. The app was tested under real customer data and conditions, and selected features have been adopted by the largest supermarket chain on the Island of Crete, Greece. The potential end-user survey results suggest that, provided personal data use issues are addressed, such apps can have a significant impact on reducing household food waste. Future work will focus on analysing the datasets produced by the application to assess its impact on household food waste management.

Network Ideological and Political Education System for College Students Based on Multimedia Service Architecture

Today, the network society has become an integral part of human society, and the network life marked by digitization, informatization and networking has become a new state of existence; a new society marked by interactivity, virtuality and innovation A mode of operation has been created. A network, in simple terms, is to connect, and can be called a computer network. Such highest degree of social informatization in my country. It is a new idea designed by making full use of computer networks, multimedia technology and modern communication technology and closely combining the cognitive hotspots of contemporary college students. way of political education. In response to the above problems, this article uses deep learning technology to develop an intelligent education system based on detection technology. The system takes identifying whether the standard is met as the main goal, and gives comprehensive evaluation and improvement suggestions for the quality of action completion. It gets rid of the constraints of the venue.

Combining Machine Learning and Lifetime-Based Resource Management for Memory Allocation and Beyond

Memory management is fundamental to the performance of all applications. On modern server architectures, an application's memory allocator needs to balance memory utilization against the ability to use 2MB huge pages, which are crucial for achieving high performance. This paper shows that prior C++ memory allocators are fundamentally limited because optimizing this trade-off depends on the knowledge of object lifetimes, which is information allocators lack. We introduce a two-step approach to attain high memory utilization in huge pages. We first introduce a novel machine-learning approach that predicts the lifetime of freshly allocated objects using the stack trace at the time of allocation and treats stack traces as natural language. We then present a fundamentally new type of memory allocator that exploits (potentially incorrect) object lifetime predictions to achieve high memory utilization at full huge page usage. In contrast to prior memory allocators that organize their heap around size classes and free lists, our allocator organizes the heap based on predicted lifetime classes and adjusts to mispredictions on the fly. We demonstrate experimentally that this learned lifetime-aware memory allocator (LLAMA) reduces fragmentation with huge pages by up to 78%. Our approach gives rise to a new methodology for applying ML in computer systems. In addition, similar space-time bin packing problems abound in computer science and we discuss how this approach has applications beyond memory allocation to a wide range of problems.

Blind-Touch: Homomorphic Encryption-Based Distributed Neural Network Inference for Privacy-Preserving Fingerprint Authentication

Fingerprint authentication is a popular security mechanism for smartphones and laptops. However, its adoption in web and cloud environments has been limited due to privacy concerns over storing and processing biometric data on servers. This paper introduces Blind-Touch, a novel machine learning-based fingerprint authentication system leveraging homomorphic encryption to address these privacy concerns. Homomorphic encryption allows computations on encrypted data without decrypting. Thus, Blind-Touch can keep fingerprint data encrypted on the server while performing machine learning operations. Blind-Touch combines three strategies to efficiently utilize homomorphic encryption in machine learning: (1) It optimizes the feature vector for a distributed architecture, processing the first fully connected layer (FC-16) in plaintext on the client side and the subsequent layer (FC-1) post-encryption on the server, thereby minimizing encrypted computations; (2) It employs a homomorphic encryption-compatible data compression technique capable of handling 8,192 authentication results concurrently; and (3) It utilizes a clustered server architecture to simultaneously process authentication results, thereby enhancing scalability with increasing user numbers. Blind-Touch achieves high accuracy on two benchmark fingerprint datasets, with a 93.6% F1- score for the PolyU dataset and a 98.2% F1-score for the SOKOTO dataset. Moreover, Blind-Touch can match a fingerprint among 5,000 in about 0.65 seconds. With its privacy-focused design, high accuracy, and efficiency, Blind-Touch is a promising alternative to conventional fingerprint authentication for web and cloud applications.

Integrated Service Architecture to Promote the Circular Economy in Agriculture 4.0

Innovation has been the transforming tool of precision agriculture as a response to population growth and the demand for more food with quality, less waste, food security, and sustainable management of environmental resources. The challenges are to increase the productivity of cultivated areas, both for current and future areas, to manage the use of potable water, scarce in many regions, to keep the soil fertile, and to reduce waste through reuse, optimization, resource sharing, and operational and strategic management based on accurate information of planting, harvesting, and management of environmental conditions, which are also objectives of the Circular Economy. Therefore, using Industry 4.0 technologies in agriculture becomes fundamental to facing such challenges. This paper presents a systematic literature review on Industry 4.0 technologies adopted in agriculture for sustainable development, considering environmental, economic, and social benefits. The research pointed to the use of IoT in irrigation control systems by sending automatic commands, monitoring soil and weather conditions, in the use of machinery with some automation features and in cloud data storage systems, and with the use of Big Data analytical tools, with access by mobile devices, these uses contribute to operational and strategic decision making in the management of planting and harvesting. However, the literature review did not find a technological architecture for Integrated Services in Agriculture 4.0. Thus, this paper proposes a Service Architecture that enables the promotion of a Circular Economy in Agriculture 4.0. The contribution of this article to the theory is in the expansion of knowledge of the use of technologies in Agriculture 4.0. In terms of practice, this article provides an Integrated Service Architecture so that new products can be developed for Agriculture 4.0 and thus contribute to society in reducing food insecurity, generating environmental, economic, and social benefits, and promoting the Circular Economy in Agriculture 4.0.