A Review on the Integration of Deep Learning and Service-Oriented Architecture

2021 ◽  
Vol 32 (3) ◽  
pp. 95-119
Author(s):  
Marcelo Fantinato ◽  
Sarajane Marques Peres ◽  
Eleanna Kafeza ◽  
Dickson K. W. Chiu ◽  
Patrick C. K. Hung
Keyword(s):  
Deep Learning ◽  
Web Services ◽  
Service Oriented Architecture ◽  
Learning Technology ◽  
Learning Approaches ◽  
Current Trends ◽  
Different Types ◽  
Information And Communication ◽  
Service Oriented ◽  
Different Levels

In recent years, machine learning has been used for data processing and analysis, providing insights to businesses and policymakers. Deep learning technology is promising to further revolutionize this processing leading to better and more accurate results. Current trends in information and communication technology are accelerating widespread use of web services in supporting a service-oriented architecture (SOA) consisting of services, their compositions, interactions, and management. Deep learning approaches can be applied to support the development of SOA-based solutions, leveraging the vast amount of data on web services currently available. On the other hand, SOA has mechanisms that can support the development of distributed, flexible, and reusable infrastructures for the use of deep learning. This paper presents a literature survey and discusses how SOA can be enabled by as well as facilitate the use of deep learning approaches in different types of environments for different levels of users.

Fault Prediction in SOA-Based Systems Using Deep Learning Techniques

2020 ◽  
Vol 17 (3) ◽  
pp. 1-19
Author(s):  
Guru Prasad Bhandari ◽  
Ratneshwer Gupta
Keyword(s):  
Deep Learning ◽  
Web Services ◽  
Service Oriented Architecture ◽  
Early Stage ◽  
System Development ◽  
Fault Prediction ◽  
Development Lifecycle ◽  
Learning Techniques ◽  
Service Oriented ◽  
And Performance

Fault prediction in Service Oriented Architecture (SOA) based systems is one of the important tasks to minimize the computation cost and time of the software system development. Predicting the faults and discovering their locations in the early stage of the system development lifecycle makes maintenance processes easy and improves the resource utilization. In this paper, the authors proposed the fault prediction model for SOA-based systems by utilizing the deep learning techniques. Twenty-one source code metrics are applied to different web services projects. The web services datasets are constructed by injecting the faults into it, and metrics are extracted for both faulty and nonfaulty data for training and testing purpose. Moreover, different deep learning techniques are inspected for fault prediction of web services and performance of different methods are compared by using standard performance measures. From the experimental results, it is observed that deep learning techniques provide effective results and applicable to the real-world SOA-based systems.

PROCESS MODEL ONTOLOGY-BASED MATCHMAKING OF SEMANTIC WEB SERVICES

2011 ◽  
Vol 20 (04) ◽  
pp. 357-370 ◽  
Author(s):  
D. PAULRAJ ◽  
S. SWAMYNATHAN ◽  
M. MADHAIYAN
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Process Model ◽  
Service Discovery ◽  
Service Oriented Architecture ◽  
Semantic Web Services ◽  
Functional Part ◽  
Service Oriented ◽  
Concise Description

One of the key challenges of the Service Oriented Architecture is the discovery of relevant services for a given task. In Semantic Web Services, service discovery is generally achieved by using the service profile ontology of OWL-S. Profile of a service is a derived, concise description and not a functional part of the semantic web service. There is no schema present in the service profile to describe the input, output (IO), and the IOs in the service profile are not always annotated with ontology concepts, whereas the process model has such a schema to describe the IOs which are always annotated with ontology concepts. In this paper, we propose a complementary sophisticated matchmaking approach which uses the concrete process model ontology of OWL-S instead of the concise service profile ontology. Empirical analysis shows that high precision and recall can be achieved by using the process model-based service discovery.

A novel two-stage method of plant seedlings classification based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Tianhong Dai ◽  
Shijie Cong ◽  
Jianping Huang ◽  
Yanwen Zhang ◽  
Xinwang Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Technology ◽  
Two Stage ◽  
Second Stage ◽  
Stage Classification ◽  
Different Types ◽  
Two Stages ◽  
Plant Seedlings

In agricultural production, weed removal is an important part of crop cultivation, but inevitably, other plants compete with crops for nutrients. Only by identifying and removing weeds can the quality of the harvest be guaranteed. Therefore, the distinction between weeds and crops is particularly important. Recently, deep learning technology has also been applied to the field of botany, and achieved good results. Convolutional neural networks are widely used in deep learning because of their excellent classification effects. The purpose of this article is to find a new method of plant seedling classification. This method includes two stages: image segmentation and image classification. The first stage is to use the improved U-Net to segment the dataset, and the second stage is to use six classification networks to classify the seedlings of the segmented dataset. The dataset used for the experiment contained 12 different types of plants, namely, 3 crops and 9 weeds. The model was evaluated by the multi-class statistical analysis of accuracy, recall, precision, and F1-score. The results show that the two-stage classification method combining the improved U-Net segmentation network and the classification network was more conducive to the classification of plant seedlings, and the classification accuracy reaches 97.7%.

Current Trends in Software as a Service (SaaS)

2018 ◽  
Vol 6 (2) ◽  
pp. 221-234
Author(s):  
T.C. Sandanayake ◽  
P.G.C. Jayangani
Keyword(s):  
Service Oriented Architecture ◽  
Software As A Service ◽  
Application Service Provider ◽  
Current Trends ◽  
Application Service ◽  
Emerging Trends ◽  
Data Application ◽  
Service Oriented ◽  
Level Model ◽  
High Level

Software as a service (SaaS) is one type of the cloud computing that has gained more popularity in the world. It is a way of delivering the software through the internet to its end users. Then users can use it through subscriptions from vendors.  Users have to pay only for what they use. SaaS architecture is a very high level model which is based on Application Service Provider (ASP) concept and Service Oriented Architecture. Currently many organizations are using SaaS as it is a service centric model and it uses technologies like multi-tenant architecture which in turn provides the users with many desired set of features. SaaS also have some security challenges which can be classified under data, application and deployment of SaaS architecture. Furthermore there are many emerging trends in SaaSwhich are focused on full filling advanced customer demands. This research study is evaluating the current trends, approaches and applications of SAAS.

scholarly journals Deep Learning Approaches to Colorectal Cancer Diagnosis: A Review

2021 ◽  
Vol 11 (22) ◽  
pp. 10982
Author(s):  
Lakpa Dorje Tamang ◽  
Byung Wook Kim
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Digital Pathology ◽  
Learning Approaches ◽  
Diagnostic Systems ◽  
Future Health ◽  
Preclinical Phase ◽  
Different Types ◽  
Future Health Care ◽  
Effective Diagnosis

Unprecedented breakthroughs in the development of graphical processing systems have led to great potential for deep learning (DL) algorithms in analyzing visual anatomy from high-resolution medical images. Recently, in digital pathology, the use of DL technologies has drawn a substantial amount of attention for use in the effective diagnosis of various cancer types, especially colorectal cancer (CRC), which is regarded as one of the dominant causes of cancer-related deaths worldwide. This review provides an in-depth perspective on recently published research articles on DL-based CRC diagnosis and prognosis. Overall, we provide a retrospective synopsis of simple image-processing-based and machine learning (ML)-based computer-aided diagnosis (CAD) systems, followed by a comprehensive appraisal of use cases with different types of state-of-the-art DL algorithms for detecting malignancies. We first list multiple standardized and publicly available CRC datasets from two imaging types: colonoscopy and histopathology. Secondly, we categorize the studies based on the different types of CRC detected (tumor tissue, microsatellite instability, and polyps), and we assess the data preprocessing steps and the adopted DL architectures before presenting the optimum diagnostic results. CRC diagnosis with DL algorithms is still in the preclinical phase, and therefore, we point out some open issues and provide some insights into the practicability and development of robust diagnostic systems in future health care and oncology.

scholarly journals Ασύρματα δίκτυα αισθητήρων που υποστηρίζουν αρχιτεκτονικές υπηρεσιών ιστού

2013 ◽  
Author(s):  
Ιωακείμ Σαμαράς
Keyword(s):  
Web Services ◽  
Low Power ◽  
Wireless Sensors ◽  
Service Oriented Architecture ◽  
Personal Area Networks ◽  
Markup Language ◽  
Network Simulator ◽  
Wireless Personal Area Networks ◽  
Extensible Markup ◽  
Service Oriented

Σκοπός της παρούσας διδακτορικής διατριβής ήταν η σχεδίαση-υλοποίηση, προσομοίωση και μοντελοποίηση ασύρματων δικτύων αισθητήρων (ΑΔΑ) που βασίζονται στην αρχιτεκτονική IPv6 over low power wireless personal area networks (6LoWPAN) και υποστηρίζουν υπηρεσίες ιστού (web services) όπως επίσης και η υλοποίηση καινούριων τέτοιων υπηρεσιών καταλληλότερων για εφαρμογή στα προαναφερθέντα ΑΔΑ. Λόγω της έλλειψης που παρατηρείται στην παροχή εργαλείων για την εκπλήρωση του παραπάνω στόχου, αναπτύχθηκε ένα πειραματικό ΑΔΑ και ένα εργαλείο προσομοιωτικών μετρήσεων της επίδρασης των υπηρεσιών ιστού σε 6LoWPAN ΑΔΑ καθώς επίσης και ένα μαθηματικό μοντέλο για την μελέτη του πρωτοκόλλου ελέγχου προσπέλασης στο μέσο μετάδοσης (MAC) αυτών των δικτύων. Το προτεινόμενο MAC πρωτόκολλο για την 6LoWPAN αρχιτεκτονική είναι o χωρίς σχισμή (unslotted) CSMA/CA μηχανισμός του ΙΕΕΕ 802.15.4 προτύπου. Στα πλαίσια της παρούσας διδακτορικής διατριβής υλοποιήθηκε μια καινούρια στοίβα πρωτοκόλλων για υπηρεσίες ιστού η οποία ονομάστηκε Tiny service oriented architecture for wireless sensors (SOAWS). Το Tiny SOAWS προσφέρει μειωμένη κατανάλωση μνήμης, μειωμένο χρόνο εκτέλεσης καθώς επίσης και μειωμένα μεγέθη ανταλλασσόμενων μηνυμάτων σε σχέση με το πρότυπο device profile for web services (DPWS) το οποίο δημιουργήθηκε για την απευθείας ενσωμάτωση των υπηρεσιών ιστού σε συσκευές. Επίσης, το Tiny SOAWS υποστηρίζει την δημιουργία υπηρεσιών ιστού πάνω σε ασύρματους αισθητήρες που έχουν την ίδια σημασιολογία με τις αντίστοιχες υπηρεσίες ιστού του DPWS. Εκτός τούτου, υποστηρίζει μία καινούρια φόρμα μηνυμάτων, η οποία στηρίζεται στην extensible markup language (XML) όπως και η φόρμα μηνυμάτων του DPWS. Τα Tiny SOAWS και DPWS υλοποιήθηκαν πάνω σε πραγματικούς ασύρματους αισθητήρες και συγκρίθηκαν μεταξύ τους χρησιμοποιώντας το αναπτυχθέν πειραματικό ΑΔΑ το οποίο είναι αποτελεί ένα πραγματικό 6LoWPAN ΑΔΑ με τον μέγιστο αριθμό των ασύρματων αισθητήρων του να είναι 12. Με σκοπό την επικύρωση των παραπάνω μετρήσεων, την επέκτασή τους σε μεγαλύτερης κλίμακας ΑΔΑ καθώς επίσης και τη σύγκρισης των 2 προαναφερθέντων στοιβών πρωτοκόλλων με ένα DPWS βασισμένο σε δυαδική κωδικοποίηση (binary-based DPWS), χρησιμοποιήθηκε το αναπτυχθέν εργαλείο προσομοίωσης το οποίο υλοποιήθηκε στον προσομοιωτή network simulator (NS)-2. Επιβεβαιώθηκε η ορθή λειτουργία του πειραματικού ΑΔΑ και του εργαλείου προσομοίωσης συγκρίνοντας τις μετρήσεις του ενός με τις μετρήσεις του άλλου. Το γεγονός αυτό επιτρέπει τη χρήση τους για την αξιολόγηση και σχεδίαση 6LoWPAN ΑΔΑ που υποστηρίζουν υπηρεσίες ιστού. Επιπλέον, η σύγκριση έδειξε ότι το Tiny SOAWS υπερτερεί του DPWS. Ωστόσο, το binary-based DPWS αποτελεί την καλύτερη επιλογή. Παρόλα αυτά, η εφαρμογή του περιορίζεται σε ασύρματους αισθητήρες με συγκεκριμένο λογισμικό καθώς το σύνολο των κανόνων της XML στο οποίο στηρίζονται οι υπηρεσίες ιστού για να προσφέρουν διαλειτουργικότητα στο επίπεδο εφαρμογής δεν χρησιμοποιείται πλέον. Τέλος, οι προβλέψεις του αναπτυχθέντος μαθηματικού μοντέλου για τον unslotted μηχανισμό του MAC υπο-επιπέδου του ΙΕΕΕ 802.15.4 προτύπου συγκρίθηκαν με μετρήσεις από τον NS-2 και βρέθηκε ότι αποκλίνουν ελάχιστα. Ως εκ τούτου, μπορεί να χρησιμοποιηθεί ως εργαλείο αξιολόγησης της σχεδίασης ΑΔΑ τα οποία μπορούν μετέπειτα να υποστηρίξουν την 6LoWPAN αρχιτεκτονική καθώς επίσης και υπηρεσίες ιστού.

Design and Implementation of Network Management Architecture for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 3895-3899 ◽  
Author(s):  
Ray I Chang ◽  
Chi Cheng Chuang
Keyword(s):  
Web Services ◽  
Network Management ◽  
Service Oriented Architecture ◽  
Wireless Sensor ◽  
Memory Space ◽  
Loosely Coupled ◽  
Sensor Platforms ◽  
Management Architecture ◽  
Service Oriented ◽  
Network Management Architecture

Traditional NM (Network Management) techniques can not be applied on WSN (Wireless Sensor Network) due to its features of low computing ability, tiny memory space, and limited energy. A new NMA (Network Management Architecture) for WSN is needed. In this paper, we design a loosely coupled NMA of WSN based on SOA (Service-Oriented Architecture), and have well defined NM interfaces. Finally, we develop a SOA platform for WSN operations according to the NMA. Based on SOA platform, users can compose and use various NM Web Services by internet depending on their requirements. Heavy tasks which need a great deal of computing resources and storage are executed on the SOA platform. Thus, energy consumption and node computation can be decreased. Moreover, external applications use Web Services to integrate SOA platform for WSN. It lowers the difficulty in integrating different sensor platforms and heterogeneous devices.

A Theoretical Foundation of Demand Driven Web Services

2015 ◽  
pp. 392-422
Author(s):  
Zhaohao Sun ◽  
John Yearwood
Keyword(s):  
Web Services ◽  
Social Services ◽  
Service Oriented Architecture ◽  
State Of The Art ◽  
The State ◽  
Cloud Services ◽  
Pivotal Role ◽  
The Internet ◽  
Service Oriented ◽  
The Web

Web services are playing a pivotal role in business, management, governance, and society with the dramatic development of the Internet and the Web. However, many fundamental issues are still ignored to some extent. For example, what is the unified perspective to the state-of-the-art of Web services? What is the foundation of Demand-Driven Web Services (DDWS)? This chapter addresses these fundamental issues by examining the state-of-the-art of Web services and proposing a theoretical and technological foundation for demand-driven Web services with applications. This chapter also presents an extended Service-Oriented Architecture (SOA), eSMACS SOA, and examines main players in this architecture. This chapter then classifies DDWS as government DDWS, organizational DDWS, enterprise DDWS, customer DDWS, and citizen DDWS, and looks at the corresponding Web services. Finally, this chapter examines the theoretical, technical foundations for DDWS with applications. The proposed approaches will facilitate research and development of Web services, mobile services, cloud services, and social services.

Semantic Web Services-Based Knowledge Management Framework

2016 ◽  
pp. 429-438
Author(s):  
Vili Podgorelec ◽  
Boštjan Grašič
Keyword(s):  
Knowledge Management ◽  
Web Services ◽  
Semantic Web ◽  
Business Processes ◽  
Service Oriented Architecture ◽  
Semantic Web Services ◽  
Semantic Web Technologies ◽  
Management Framework ◽  
Knowledge Based ◽  
Service Oriented

In this chapter, a Semantic Web services-based knowledge management framework that enables holistic knowledge management in organizations is presented. As the economy is becoming one single global marketplace, where the best offer wins, organizations have to search for competitive advantage within themselves. With the growing awareness that key potentials of an organization lie within its people and their knowledge, efficient knowledge management is becoming one of key focuses in organizational activities. The proposed knowledge management framework is based on Semantic Web technologies and service-oriented architecture, supporting the operational business processes as well as knowledge-based management of services in service-oriented architecture.

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