Comparative analysis of data reading performance from the Salesforce platform using GraphQL, REST and SOAP interfaces

The article describes a comparative analysis of data reading from tables in the Salesforce environment using three different application programming interfaces. The popularity of the Salesforce platform and the release of the GraphQL interface on October 5, 2022 contributed to the study. No such study specifically for the Salesforce platform was found in the literature. The performance of reading data from the Salesforce platform was investigated using an automation script. For four tables containing a different number of rows, 8 types of queries were repeatedly executed using each of the three interfaces. It was found that depending on the number of rows, either REST API or SOAP API should be considered. In all cases, the lowest performance was observed while using GraphQL API

Cloud and Application Programming Interface – Issues and Developments

T Cloud computing is a unique IT paradigm that is fast gaining popularity in organizations and enterprises. The cloud has made it possible to store vast amount of data based on infrastructure provided by cloud service providers. The users are able to scale storage up or down on demand. The users are also able to utilize applications already deployed on the cloud by the cloud service providers. Other cloud service providers such as OpenNebula, CloudStack and OpenStack have made it possible to develop applications and deploy them on the cloud. Application programming interfaces (APIs) are available to guarantee such deployment. As the name implies, APIs serve as interfaces between programs. The interface is usually between a software developer and software developer’s application. Basically, the API allows one software to access some functionalities of another software. This paper examines present trends in the area of API and provides a guide for future research. Papers published in journals, conferences, white papers and those published in reputable magazines were analysed. The expected result at the end of this review is the identification of trends in API. This will be of benefit to prospective cloud users and even cloud providers

GLT: A Unified API for Lightweight Thread Libraries

In recent years, several lightweight thread (LWT) libraries have emerged to tackle exascale challenges. These offer programming models (PMs) based on user-level threads and incorporate their own lightweight mechanisms. However, each library proposes its own PM, exposing different semantics and hindering portability. To address this drawback, we have designed Generic Lightweight Thread (GLT), an application programming interface that frames the functionality of the most popular LWT libraries for high-performance computing under a single PM. We implement GLT on top of Argobots, MassiveThreads, and Qthreads. We provide GLT as a dynamic library, as well as in the form of a static version based on macro preprocessing resolution to reduce overhead. This paper discusses the GLT PM and demonstrates its minimal performance impact.Researchers from the Universitat Jaume I de Castelló were supported by project TIN2014-53495-R of the MINECO, the Generalitat Valenciana fellowship programme Vali+d 2015, and FEDER. Antonio J. Peña is cofinancied by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva fellowship number IJCI-2015-23266. This work was partially supported by the U.S. Dept. of Energy, Office of Science, Office of Advanced Scientific Computing Research (SC-21), under contract DE-AC02-06CH11357.Peer ReviewedPostprint (author's final draft

Arquiteturas federadas para integração de dados biomédicos

Doutoramento Ciências da ComputaçãoThe last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.A adoção sucessiva das tecnologias de comunicação e de informação na área da saúde tem permitido um aumento na diversidade e na qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado uma enorme quantidade de dados, cujo valor científico está ainda por explorar. A partilha e o acesso integrado a esta informação poderá permitir a identificação de novas descobertas que possam conduzir a melhores diagnósticos e a melhores tratamentos clínicos. Esta tese propõe novos modelos de integração e de exploração de dados com vista à extração de conhecimento biomédico a partir de múltiplas fontes de dados. A primeira contribuição é uma arquitetura baseada em nuvem para partilha de serviços de imagem médica. Esta solução oferece um mecanismo de registo simplificado para fornecedores e serviços, permitindo o acesso remoto e facilitando a integração de diferentes fontes de dados. A segunda proposta é uma arquitetura baseada em sensores para integração de registos electrónicos de pacientes. Esta estratégia segue um modelo de integração federado e tem como objetivo fornecer uma solução escalável que permita a pesquisa em múltiplos sistemas de informação. Finalmente, o terceiro contributo é um sistema aberto para disponibilizar dados de pacientes num contexto europeu. Todas as soluções foram implementadas e validadas em cenários reais

Cloud Computing Present Limitations and Future Trends

Cloud computing is still in its early stage. There are several companies, both big and small, that provide a diverse range of cloud-based services. There are several types of apps, such as complete programs, support services, mail filtering services, and storage services. IT professionals have become used to using some of the many cloud-based services as business requirements required. Cloud computing aggregators and integrators, on the other hand, are already developing, providing bundles of goods and services as a single point of access to the cloud. This research attempts to explore the current limitations and future trends of cloud computing. More specifically, this research discusses current limitations such as limited control, Cloud outage, Vendor lock-in, Cloud security, Energy consumption and the future trends to combat these limitations such as Edge computing, Hybrid and Multi-Cloud solutions, green cloud computing, serverless computing

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja