GET Requests Research Articles

Networking Aspects of the Electronic Health Records: Hypertext Transfer Protocol Version 2 (HTTP/2) vs HTTP/3.

The rapid development of the digital healthcare and the electronic health records (EHR) requires smooth networking infrastructure to access data using Hypertext Transfer Protocol (HTTP)-based applications. The new HTTP/3 standard should provide performance and security improvements over HTTP/2. The goal of our work was to test the performance of HTTP/2 and HTTP/3 in the context of the EHRs. We used 45,000 test FHIR Patient resources downloaded and uploaded using 20, 50, 100 and 200 resources per Bundle, which resulted in 2251, 901, 451 and 226 HTTP GET and POST requests respectively. The first test downloading 20 resources per Bundle showed that HTTP/3 outperformed HTTP/2 in the local (mean request time 16.57 ms ± 7.2 standard deviation [SD]) and in the remote network (71.45 ms ± 43.5 SD) which is almost 3 times faster. In the 50 and 100 resources per Bundle test the HTTP/3 protocol demonstrated again more than two times gain in downloading performance for remote requests with mean request time 91.13 ms ± 34.54 SD and 88.09 ms ± 21.66 SD respectively. Furthermore, HTTP/3 outperformed HTTP/2 in the constructed clinical dataset remote transfer. In the upload tests HTTP/3 showed only a slight gain in performance merely in the remote network. The HTTP/3 protocol is a relatively new development and a major improvement for the worldwide web. This new technology is still missing in the digital health and EHRs. Its use could offer a major performance gain in situations where data is gathered from multiple remote locations.

WarenstromInfo: a tool for the easy extraction and visualisation of trade flow data

Epidemiological outbreak investigations often prove to be lengthy and inconclusive due to the time-consuming nature of the currently-used approaches. An alternative approach to address these challenges could involve the application of algorithms to support authorities and food business operators by providing timely, relevant and reliable information. Algorithms, such as gravity models, could be applied as commodity trade models, but they require a large amount of reliable and consistent data on trade for generating projections at international, national or even regional level. Several trade databases, such as UN COMTRADE, EUROSTAT, BACI, CHELEM and GTAP, provide information on trace, albeit with variations in the provided information and in the structure. However, it is worth noting that not all of these databases are freely accessible and data management can pose challenges, hampering the access to the trade data. WarenstromInfo (WI) was created as a software solution that allows easy trade data extraction and visualisation for application in different areas, such as outbreak investigations. WarenstromInfo (WI) is an application tool that automatically extracts, decodes and visually displays trade flow data from EUROSTAT "EU trade since 2002 by statistical procedure, by HS2-4-6 and CN8 (DS-059322)" (hereinafter referred to EUROSTAT) and the BACI databases, based on user input. WI was developed by using the open-source desktop software KNIME Analytics Platform. WI offers the flexibility to be executed either as a web service on a KNIME Web Server infrastructure or as a local resource. To integrate the BACI database into WI, the database is annually downloaded as csv files, rebuilt as a SQLite database and hosted locally into the KNIME Web Server Infrastructure. In order to optimise storage space on the KNIME server, this SQLite database specifically includes only agrifood data, reflecting the tool´s focus. However, if new objectives are established, this database can be expanded. Further, data of the SQLite database can be customised by executing the WI workflow locally, enabling the user to expand the database at any time. In contrast to BACI, trade data extraction from the EUROSTAT database is performed via the EUROSTAT’s API (Application Programming Interface) applying GET requests and XML data management. WI displays four User-friendly Interfaces (UIs) designed with interactive KNIME nodes that facilitate the input of variables. The extracted trade flow data are shown through interactive tables directly within the UIs. This feature enables users to easily explore the data in a structured and user-friendly manner. Additionally, WI incorporates the extracted trade flow data into maps. These maps provide a visual representation of the data, allowing users to gain insights and identify patterns and trends geographically. Both, the data table and the maps, can be downloaded as a single Excel file (containing multiple preformatted tables) and as png files, respectively.

Metamorphic Testing for Web System Security

Security testing aims at verifying that the software meets its security properties. In modern Web systems, however, this often entails the verification of the outputs generated when exercising the system with a very large set of inputs. Full automation is thus required to lower costs and increase the effectiveness of security testing. Unfortunately, to achieve such automation, in addition to strategies for automatically deriving test inputs, we need to address the oracle problem, which refers to the challenge, given an input for a system, of distinguishing correct from incorrect behavior (e.g., the response to be received after a specific HTTP GET request). In this paper, we propose Metamorphic Security Testing for Web-interactions ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MST-wi</i> ), a metamorphic testing approach that integrates test input generation strategies inspired by mutational fuzzing and alleviates the oracle problem in security testing. It enables engineers to specify metamorphic relations (MRs) that capture many security properties of Web systems. To facilitate the specification of such MRs, we provide a domain-specific language accompanied by an Eclipse editor. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MST-wi</i> automatically collects the input data and transforms the MRs into executable Java code to automatically perform security testing. It automatically tests Web systems to detect vulnerabilities based on the relations and collected data. We provide a catalog of 76 system-agnostic MRs to automate security testing in Web systems. It covers 39% of the OWASP security testing activities not automated by state-of-the-art techniques; further, our MRs can automatically discover 102 different types of vulnerabilities, which correspond to 45% of the vulnerabilities due to violations of security design principles according to the MITRE CWE database. We also define guidelines that enable test engineers to improve the testability of the system under test with respect to our approach. We evaluated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MST-wi</i> effectiveness and scalability with two well-known Web systems (i.e., Jenkins and Joomla). It automatically detected 85% of their vulnerabilities and showed a high specificity (99.81% of the generated inputs do not lead to a false positive); our findings include a new security vulnerability detected in Jenkins. Finally, our results demonstrate that the approach scale, thus enabling automated security testing overnight.

Comparison of virtualization methods at operating system level

The aim of the work is comparative analysis of three tools for application container’s orchestration: Kubernetes 1.2.2, Docker Swarm 1.24 and Nomad Hashicorp 1.2.0. For this purpose, test application was implemented, responding requests, then it was contenerized using Docker. For each tool, the scenario aimed at measuring pods startup time. The research was repeated three times. During each repetition number of replics were increased. Simultaneously with startup time test, CPU load and memory strain were measured. In comparison also time of regeneration was taken into consideration, what was realized by gauging time of response for GET request. The analysis showed that Docker Swarm in terms of most of the criteria examined in this work turned out as the best orchestration tool.

Web Service Sistem Informasi Terpadu (SIMIPA) Menggunakan REST API

SIMIPA web service is a service that is used to provide services in the form of information to the Android mobile apps, is the Student module, the Lecturer module, and the Parent module. The service provided uses the REST API as a bridge between the server and the client. The goal is that the REST API can be accessed on the Android mobile apps. The development of web services in this study uses the Scrum development method which has 26 product backlogs with 9 iterations of sprints. Each sprint has several stages, namely sprint planning, daily sprint, sprint review, and sprint retrospective. Web services developed using the PHP programming language and MySQL database. The result of this research is the SIMIPA REST API which can be accessed on the Android front-end. Android accesses the REST API via the GET and POST request methods using a URL that generates a JSON response. Based on several tests, the SIMIPA REST API URL is said to have been successfully developed and can be accessed on Android mobile apps according to the expected response. Data security using the REST API is focused on the POST method using JSON Web Token (JWT).

Does TDWG Need an API Design Guideline?

RESTful APIs (REpresentational State Transfer Application Programming Interfaces) are the most commonly used mechanism for biodiversity informatics databases to provide open access to their content. In its simplest form an API provides an interface based on the HTTP protocol whereby any client can perform an action on a data resource identified by a URL using an HTTP verb (GET, POST, PUT, DELETE) to specify the intended action. For example, a GET request to a particular URL (informally called an endpoint) will return data to the client, typically in JSON format, which the client converts to the format it needs. A client can either be custom written software or commonly used programs for data analysis such as R (programming language), Microsoft Excel (everybody’s favorite data management tool), OpenRefine, or business intelligence software. APIs are therefore a valuable mechanism for making biodiversity data FAIR (findable, accessible, interoperable, reusable). There is currently no standard specifying how RESTful APIs should be designed, resulting in a variety of URL and response data formats for different APIs. This presents a challenge for API users who are not technically proficient or familiar with programming if they have to work with many different and inconsistent data sources. We undertook a brief review of eight existing APIs that provide data about taxa to assess consistency and the extent to which the Darwin Core standard (Wieczorek et al. 2021) for data exchange is applied. We assessed each API based on aspects of URL construction and the format of the response data (Fig. 1). While only cursory and limited in scope, our survey suggests that consistency across APIs is low. For example, some APIs use nouns for their endpoints (e.g. ‘taxon’ or ‘species’), emphasising their content, whereas others use verbs (e.g. ‘search’), emphasising their functionality. Response data seldom use Darwin Core terms (two out of eight examples) and a wide range of terms can be used to represent the same concept (e.g. six different terms are used for dwc:scientificNameAuthorship). Terms that can be considered metadata for a response, such as pagination details, also vary considerably. Interestingly, the public interfaces for the majority of APIs assessed do not provide POST, PUT or DELETE endpoints that modify the database. POST is only used for providing more detailed request bodies to retrieve data than possible with GET. This indicates the primary use of APIs by biodiversity informatics platforms for data sharing. An API design guideline is a document that provides a set of rules or recommendations for how APIs should be designed in order to improve their consistency and useability. API design guidelines are typically created by particular organizations to standardize API development within the organization, or as a guideline for programmers using an organization’s software to build APIs (e.g., Microsoft and Google). The API Stylebook is an online resource that provides access to a wide range of existing design guidelines, and there is an abundance of other resources available online. This presentation will cover some of the general concepts of API design, demonstrate some examples of how existing APIs vary, and discuss potential options to encourage standardization. We hope our analysis, the available body of knowledge on API design, and the collective experience of the biodiversity informatics community working with APIs may help answer the question “Does TDWG need an API design guideline?”

The comparative analysis of web applications frameworks in the Node.js ecosystem

The subject of the research was the comparative analysis of three frameworks for building web applications, i.e. Express, Hapi and Koa, operating in the Node.js ecosystem. An experiment was prepared consisting of a number of scenarios, during which the server response times to incoming requests from the client were measured. As part of the work, server test applications handling HTTP requests (GET, POST, PUT, DELETE) performing typical data operations were implemented. The applications contained the same functionalities and were built using the three tested frameworks. In individual scenarios, 1000 requests of a given type were sent from independent clients, the times of successive responses were measured and their averages were calculated. On the basis of the obtained results, Hapi and Koa frameworks for GET, POST, PUT, DELETE requests, operating on one object or a string "Hello World!" have achieved the best, although very similar, response times. In the case of the GET request, the Koa framework proved to be the best for higher loads, achieving response times approximately 20% better than the Express framework. For high loads, the Hapi framework achieved the worst results, reaching over 2 times longer response times than the Koa framework.

Enhanced Detection Algorithms to Detect HTTP DDoS

A web application utilizes Hypertext Transfer Protocol (HTTP) to surf client requests. This protocol is used widely, especially in business areas such as in online transactions and websites, including in government websites. A client delivers information to a server carried by a client web browser. An HTTP distributed denial of service (DDoS) attack occurs when the attacker is able to mimic client information, which makes a DDoS attack at the application layer difficult to distinguish as the traffic pattern is similar to a genuine request. Furthermore, it is not compulsory for the client to present the GET headers component to a web server during the GET request transaction. Existing detection of HTTP DDoS attacks still faces challenges in differentiating between authentic and bogus GET requests in real time. In this paper, a fast algorithm (FARGO) method to detect HTTP DDoS attacks is introduced. FARGO consists of three detection algorithms to recognize HTTP DDoS categories as request flooding attacks. The assessment of the proposed detection system was conducted in real experimental conditions with real attack scripts. The proposed detection method provided expected outcomes with improvements of 11.30% for true positive rates and 8.9% for false-positive rates.

A Device for Remote Monitoring of Solar Power Plant Parameters

The need for application of a device for online remote monitoring of electrical parameters and the operability of photovoltaic converters of solar power plants is justified in the context of the problems encountered in the Sevastopol Solar Power Plant (S. Energy Sevastopol LLC) operation. A structural diagram of the device showing the connection and purpose of its main functional components is presented. The circuit is based on an ATmega 328p microcontroller, which transfers processed data from the sensors to the server by sending a GET request using a W5100 Wiznet Ethernet controller. Such a solution allows for a high data transfer rate—up to 25 Mbps—and provides a simple connection to the Internet independently from operating systems and external computers. The characteristics and performance analysis of galvanically isolated sensors used in the device are presented, such as a current sensor based on an Allegro ACS712 integrated current sensor, and a voltage sensor based on the transistor optocoupler. The results of the device operation illustrating the photovoltaic plant daily operation on a sunny fall day are provided. The device provides for continuous monitoring of the operation of the photovoltaic converters with long-term storage of measured values in graphical and numerical form, which makes it possible for operational and dispatching personnel to visually analyze the plant operation, monitor its performance, compare key performance indicators of various sections, and obtain production reports by periods with plotting of curves, as well as receive alarm signals.

Lightweight IoT middleware for rapid application development

Sensors connected to the cloud services equipped with data analytics has created a plethora of new type of applications ranging from personal to an industrial level forming to what is known today as Internet of Things (IoT). IoT-based system follows a pattern of data collection, data analytics, automation, and system improvement recommendations. However, most applications would have its own unique requirements in terms of the type of the smart devices, communication technologies as well as its application provisioning service. In order to enable an IoT-based system, various services are commercially available that provide services such as backend-as-a-service (BaaS) and software-as-a-service (SaaS) hosted in the cloud. This, in turn, raises the issues of security and privacy. However there is no plug-and-play IoT middleware framework that could be deployed out of the box for on-premise server. This paper aims at providing a lightweight IoT middleware that can be used to enable IoT applications owned by the individuals or organizations that effectively securing the data on-premise or in remote server. Specifically, the middleware with a standardized application programming interface (API) that could adapt to the application requirements through high level abstraction and interacts with the application service provider is proposed. Each API endpoint would be secured using Access Control List (ACL) and easily integratable with any other modules to ensure the scalability of the system as well as easing system deployment. In addition, this middleware could be deployed in a distributed manner and coordinate among themselves to fulfil the application requirements. A middleware is presented in this paper with GET and POST requests that are lightweight in size with a footprint of less than 1 KB and a round trip time of less than 1 second to facilitate rapid application development by individuals or organizations for securing IoT resources.

Proxy Cache Maintenance Using Multicasting in CoAP IoT Domains

In this paper, we consider Internet of Things (IoT) domain running multicasting constrained application protocol (CoAP) over IEEE 802.15.4 network ended by CoAP proxy/cache. We examine the features of CoAP multicasting in order to ensure freshness of data in the cache as a function of the leisure parameter which allows devices to reply in arbitrary (random) time periods after receiving multicast GET request. We also investigate communication delay in the IoT domain and daily energy consumption of devices under several leisure schemes which may be implemented at the application level or at the medium access control layer. The impact of the leisure parameter appears to be critical for congestion avoidance. We show that a combination of proactive and reactive cache update with appropriate multicast leisure scheme can achieve low probability of outdated data while limiting the energy expenditure of nodes to a satisfactory value. Furthermore, best performance with respect to delay is obtained when the leisure period is integrated in the CSMA/CA backoff process.

Open Astronomy Catalogs API

We announce the public release of the application program interface (API) for the Open Astronomy Catalogs (OACs), the OACAPI. The OACs serve near-complete collections of supernova, tidal disruption, kilonova, and fast stars data (including photometry, spectra, radio, and X-ray observations) via a user-friendly web interface that displays the data interactively and offers full data downloads. The OACAPI, by contrast, enables users to specifically download particular pieces of the OAC dataset via a flexible programmatic syntax, either via URL GET requests, or via a module within the astroquery Python package.

Entropy-Based Application Layer DDoS Attack Detection Using Artificial Neural Networks

Distributed denial-of-service (DDoS) attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention systems (IDS/IPS), mostly caused by application-layer DDoS attacks. Within this context, the objective of the paper is to detect a DDoS attack using a multilayer perceptron (MLP) classification algorithm with genetic algorithm (GA) as learning algorithm. In this work, we analyzed the standard EPA-HTTP (environmental protection agency-hypertext transfer protocol) dataset and selected the parameters that will be used as input to the classifier model for differentiating the attack from normal profile. The parameters selected are the HTTP GET request count, entropy, and variance for every connection. The proposed model can provide a better accuracy of 98.31%, sensitivity of 0.9962, and specificity of 0.0561 when compared to other traditional classification models.

Network-based video freeze detection and prediction in HTTP adaptive streaming

Given the popularity of HTTP adaptive streaming (HAS) technology for media delivery over mobile and fixed networks, the clients Quality of Experience (QoE) for HAS video sessions is of particular interest for network providers and Content Delivery Network (CDN) operators. Despite that, network providers are not able to directly obtain QoE-relevant metrics such as video freezes, initial buffering time, and the frequency of quality switches from the client. This paper proposes a scalable machine learning (ML) based scheme that offline detects and online predicts video freezes using a few features extracted from the network-based monitoring data, i.e., a sequence of HTTP GET requests sent from the video client. We determine the discriminative features for detecting video freezes based on multi-scale windows using the criterion of information gain (IG). Four traditional classifiers are investigated and the C4.5 decision tree is selected because of its simplicity, scalability, accuracy, and interpretability. Our approach for session-based offline freeze detection is evaluated on the Apple HTTP Live Streaming video sessions obtained from a number of operational CDN nodes and on the traces of Microsoft Smooth Streaming video sessions acquired in a controlled lab environment. Experimental results show that, even with the disturbance of user interactivity, an accuracy of about 91% can be obtained for the detection of a video freeze, a long video freeze, and multiple video freezes. The experiments for the online freeze prediction show that more than 30% of the video freezes can be foreseen one segment in advance.

Rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive

The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment information. Data are served through the NRFA web services via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for flow and rainfall data, respectively. Visualization examples are also provided with a shiny web application and functions provided in the package. Although this package is regional specific, the general framework and structure could be applied to similar databases.

Hierarchical Cache Performance Analysis Under TTL-Based Consistency

This paper introduces an analytical model for characterizing the instantaneous hit ratio and instantaneous average hit distance of a traditional least recently used (LRU) cache hierarchy. The analysis accounts for the use of two variants of the Time-to-Live (TTL) weak consistency mechanism. The first is the typical TTL scheme (TTL-T) used in the HTTP/1.1 protocol where expired objects are refreshed using conditional GET requests. The second is TTL immediate ejection (TTL-IE) where objects are ejected as soon as they expire. The analysis also accounts for two sharing protocols: Leave Copy Everywhere (LCE) and Promote Cached Objects (PCO). PCO is a new sharing protocol introduced in this paper that decreases the user's perceived latency and is robust under nonstationary access patterns.

Building a high-performance key–value cache as an energy-efficient appliance

Key–value (KV) stores have become a critical infrastructure component supporting various services in the cloud. Long considered an application that is memory-bound and network-bound, recent KV-store implementations on multicore servers grow increasingly CPU-bound instead. This limitation often leads to under-utilization of available bandwidth and poor energy efficiency, as well as long response times under heavy load. To address these issues, we present Hippos, a high-throughput, low-latency, and energy-efficient key–value store implementation. Hippos moves the KV store into the operating system’s kernel and thus removes most of the overhead associated with the network stack and system calls. Hippos uses the Netfilter framework to quickly handle UDP packets, removing the overhead of UDP-based GET requests almost entirely. Combined with lock-free multithreaded data access, Hippos removes several performance bottlenecks both internal and external to the KV-store application.We prototyped Hippos as a Linux loadable kernel module and evaluated it against the ubiquitous Memcached using various micro-benchmarks and workloads from Facebook’s production systems. The experiments show that Hippos provides some 20%–200% throughput improvements on a 1 Gbps network (up to 590% improvement on a 10 Gbps network) and 5%–20% saving of power compared with Memcached.

TU‐F‐BRD‐01: Automatic Segmentation of Multiple Pelvic Organs On a Web‐Based Image Processing and Plan Evaluation Platform (WIPPEP)

Purpose:To present a novel automatic segmentation method for multiple pelvic organs and integrate into the web‐based image processing and plan evaluation platform (WIPPEP) to provide easy access through a web browser and leverage the power of cloud for faster computation.Methods:This segmentation method uses principal component analysis to model organ shapes and hierarchical clustering to model the appearance of each organ surface patch. Coarse and refined segmentation are done iteratively for each surface patch to find the best reference patch profile via a hierarchical cluster decision tree. Final segmentation is obtained using the generated global reference profile. The user chooses the CT image data to be segmented from the image server; the image volume is then visualized in the web browser and an HTTP POST request is sent to the computation server by clicking a button. When the computation server receives the segmentation request, it would then send an HTTP GET request to the image server to download the image volumes, call the segmentation program, and eventually send the segmentation results back to the web server. The segmentation results are transferred in JSON format and quickly passed to the canvas element in the web browser to display the contours.Results:For 5 test patients, the average DICE overlaps for prostate, bladder and rectum were 0.75, 0.78 and 0.57, respectively. With the platform running on hospital intranet, it took 20 seconds to load CT image volume to the web‐browser and 80 seconds to receive segmentation results from the computation server.Conclusion:This system allows users to access image data and send segmentation requests from a web browser, perform segmentation on a computation server, and quickly visualize resulting segmentation contours on a web browser. The software prototype achieves auto‐segmentation of prostate, bladder and rectum with moderate accuracy in a minute's timeframe.

ARQUITECTURA DE BÚSQUEDA PARA REPOSITORIOS DE OBJETOS DE APRENDIZAJE

With the emergence of Repositories of Learning Objects, and for a more efficient use of them, different search engines have been developed that allow users to easily and effectively find the materials they need. There are many engines that are based on keywords, but these limit the search area, some based on ontologies and others like the one used, based on the metadata that describe learning objects. A very powerful engine is SOLR, this is based on the LUCENE library, which runs as a Web application in Java, allowing documents to be sent to be indexed via HTTP and consulted using HTTP GET requests. The experiments carried out with the tool implemented based on this engine demonstrate the efficiency and quality of the results with respect to the other engines.

Thin servers with smart pipes

Distributed in-memory key-value stores, such as memcached, are central to the scalability of modern internet services. Current deployments use commodity servers with high-end processors. However, given the cost-sensitivity of internet services and the recent proliferation of volume low-power System-on-Chip (SoC) designs, we see an opportunity for alternative architectures. We undertake a detailed characterization of memcached to reveal performance and power inefficiencies. Our study considers both high-performance and low-power CPUs and NICs across a variety of carefully-designed benchmarks that exercise the range of memcached behavior. We discover that, regardless of CPU microarchitecture, memcached execution is remarkably inefficient, saturating neither network links nor available memory bandwidth. Instead, we find performance is typically limited by the per-packet processing overheads in the NIC and OS kernel---long code paths limit CPU performance due to poor branch predictability and instruction fetch bottlenecks. Our insights suggest that neither high-performance nor low-power cores provide a satisfactory power-performance trade-off, and point to a need for tighter integration of the network interface. Hence, we argue for an alternate architecture---Thin Servers with Smart Pipes (TSSP)---for cost-effective high-performance memcached deployment. TSSP couples an embedded-class low-power core to a memcached accelerator that can process GET requests entirely in hardware, offloading both network handling and data look up. We demonstrate the potential benefits of our TSSP architecture through an FPGA prototyping platform, and show the potential for a 6X-16X power-performance improvement over conventional server baselines.