Mission Critical Messaging Using Multi-Access Edge Computing

Abstract 5th Generation (5G) mobile system is expected to support the requirements of mission critical communications for ultra reliability and availability, and very low latency. With the development of messaging and data transfer in mobile networks, mission critical communication users see more and more potential in data communications. In this paper, we explore the capabilities of Multi-access Edge Computing (MEC) that appears to be a key 5G component, to provide short messaging service at the network edge. The provided use cases illustrate the capabilities for transferring mobile originating and mobile terminating short messages to and from mission critical mobile edge applications. The data model describes the service resource structure and the Application Programming Interface definitions illustrate how the mobile edge applications can use the service. Some implementation aspects related to behavioral logic of the network and applications are provided. The performance analysis enables estimation of latency introduced by the service.

Download Full-text

Arangopipe, a tool for machine learning meta-data management

Data Science ◽

10.3233/ds-210034 ◽

2021 ◽

pp. 1-15

Author(s):

Jörg Schad ◽

Rajiv Sambasivan ◽

Christopher Woodward

Keyword(s):

Machine Learning ◽

Life Cycle ◽

Open Source ◽

Data Model ◽

Application Programming Interface ◽

Learning Models ◽

Essential Components ◽

Application Programming ◽

Programming Interface ◽

Machine Learning Models

Experimenting with different models, documenting results and findings, and repeating these tasks are day-to-day activities for machine learning engineers and data scientists. There is a need to keep control of the machine-learning pipeline and its metadata. This allows users to iterate quickly through experiments and retrieve key findings and observations from historical activity. This is the need that Arangopipe serves. Arangopipe is an open-source tool that provides a data model that captures the essential components of any machine learning life cycle. Arangopipe provides an application programming interface that permits machine-learning engineers to record the details of the salient steps in building their machine learning models. The components of the data model and an overview of the application programming interface is provided. Illustrative examples of basic and advanced machine learning workflows are provided. Arangopipe is not only useful for users involved in developing machine learning models but also useful for users deploying and maintaining them.

Download Full-text

Mobile Networks and Indian Agricultural Sector

Advances in Wireless Technologies and Telecommunication - Routing Protocols and Architectural Solutions for Optimal Wireless Networks and Security ◽

10.4018/978-1-5225-2342-0.ch004 ◽

2017 ◽

pp. 60-79 ◽

Cited By ~ 1

Author(s):

Lokesh Jain ◽

Harish Kumar

Keyword(s):

Mobile Networks ◽

Information Dissemination ◽

Agricultural Sector ◽

Fuzzy Rule ◽

Mobile Network ◽

Application Programming Interface ◽

Application Architecture ◽

Information And Communication ◽

Application Programming ◽

Programming Interface

Information dissemination in agricultural sector for its growth using information and communication technology (ICT) as a tool is need of the hour. This can be achieved using information systems. ICT benefits are helpful in exchange and dissemination of information among farming stakeholders. By using the latest tool of mobile technology, farmers can get the current information related to their farming jobs around the clock and at any location, as the mobile network have touched every part/location of the India. Using the features of the mobile-phones like GPS etc. one can get the localized information. Only need is to structure the abundant information available across the various organizations. So, a mobile based agricultural information system framework ‘mAgIDS' has been proposed employing the hybrid mobile application architecture approach. Client-server architecture using the location Application Programming Interface (API) has been proposed. Inference mechanism of the system has implemented on the basis of improved fuzzy rule promotion technique.

Download Full-text

The Paleobiology Database application programming interface

Paleobiology ◽

10.1017/pab.2015.39 ◽

2015 ◽

Vol 42 (1) ◽

pp. 1-7 ◽

Cited By ~ 23

Author(s):

Shanan E. Peters ◽

Michael McClennen

Keyword(s):

Real Time ◽

Data Model ◽

Application Programming Interface ◽

Scientific Workflows ◽

Scientific Applications ◽

Database Application ◽

Occurrence Data ◽

Analysis Tools ◽

Application Programming ◽

Programming Interface

AbstractThe Paleobiology Database (PBDB; https://paleobiodb.org) consists of geographically and temporally explicit, taxonomically identified fossil occurrence data. The taxonomy utilized by the PBDB is not static, but is instead dynamically generated using an algorithm applied to separately managed taxonomic authority and opinion data. The PBDB owes its existence to many individuals, some of whom have entered more than 1.26 million fossil occurrences and over 570,000 taxonomic opinions, and some of whom have developed and maintained supporting infrastructure and analysis tools. Here, we provide an overview of the data model currently used by the PBDB and then briefly describe how this model is exposed via an Application Programming Interface (API). Our objective is to outline how PBDB data can now be accessed within individual scientific workflows, used to develop independently managed educational and scientific applications, and accessed to forge dynamic, near real-time connections to other data resources.

Download Full-text

Mobile Networks and Indian Agricultural Sector

Environmental and Agricultural Informatics ◽

10.4018/978-1-5225-9621-9.ch024 ◽

2020 ◽

pp. 516-535

Author(s):

Lokesh Jain ◽

Harish Kumar

Keyword(s):

Mobile Networks ◽

Information Dissemination ◽

Agricultural Sector ◽

Fuzzy Rule ◽

Mobile Network ◽

Application Programming Interface ◽

Application Architecture ◽

Information And Communication ◽

Application Programming ◽

Programming Interface

Download Full-text

DIN CWA 14050-1:2001-04, Erweiterungen für die Schnittstellenspezifikation für Finanzdienstleistungen (XFS)_- Version_3.0_- Teil_1: Application Programming Interface (API); Service Provider Interface (SPI); Programmierhandbuch (Englische Fassung CWA_14050-1:2000)

10.31030/9135296 ◽

2001 ◽

Keyword(s):

Service Provider ◽

Application Programming Interface ◽

Application Programming ◽

Programming Interface

Download Full-text

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

Jurnal ULTIMA InfoSys ◽

10.31937/si.v9i1.839 ◽

2018 ◽

Vol 9 (1) ◽

pp. 24-31

Author(s):

Rudianto Rudianto ◽

Eko Budi Setiawan

Keyword(s):

Application Programming Interface ◽

Third Party ◽

Image Content ◽

Image File ◽

Application Programming ◽

Index Terms ◽

Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

Download Full-text