The Alliance for Telecommunications Industry Solutions (ATIS) is an ANSI accredited standards development organization that develops technical and operational standards and solutions for the ICT industry. The home page for its standards development enterprise is linked below:
Two of its consensus products have entered a revision cycle:
Scope: This standard covers the minimum temperature, humidity, and altitude criteria for wireline and wireless telecommunications network equipment to be installed and utilized by service providers in controlled environmental spaces (e.g., Carrier Communication Spaces, Central Offices, MTSOs, Huts, CEVs, and customer premises). It describes test methodologies and test report criteria necessary for proper evaluation by interested parties, and those intending to deploy equipment in such environments (also called Class 1 environments).
This standard defines temperature and humidity ranges in which the equipment must operate, and provides test methodologies to evaluate equipment operation in those environments. The expectation is that equipment will continue to function properly and without degradation of performance when placed in these environments.
This standard covers the minimum temperature, humidity, and altitude criteria for telecommunications network equipment to be installed and utilized by service providers in controlled environmental spaces (e.g., Carrier Communication Spaces, COs, MTSOs, Huts, CEVs, and customer premises). It describes test methodologies and test report criteria necessary for proper evaluation by interested parties, and those intending to deploy equipment in such environments. The expectation is that equipment will continue to function properly and without any unexpected degradation of performance when placed in the temperature and humidity controlled environmental spaces defined in the standard. Equipment is also expected to function properly after exposure to other environmental stresses, such as experienced in high-altitude applications and during storage and transportation.
Scope. This standard covers the minimum temperature, humidity, altitude, and salt fog criteria for telecommunications network equipment to be installed and utilized by service providers in Outside Plant (OSP) environments. These environments include those found in OSP cabinets, enclosures, pedestals, etc., as well as those outside of protective enclosures. Test methodologies and test report criteria necessary for proper evaluation by interested parties and those intending to deploy equipment in such environments are also provided.
This document defines Environmental Classifications based on the temperature, humidity, altitude, and salt fog ranges in which the equipment must operate, and provides test methodologies to evaluate equipment operation in those environments. Based on the intended usage, network equipment could be placed in one or more of the “Environment Classifications”.
The expectation is that equipment will continue to function properly and without any unexpected degradation of performance when placed in these environments. Regardless of the operational environmental classification, equipment is expected to function properly after exposure to other environmental stresses, such as operational altitude and storage/transportation temperature-humidity. The test criteria defined in this document apply to all equipment.
Public consultation closes January 6th. In both cases, you may obtain an electronic copy from Drew Greco (dgreco@atis.org). Send comments to Drew (with optional copy to psa@ansi.org)
We keep all ATIS titles on the standing agenda of our Infotech colloquia. We collaborate with the IEEE Education & Healthcare Facilities Committee. See our CALENDAR for the next online meeting.
Issue: [16-138]
Category: Information & Communications Technology, Telecommunications
Colleagues: Mike Anthony, Jim Harvey, Mike Hiler, William McCoy, Keith Waters
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An Architectural Risk Analysis for Internet of Things (IoT) Services
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Dávid Haja – Balázs Vass – László Toka
Abstract: Data analysis is widely used in all domains of the economy. While the amount of data to process grows, the time criteria and the resource consumption constraints get stricter. These phenomena call for advanced resource orchestration for the big data applications. The challenge is actually even greater at the advent of edge computing: orchestration of big data resources in a hybrid edge-cloud infrastructure is challenging. The difficulty stems from the fact that wide-area networking and all its well-known issues come into play and affect the performance of the application. In this paper we present the steps we made towards network-aware big data application design over such distributed systems. We propose a HDFS block placement algorithm for the network reliability problem we identify in geographically distributed topologies. The heuristic algorithm we propose provides better big data application performance compared to the default block placement method. We implement our solution in our simulation environment and show the improved quality of big data applications.
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Malmo University
Chalmers University of Technology
Abstract. The INTERO (interoperability) model helps organizations manage and improve interoperability among their large, evolving software systems. They can analyze a specific interoperability problem, conceive strategies to enhance interoperability, and reevaluate the problem to determine whether interoperability has improved.
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A Big Data Analytics Architecture for the Internet of Small Things
Moneeb Gohar & Murad Khan & Awais Ahmad – Kyungpook National University
Syed Hassan Ahmed – University of Central Florida
Nadra Guizani – Purdue University
Abstract. The SK Telecom Company of South Korea recently introduced the concept of IoST to its business model. The company deployed IoST, which constantly generates data via the LoRa wireless platform. The increase in data rates generated by IoST is escalating exponentially. After attempting to analyze and store the massive volume of IoST data using existing tools and technologies, the South Korean company realized the shortcomings immediately. The current article addresses some of the issues and presents a big data analytics architecture for its IoST. A system developed using the proposed architecture will be able to analyze and store IoST data efficiently while enabling better decisions. The proposed architecture is composed of four layers, namely the small things layer, infrastructure layer, platform layer, and application layer. Finally, a detailed analysis of a big data implementation of the IoST used to track humidity and temperature via Hadoop is presented as a proof of concept.
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