Slides for the INSPIRE conference workshop held in Aalborg, Denmark on the 17th of June 2014.
The focus of the workshop was practical steps for improving the Quality of Service for INSPIRE network services, so that they could be more useful and reliable sources of information for the data users.
Workshop was hosted in Ilkka Rinne and Kristian Jaakkola on Spatineo Inc.
The Internet of Things (IoT) can be considered as a modern manifestation of Mark Weiser’s classic vision of ubiquitous computing where tiny networked computers become part of everyday objects interweaving the virtual world and the physical world. The concept of the IoT originated some 15 years ago from linking real-world artifacts to virtual counterparts through radio-frequency identification (RFID) tags. More recently, environments have become ‘smart’ by augmenting physical objects with sensing or actuation capabilities and networking them with digital services. The ongoing standardization of Internet protocols for such IoT devices enables the seamless integration of smart things into the Internet. This trend is expected to eventually result in hundreds of billions of connected devices that need to be programmed, managed, and maintained. It has been shown that Web technology can significantly ease this process by providing well-known patterns and tools for developers and users. The existing solutions are, however, often too heavyweight for highly resource-constrained IoT devices. Indeed, most connected devices are expected to remain resource-constrained, as progress in technology witnessed by Moore’s Law is primarily leveraged to minimize dimensions, power consumption, and unit costs.
This dissertation presents a comprehensive solution for the seamless integration of highly resource-constrained IoT systems into the World Wide Web. Our thesis is that existing protocols and programming models do not effectually meet the needs of the IoT. We identify two key challenges for the vision to succeed: application-layer interoperability and improved usability for both developers and users. Both requirements can be met by an approach that amalgamates results from the field of Wireless Sensor Networks and the World Wide Web. This leads to the research questions (i) how to scale Web technology down to resource-constrained devices, (ii) how to scale it up to hundreds of billions of devices, and (iii) how to use it to improve the usability of the tiny networked computers. Our work addresses the resulting challenges with the following contributions: Being actively involved in the design and standardization of the Constrained Application Protocol (CoAP) within the Internet Engineering Task Force (IETF), we (i) evaluate the new Web protocol in the different components of IoT systems, namely resource-constrained devices, Cloud-based services, and user interaction. Based on this, we (ii) propose system architectures and guidelines for an optimal implementation and utilization of CoAP. Furthermore, we (iii) present concepts and tools for Web-like software development for the IoT. To supportour thesis, we also (iv) provide working open source implementations of our concepts, which build the basis for several IoT projects in academia and industry.
The Internet of Things (IoT) can be considered as a modern manifestation of Mark Weiser’s classic vision of ubiquitous computing where tiny networked computers become part of everyday objects interweaving the virtual world and the physical world. The concept of the IoT originated some 15 years ago from linking real-world artifacts to virtual counterparts through radio-frequency identification (RFID) tags. More recently, environments have become ‘smart’ by augmenting physical objects with sensing or actuation capabilities and networking them with digital services. The ongoing standardization of Internet protocols for such IoT devices enables the seamless integration of smart things into the Internet. This trend is expected to eventually result in hundreds of billions of connected devices that need to be programmed, managed, and maintained. It has been shown that Web technology can significantly ease this process by providing well-known patterns and tools for developers and users. The existing solutions are, however, often too heavyweight for highly resource-constrained IoT devices. Indeed, most connected devices are expected to remain resource-constrained, as progress in technology witnessed by Moore’s Law is primarily leveraged to minimize dimensions, power consumption, and unit costs.
This dissertation presents a comprehensive solution for the seamless integration of highly resource-constrained IoT systems into the World Wide Web. Our thesis is that existing protocols and programming models do not effectually meet the needs of the IoT. We identify two key challenges for the vision to succeed: application-layer interoperability and improved usability for both developers and users. Both requirements can be met by an approach that amalgamates results from the field of Wireless Sensor Networks and the World Wide Web. This leads to the research questions (i) how to scale Web technology down to resource-constrained devices, (ii) how to scale it up to hundreds of billions of devices, and (iii) how to use it to improve the usability of the tiny networked computers. Our work addresses the resulting challenges with the following contributions: Being actively involved in the design and standardization of the Constrained Application Protocol (CoAP) within the Internet Engineering Task Force (IETF), we (i) evaluate the new Web protocol in the different components of IoT systems, namely resource-constrained devices, Cloud-based services, and user interaction. Based on this, we (ii) propose system architectures and guidelines for an optimal implementation and utilization of CoAP. Furthermore, we (iii) present concepts and tools for Web-like software development for the IoT. To supportour thesis, we also (iv) provide working open source implementations of our concepts, which build the basis for several IoT projects in academia and industry.
Choosing the best quality of service algorithm using OPNET simulationIJECEIAES
The concept of quality of service (QoS) is a new computer technology. Previously, there was a slow internet connection to access the sites and it was slow to send information. But now, it requires speeding up the traffic and increasing the efficiency for audio and video. In this study, we discuss the concepts of QoS provided over the network to achieve these goals. This study aims to compare six algorithms to control the QoS, then, the best algorithm will be selected to improve the traffic. These algorithms are named first in first out (FIFO), priority queuing (PQ), custom queuing (CQ), CQ with low latency queuing (LLQ), weighted fair queuing (WFQ), WFQ with low latency queuing (LLQ), so the behavior of these algorithms can be measured. The results obtained by comparing between them using OPNET simulation show that the best algorithm is the priority queuing algorithm, followed by CQ, then CQ with LLQ, then WFQ, then WFQ with LLQ and finally FIFO. All these results are plotted in the form of graphs to show the paths of these algorithms for the single state with an operation time of 5 minutes for each algorithm.
The Optimization of IPTV Service Through SDN In A MEC Architecture, Respectiv...CSCJournals
The aim of this paper is to present the ‘Power’ of SDN Technology and MEC Technic in improving the delivering of IPTV Service. Those days, the IPTV end –users are tremendous increased all over the world , but in the same time also the complains for receiving these prepaid real time multimedial services like; high latency, high bandwidth, low performance and low QoE/QoS. On the other end, IPTV Distributors need a new system, technics, network solutions to distribute content continuesly and simultaneously to all active end-users with high-quality, lowlatency and high Performance, thus monitoring and re-configuring this ‘Big Data’ require high Bandwidth by causing difficult problems by offering it affecting in the same time the price and QoE/QoSperformance of delivered service.
For this reason, we have achieved to optimize the IPTV service by applying SDN solution in a MEC Architecture (Multiple-Access Edge Computing). In this way , through MEC Technology and SDN, it is possible to receive an IPTV service with Low Latency, High Performance and Low Bandwidth by solving successfully all the problems faced by the actual IPTV Operators. These improvements of delivering IPTV service through MEC will be demonstrated by using the OMNet +++ simulator in an LTE-A mobile network. The results show clearly that by applying the MEC technique in the LTE-A network for receiving IPTV Service through SDN Network, the service was delivered with latency decreased by >90% (compared to the cases when the MEC technique is not applied), with PacketLoss of almost 0 and with high performance QoE. In addition these strong Contributions, the ‘Big’ innovation achieved in this work through simulations is that the quality of delivered IPTV Service did not change according to the increasing of the end-users.This latency of delivering the video streaming services did not change. This means that the IPTV Service providers will increase their benefits by ensuring in the same time also the delivering of service with high quality and performance toward innumerous end users. Consequently, MEC Technology and SDN solution will be the two right and "smart" network choices that will boost the development of the 5th Mobile generation and will significantly improve the benefit of Video Streaming services offered by current providers worldwide (Netflix, HULU, Amazon Prime, YouTube, etc).
Essential quality criteria for planning and validation of PROFINET networks
For PROFINET devices the quality criteria that are checked within the scope of the device certification are described in published specifications, standards and test specifications. Interoperability is protected by both the specification and the test procedures in the cooperation of the devices. From practical experience in the realization of network arrangements it appears that beside the device qualities also the planning quality and the quality of the validation of a whole arrangement can have an influence on the functionality.
In the task force CB / PG3 "Installation Guidelines" the suitable planning directives and introduction directives are now integrated into the quality criteria for the planning and validation of the PROFINET networks. The methods, measuring procedures and also the background will be fully explained.
Pipelined Compression in Remote GPU Virtualization Systems using rCUDA: Early...Carlos Reaño González
Paper presented at the 2nd International Workshop on Deployment and Use of Accelerators (DUAC). Co-located with the 51st International Conference on Parallel Processing (ICPP). August 29, 2021 (virtual event). More information at: https://duac2022.wordpress.com/
Real Time Monitoring and Electro Magnetic Interference causing Data corruptionRekaNext Capital
On site, where there are motors and generators, the sensor reading are affected by Electro-Magnetic Interference. The presentation shares some Good Engineering Practices to minimize Data Corruption. Real Time Monitoring Data Quality is even more sensitive to Data Corruption as there is a huge amount of sensors per hour.
Intelligent Network Services through Active Flow ManipulationTal Lavian Ph.D.
Active Flow Manipulation Abstractions:
Aggregate data into traffic flows
Flows whose characteristics can be identified in real-time
E.g., “all UDP packets to a particular service”, “all TCP packets from a particular machine”.
Actions to be performed in the traffic flows
Actions that can be performed in real-time
E.g., “Change the priority of all traffic destined to a particular service on a particular machine”, “Stop all traffic out of a particular link of a router”.
Presentació a càrrec de Maria Isabel Gandia, cap de Comunicacions, duta a terme a la comunitat usuària de LAC-IX (Latin America and Caribbean IXPS) el 30 d'abril de 2021 en format virtual.
Enabling Carrier-Grade Availability Within a Cloud InfrastructureOPNFV
Aaron Smith, Red hat, Pasi Vaananen, Red Hat
Carrier-Grade Cloud Infrastructure (Aaron Smith, Pasi Vaananen, Red Hat): The move from vertically integrated hardware and software to distributed execution in a cloud complicates the delivery of highly available services. Vertically integrated systems enabled all system layers required to communicate and participate in the support of availability of the service to be under control of single system vendor. With NFV, the cloud philosophy of infrastructure and application decoupling requires new open interfaces to support the necessary flow of information between layers and clear separation of the fault and availability management responsibilities between the infrastructure and application SW subsystems. Even in the cloud environment, traditional availability concepts such as fast detection, correlation, and fault notification still apply. A fast, low-latency fault management platform will be presented that allows cloud-based services to achieve 5NINES of availability and service continuity. Performance measurements from a prototype of the system will be presented along with a demo of the operation of a service requiring 50 ms fault remediation.
Project Business Case and Capital Justification for Implementation of Applica...Duane Bodle
Business Case and Capital Justification Presentation For
Application Performance Monitoring and Retrospective Network Analysis Implementation. *** This Presentation Has Been Sanitized of IP Information ***
Achievements and future works of ITU-T Study Group 11 on Signalling requirements, protocols and test specifications
Presented at WTSA-16 by Mr Kaoru Kenyoshi, Vice-Chairman, on behalf of Mr Wei Feng, Chairman of of ITU-T Study Group 11
NETWORK PERFORMANCE EVALUATION WITH REAL TIME APPLICATION ENSURING QUALITY OF...ijngnjournal
The quality of service is a need in recent computer network developments. The present paper evaluates some characteristics in a proposed network topology such as dropped packets and bandwidth use, using two traffic sources, firstly a VoIP source over an UDP agent, then a CBR traffic source over an UDP agent as well as the previous one. Two possible configurations are proposed, implementing both of them in the Network Simulator, and implementing in one of them differentiated services to compare the results. Statistics results are shown, in both cases showing the accumulative dropped packet number and the throughput in the link, obtaining a reducer number of dropped packets in the stage with differentiated services, and an improvement in the bandwidth use.
Choosing the best quality of service algorithm using OPNET simulationIJECEIAES
The concept of quality of service (QoS) is a new computer technology. Previously, there was a slow internet connection to access the sites and it was slow to send information. But now, it requires speeding up the traffic and increasing the efficiency for audio and video. In this study, we discuss the concepts of QoS provided over the network to achieve these goals. This study aims to compare six algorithms to control the QoS, then, the best algorithm will be selected to improve the traffic. These algorithms are named first in first out (FIFO), priority queuing (PQ), custom queuing (CQ), CQ with low latency queuing (LLQ), weighted fair queuing (WFQ), WFQ with low latency queuing (LLQ), so the behavior of these algorithms can be measured. The results obtained by comparing between them using OPNET simulation show that the best algorithm is the priority queuing algorithm, followed by CQ, then CQ with LLQ, then WFQ, then WFQ with LLQ and finally FIFO. All these results are plotted in the form of graphs to show the paths of these algorithms for the single state with an operation time of 5 minutes for each algorithm.
The Optimization of IPTV Service Through SDN In A MEC Architecture, Respectiv...CSCJournals
The aim of this paper is to present the ‘Power’ of SDN Technology and MEC Technic in improving the delivering of IPTV Service. Those days, the IPTV end –users are tremendous increased all over the world , but in the same time also the complains for receiving these prepaid real time multimedial services like; high latency, high bandwidth, low performance and low QoE/QoS. On the other end, IPTV Distributors need a new system, technics, network solutions to distribute content continuesly and simultaneously to all active end-users with high-quality, lowlatency and high Performance, thus monitoring and re-configuring this ‘Big Data’ require high Bandwidth by causing difficult problems by offering it affecting in the same time the price and QoE/QoSperformance of delivered service.
For this reason, we have achieved to optimize the IPTV service by applying SDN solution in a MEC Architecture (Multiple-Access Edge Computing). In this way , through MEC Technology and SDN, it is possible to receive an IPTV service with Low Latency, High Performance and Low Bandwidth by solving successfully all the problems faced by the actual IPTV Operators. These improvements of delivering IPTV service through MEC will be demonstrated by using the OMNet +++ simulator in an LTE-A mobile network. The results show clearly that by applying the MEC technique in the LTE-A network for receiving IPTV Service through SDN Network, the service was delivered with latency decreased by >90% (compared to the cases when the MEC technique is not applied), with PacketLoss of almost 0 and with high performance QoE. In addition these strong Contributions, the ‘Big’ innovation achieved in this work through simulations is that the quality of delivered IPTV Service did not change according to the increasing of the end-users.This latency of delivering the video streaming services did not change. This means that the IPTV Service providers will increase their benefits by ensuring in the same time also the delivering of service with high quality and performance toward innumerous end users. Consequently, MEC Technology and SDN solution will be the two right and "smart" network choices that will boost the development of the 5th Mobile generation and will significantly improve the benefit of Video Streaming services offered by current providers worldwide (Netflix, HULU, Amazon Prime, YouTube, etc).
Essential quality criteria for planning and validation of PROFINET networks
For PROFINET devices the quality criteria that are checked within the scope of the device certification are described in published specifications, standards and test specifications. Interoperability is protected by both the specification and the test procedures in the cooperation of the devices. From practical experience in the realization of network arrangements it appears that beside the device qualities also the planning quality and the quality of the validation of a whole arrangement can have an influence on the functionality.
In the task force CB / PG3 "Installation Guidelines" the suitable planning directives and introduction directives are now integrated into the quality criteria for the planning and validation of the PROFINET networks. The methods, measuring procedures and also the background will be fully explained.
Pipelined Compression in Remote GPU Virtualization Systems using rCUDA: Early...Carlos Reaño González
Paper presented at the 2nd International Workshop on Deployment and Use of Accelerators (DUAC). Co-located with the 51st International Conference on Parallel Processing (ICPP). August 29, 2021 (virtual event). More information at: https://duac2022.wordpress.com/
Real Time Monitoring and Electro Magnetic Interference causing Data corruptionRekaNext Capital
On site, where there are motors and generators, the sensor reading are affected by Electro-Magnetic Interference. The presentation shares some Good Engineering Practices to minimize Data Corruption. Real Time Monitoring Data Quality is even more sensitive to Data Corruption as there is a huge amount of sensors per hour.
Intelligent Network Services through Active Flow ManipulationTal Lavian Ph.D.
Active Flow Manipulation Abstractions:
Aggregate data into traffic flows
Flows whose characteristics can be identified in real-time
E.g., “all UDP packets to a particular service”, “all TCP packets from a particular machine”.
Actions to be performed in the traffic flows
Actions that can be performed in real-time
E.g., “Change the priority of all traffic destined to a particular service on a particular machine”, “Stop all traffic out of a particular link of a router”.
Presentació a càrrec de Maria Isabel Gandia, cap de Comunicacions, duta a terme a la comunitat usuària de LAC-IX (Latin America and Caribbean IXPS) el 30 d'abril de 2021 en format virtual.
Enabling Carrier-Grade Availability Within a Cloud InfrastructureOPNFV
Aaron Smith, Red hat, Pasi Vaananen, Red Hat
Carrier-Grade Cloud Infrastructure (Aaron Smith, Pasi Vaananen, Red Hat): The move from vertically integrated hardware and software to distributed execution in a cloud complicates the delivery of highly available services. Vertically integrated systems enabled all system layers required to communicate and participate in the support of availability of the service to be under control of single system vendor. With NFV, the cloud philosophy of infrastructure and application decoupling requires new open interfaces to support the necessary flow of information between layers and clear separation of the fault and availability management responsibilities between the infrastructure and application SW subsystems. Even in the cloud environment, traditional availability concepts such as fast detection, correlation, and fault notification still apply. A fast, low-latency fault management platform will be presented that allows cloud-based services to achieve 5NINES of availability and service continuity. Performance measurements from a prototype of the system will be presented along with a demo of the operation of a service requiring 50 ms fault remediation.
Project Business Case and Capital Justification for Implementation of Applica...Duane Bodle
Business Case and Capital Justification Presentation For
Application Performance Monitoring and Retrospective Network Analysis Implementation. *** This Presentation Has Been Sanitized of IP Information ***
Achievements and future works of ITU-T Study Group 11 on Signalling requirements, protocols and test specifications
Presented at WTSA-16 by Mr Kaoru Kenyoshi, Vice-Chairman, on behalf of Mr Wei Feng, Chairman of of ITU-T Study Group 11
NETWORK PERFORMANCE EVALUATION WITH REAL TIME APPLICATION ENSURING QUALITY OF...ijngnjournal
The quality of service is a need in recent computer network developments. The present paper evaluates some characteristics in a proposed network topology such as dropped packets and bandwidth use, using two traffic sources, firstly a VoIP source over an UDP agent, then a CBR traffic source over an UDP agent as well as the previous one. Two possible configurations are proposed, implementing both of them in the Network Simulator, and implementing in one of them differentiated services to compare the results. Statistics results are shown, in both cases showing the accumulative dropped packet number and the throughput in the link, obtaining a reducer number of dropped packets in the stage with differentiated services, and an improvement in the bandwidth use.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
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Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...
Practical Quality Assurance of Spatial Web Services
1. Copyright Spatineo
Spatineo
Linnankoskenkatu 16 A 17
FI-00250 Helsinki
+358 20 703 2210
Practical Quality Assurance
of Spatial Web Services
Spatineo Inc.
Ilkka Rinne & Kristian Jaakkola
Workshop
INSPIRE Conference 17th June 2014 at 9:00 am
Aalborg University, Badstuestræde 9/auditorium 1
2. Copyright Spatineo
Session 1 schedule
Presentation: Overview of the INSPIRE QoS
requirements for Network Services (20 min)
Demo: Evaluating the Spatial Web Service
availability and continuous performance
with Spatineo Monitor (10 min)
Group discussions (45 min): INSPIRE QoS
9:00 - 10:30, auditorium 1
Ice-breaker: Say hello to the people around you and
share your workshop expectations (10 min)
4. Copyright Spatineo
Our Common Expectations
For This Workshop
Let’s make this a proper discussing workshop. See
who’s sitting next to you, and introduce yourself.
What are you working with, if and how it relates to the
INSPIRE network services, and what are your
expectations for this workshop.
6. Copyright Spatineo
INSPIRE Network Services
Quality of Service
Capacity: Must handle at least the given number of
simultaneous users / requests without degrading it’s
performance.
Performance: Must succeed to continuously serve
it’s data sets within the given time limits.
Availability: Must be available for use 99% of the
time excluding maintenance breaks announced early
enough.
7. Copyright Spatineo
Criteria and Normalized
Testing Procedures
The QoS metrics and the criteria are given in the
directive legal text (Implementation Rules).
The technical details and normalized testing
procedures are defined in the Technical Guidance
documents for each of the Network Service types:
• Discovery Service: Catalog Service for Web (CSW)
• View Service: Web Map Service (WMS) or Web Map Tiling Service (WMTS)
• Download Service: Web Feature Service (WFS) or Atom + data files
8. Copyright Spatineo
Performance Criteria:
Discovery Services
“The response time for sending the initial response to a discovery service
request shall be maximum 3 seconds in normal situation.
[..]
Normal situation represents periods out of peak load. It is set at 90% of the
time.”
(IR Network Services*)
*) “Commission Regulation (EC) No 976/2009 of 19 October 2009 implementing Directive 2007/2/EC of the European Parliament and of the
Council as regards the Network Services”, http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:02009R0976-20101228
and “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
9. Copyright Spatineo
Performance Testing:
TG Discovery Services 3.1
Technical Guidance for INSPIRE Discovery Services, version 3.1, http://inspire.jrc.ec.europa.eu/documents/Network_Services/
TechnicalGuidance_DiscoveryServices_v3.1.pdf
Minimum of 10 Discovery Metadata (CSW GetRecords) requests per hour shall
be issued to the service continuously during its lifetime.
Recommendation: Search metadata with filter PropertyName=AnyText,
Literal=dataset, and with varying BBOX requests.
Evaluation: A minimum of 90% of the initial services responses have to comply
with the mandated 3 seconds response time, thus, a normal situation is identified
by the 90% best performing sample reference requests.
10. Copyright Spatineo
Capacity Criteria:
Discovery Services
“The minimum number of simultaneous requests to a discovery service to be
served in accordance with the quality of service performance criteria shall be 30
per second.”
(IR Network Services*)
*) “Commission Regulation (EC) No 976/2009 of 19 October 2009 implementing Directive 2007/2/EC of the European Parliament and of the
Council as regards the Network Services”, http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:02009R0976-20101228
and “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
11. Copyright Spatineo
Capacity Testing:
Discovery Services
Technical Guidance for INSPIRE Discovery Services, version 3.1, http://inspire.jrc.ec.europa.eu/documents/Network_Services/
TechnicalGuidance_DiscoveryServices_v3.1.pdf
For the testing duration of one minute, send 30 new requests each second.
Evaluation: Performance must not be degraded during this test, so the fastest
90% share of requests for all operations must start returning data under 5
seconds.
Recommended mix of operations: 10% Get Discovery Service Metadata (CSW
GetCapabilities), and 90% Get Discovery Metadata requests (CSW GetRecord)
Capacity testing must be done at least once before launching in production
environment and should be done regularly after that (monthly or so during
maintenance breaks).
12. Copyright Spatineo
Performance Criteria:
View Services
“For a 470 Kilobytes image (e.g. 800x600 pixels with a colour depth of 8 bits),
the response time for sending the initial response to a Get Map Request to a
view service shall be maximum 5 seconds in normal situation.
Normal situation represents periods out of peak load. It is set at 90% of the
time.”
(IR Network Services*)
*) “Commission Regulation (EC) No 976/2009 of 19 October 2009 implementing Directive 2007/2/EC of the European Parliament and of the
Council as regards the Network Services”, http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:02009R0976-20101228
and “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
13. Copyright Spatineo
Performance Testing:
TG View Services 3.11
Minimum of 10 requests per hour shall be issued to the service continuously
during its lifetime.
Evaluation: Must return a non-empty image if data is present for the given
request parameters (BBOX, scale, etc.)
A minimum of 90% of the initial services responses have to comply with the
mandated 5 seconds response time, thus, a normal situation is identified by the
90% best performing sample reference requests.
Technical Guidance for INSPIRE View Services, version 3.11, http://inspire.jrc.ec.europa.eu/documents/Network_Services/
TechnicalGuidance_ViewServices_v3.11.pdf
Request must contain only one layer at a time, the image color depth should be
8-bit, and it’s size 800 x 600 pixels (to make an approx. of 470kB file size).
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Capacity Criteria:
View Services
“The minimum number of served simultaneous service requests to a view
service according to the performance quality of service shall be 20 per
second.”
(IR Network Services*)
*) “Commission Regulation (EC) No 976/2009 of 19 October 2009 implementing Directive 2007/2/EC of the European Parliament and of the
Council as regards the Network Services”, http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:02009R0976-20101228
and “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
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Capacity Testing:
TG View Services 3.11
For the testing duration of one minute, send 20 new requests each second.
Evaluation: Performance must not be degraded during this test, so the fastest
90% share of requests for all operations must start returning data under 5
seconds.
Recommended mix of operations: 10% Get View Service Metadata (Get
Capabilities for WMS and WMTS services) and 90% Get Map requests.
Capacity testing must be done at least once before launching in production
environment and should be done regularly after that (monthly or so during
maintenance breaks).
Technical Guidance for INSPIRE View Services, version 3.11, http://inspire.jrc.ec.europa.eu/documents/Network_Services/
TechnicalGuidance_ViewServices_v3.11.pdf
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Performance Criteria:
Download Services
“For the Get Download Service Metadata operation, the response time for
sending the initial response shall be maximum 10 seconds in normal situation.
For the Get Spatial Data Set operation and for the Get Spatial Object operation,
and for a query consisting exclusively of a bounding box, the response time for
sending the initial response shall be maximum 30 seconds in normal situation
then, and still in normal situation, the download service shall maintain a sustained
response greater than 0,5 Megabytes per second or greater than 500 Spatial
Objects per second.
For the Describe Spatial Data Set operation and for the Describe Spatial
Object Type operation, the response time for sending the initial response shall be
maximum 10 seconds in normal situation then, and still in normal situation, the
download service shall maintain a sustained response greater than 0,5 Megabytes
per second or greater than 500 descriptions of Spatial Objects per second.”
(IR Network Services*)
*) “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
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Performance Testing:
TG Download Services 3.1
At least one request every 6 minutes (10 requests / hour) shall be issued to the
service during test periods (?) (recommended to be monthly, during maintenance
breaks).
All operations should be included in test requests: Get Download Service
Metadata, Get Spatial Data Set, Get Spatial Object, Describe Spatial Data Set
and Describe Spatial Object Type operations.
Use BBOX filtering (only) for Get Spatial Object operations. Include only one
spatial object type and data set for Get Spatial Object and Get Spatial Data Set
operations.
Evaluation: First bytes of the responses must arrive in less than 30s (data) and
10s (metadata) excluding the estimated network latency (?). After that the
downstream speed must be > 0.5MB/s or > 500 objects/s for the fastest 90% of
the test requests.
Technical Guidance for the implementation of INSPIRE Download Services, version 3.1, http://inspire.ec.europa.eu/documents/
Network_Services/Technical_Guidance_Download_Services_v3.1.pdf
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Capacity Criteria:
Download Services
“The minimum number of simultaneous requests to a download service to
be served in accordance with the quality of service performance criteria
shall be 10 requests per second. The number of requests processed in
parallel may be limited to 50.”
(IR Network Services*)
*) “Commission Regulation (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32010R1088
19. Copyright Spatineo
Capacity Testing:
TG Download Services 3.1
For the testing duration of one minute, send 10 new requests each second. It’s
allowed for the server not to respond in orderly fashion to requests exceeding 50
simultaneous request limit.
Evaluation: Performance must not be degraded during this test, so the fastest
90% share of requests for all operations must start returning data under 30s and
metadata under 10s.
Recommended mix of operations: 10% Get Download Service Metadata
requests, 10% Describe Spatial Data Set or Describe Spatial Object Type and
80% Get Spatial Data Set or Get Spatial Object. At least 2% of the requests
should be Get Spatial Data Set.
Capacity testing must be done at least once before launching in production
environment and should be done regularly after that (monthly or so during
maintenance breaks).
Technical Guidance for the implementation of INSPIRE Download Services, version 3.1, http://inspire.ec.europa.eu/documents/
Network_Services/Technical_Guidance_Download_Services_v3.1.pdf
20. Copyright Spatineo
Availability Criteria:
All Network Services
“The probability of a Network Service to be available shall be 99% of the time”
(IR Network Services*)
*) “Commission Regulation (EC) No 976/2009 of 19 October 2009 implementing Directive 2007/2/EC of the European Parliament and of the
Council as regards the Network Services”, http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32009R0976:EN:NOT
and “COMMISSION REGULATION (EU) No 1088/2010 of 23 November 2010 amending Regulation (EC) No 976/2009 as regards download
services and transformation services”, http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:02009R0976-20101228
21. Copyright Spatineo
Availability Testing:
Same method in all TGs
Minimum 10 requests per hour shall be issued to the service continuously
during its lifetime.
“Available” is not explicitly defined: Does the response for all the test requests
need to arrive in certain time, like 5 or 30 seconds? Has the service been
“available” during a certain hour if 1 of 10 requests made during that time has
failed?
Evaluation: Service must be available 99% of the time. The reference time frame
is one year, so it’s allowed for each service to be down maximum of 3.63 days /
year. The pre-announced maintenance breaks (notified at least one week in
advance) are excluded (recommendation for these is max. 10hrs / month).
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Work in groups
• Split into small groups, select one QoS-related topic
per group.
• Some suggestions for topics on the next slide
• 10 minutes to discuss about the topic in each group
+ 5 minutes to finalize a short wrap-up to present.
• 5 minutes for each group to present their wrap-up for
others.
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Some discussion topics
• INSPIRE QoS requirements: Difficult or easy to achieve? Useful or
not very? Any ideas to making them more useful?
• How to make it worthwhile and easy enough for the INSPIRE data
providers to improve the QoS of their services?
• Application developer perspective: What QoS indicators would be
most useful for the data users? How should they be advertised for
INSPIRE services?
• Data provider view: How to integrate QoS measuring and
improvements to a daily / monthly / yearly development plans &
practices? Dev. team / management view?
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Finding and Following
New Services
• We already know and monitor a lot of publicly accessible spatial
web services:
• Currently over 21500 WMS, WMTS and WFS services monitored around the world.
• Free search engine Spatineo Directory: http://directory.spatineo.com/
• Add a service to your followed a services by clicking “Follow in Spatineo Monitor”
button on the Directory service page.
• If your service is not found, paste the GetCapabilities URL to the search field of
Spatineo Directory and we’ll check it out immediately.
• Monitoring will start automatically, but the owners of the services
can modify how the monitoring is done by adding or changing
meters: layer, image format & size, CRS etc.
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Exercise 1:
Add a new meter
• Group-up with the people nearest to you.
• At least one laptop per group: select who’s “the operator”.
• Each group has their own demo credentials to Spatineo Monitor.
• Login address and the credentials are included in the printed
training material sheets provided each of the groups.
• Complete the exercise in your group.
• Review will be done in 10 minutes.
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Monitoring continuous
performance & availability
• For each of your followed services a the continuous performance
and availability analysis is provided:
• Graphical timeline-based navigation.
• Service availability percentage for the selected time period.
• Response time analysis and list of monitoring requests with selected response time
category highlighting.
• For any of the meters used for monitoring, you can add an indicator to get alerts if the
performance measurements exceed given thresholds.
• Alerts are sent by email or SMS
• Also get notified when the service is back in a normal state again.
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Exercise 2:
Add an alert to a meter
• Use the same demo credentials to Spatineo Monitor as in
exercise 1.
• Complete the exercise in your group.
• Review will be done in 5 minutes.
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Analyzing service usage
• Usage analytics is a an add-on component of Spatineo Monitor.
• Similar to website analytics, it provides information about how
much the services are used, where the users come from and how
are they using the service.
• Graphical timeline-based navigation with number of requests and server-side response
time.
• Segmented analytics: by user country, ISP, device, CRS, image size & format etc.
• Graphs for access by time of day, day-of-week and a map of request area.
• See statistics by layer or feature type.
• Drill-down user interface: Select an analytics segment to limit the visualization to those
requests only.
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Scheduled reporting
• Reporting features of Spatineo Monitor offer an easy way
to follow the statistical trends for the followed services.
• Weekly, monthly or yearly reports of usage analytics, for
example to be used in the yearly INSPIRE monitoring
spreadsheets, can be configured.
• You can order the reports to sent automatically by email
or download them at any time from the Report archive.
• Select any of your followed services to be included in a
each of the reports.
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Exercise 3:
Create a usage report
• Use the same demo credentials to Spatineo Monitor as in
exercise 1.
• Complete the exercise in your group.
• Review will be done in 5 minutes.
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Notifications: Announcing
Maintenance Breaks
• Maintenance breaks for your own services can be
announced using Spatineo Monitor notification features.
• Breaks and other notifications are published in the
Spatineo Directory page for the selected services.
• The users can also subscribe using Atom and iCal feed
syndication.
• Designed to fulfill the INSPIRE requirement for pre-
announcing maintenance breaks to the users.
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Validating Service Metadata
• Spatineo Monitor contains a standards compliance
validator for service metadata documents
(GetCapabilities)
• Checks for the OGC and INSPIRE requirements.
• Supported standards: WMS 1.3.0, WMTS 1.0.0, INSPIRE
Profiles for WMS and WMTS.
• On-going work to integrate with the “commonly agreed”,
official INSPIRE validator software:
• Spatineo is active in MIG subgroup MIWP-5 “Validation and conformity testing”
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Wrap-up: What have we
learned this morning?
Slides: http://www.slideshare.net/iorinne/practical-
quality-assurance-of-spatial-web-services