Transcends now delivers to the Rifidi Community integration with Cloud and Social Media Jumpstarting your Sensor Solutions
Through numerous responses to our Rifidi Product Roadmap Survey we have delivered several jumpstarts for your Sensor based Solutions:
Rifidi Edge Database Integration Jumpstart + example application
As the Rifidi Community continues to grow and the Industry Leading Open Source Platforms Rifidi is built on evolves (Spring – Application Framework, Esper – Sensor Event Engine, Eclipse – IDE, OSGI – Lightweight Middleware Container capable of running on a device as small as the Rasberry PI) Transcends is enabled to bring more powerful Soluitions to market lowering the overall TCO for everyone envolved. Come learn about the Transcends Powered by Rifidi
Transcends Now Offers Extended Rifidi Consulting and Support for your
Solution – Our Team and Partner Community can help…
- Looking to prepare a Demostration/prototype of you hardware and need a richer solution
- Want to turn your idea into a Business Solution you can bring to the Global marketplce
- Have a business problem and need to effectively turn around an implementation leveraging the Rifidi Open Source Community
Contact Us For Asssitance in Bringing your Solution to Reality.
Transcends Announces Rifidi Edge Server 1.3.1 Public Release Global Leader
in RFID Open Source Solutions.
Many of the features released here were based on input from the Rifidi
Forums Community – The Rifidi Support team Thanks You and Asks for You to
Keep the Feedback Coming!!
Contribute to Transcends Product Roadmap by Filling Out This Survey
The Rifidi Edge 1.3.1 Release includes improvements to the LLRP Support
(GPIO and Increased Performance)
Complete 1.3.1 Release Notes –
Download Rifidi Edge 1.3.1 Latest Version –
Thanks, The Transcends Support Team -Powered by Rifidi
http://www.transcends.co – Community Sponsors
http://www.rifidi.org – Rifidi Platform – Edge Server (Edge), Load Testing (TagStreamer), Prototyping (Prototyper), Emulation (Emulator)
http://wiki.rifidi.org – Product Documentations and HowTOS
http://forums.rifidi.org – Rifidi Community Product Forum
Transcends, the Lead Contributor to the Rifidi Platform, is in progress of planning our next major release. We are reaching out to the Rifidi Community to provide input to our roadmap by completeing the following survery. The survery should take no more than a few minutes (Six questions) and will be valuable in helping us provide more value to the RFID Open Source Community
Rifidi Community Roadmap Survey click here
The questions address social media, cloud computing, smart phones, sensors adapters, roles and community solutions/support. This feedback will be critical in determining the Rifidi Platform Roadmap direction as the community is what makes Rifidi powerful.
Global Leader in RFID Open Source Solutions – Delivering Sensor based Business Solution for the Next Generation Better, Faster and Cost Effective
The Rifidi Edge 1.3 Release includes updates to the latest version of Spring 3.0.5 and Esper 4 (The open source sensor event processlng language). These updates have show in performance testing 3x increase in ability to process sensor events on equilvalent hardware. The release is fully compatable with the Rifidi Platform (Workbench, Emulator, TagStreamer-Sensor Load Testing Tool and Prototyper).
Note: Workbench has been modified to interoperate with current release. ALE support has been removed but is planned to be added back in the next release as we are in the process of refactoring.
More than ever I now realize the importance of learning from life’s sessions. Who could have ever predicted in the past 10 years we would have globalized as much as we have and in the past three years have been faced with the most challenging economic conditions in all our generations. As part of my six year journey in the RFID industry, I have had the opportunity to travel around the globe and be introduced to more cultures and ways of thinking than ever before. You look around both here at home (which for me is between North and South America) and globally to realize how much of impact we have had on each other, how much more there is still to learn and the potential opportunity the combination of both these circumstances presents.
So what does this retrospect of thoughts mean to us in RFID? In general, many market conditions have caused us to get where we are today. The potential of an emerging industry like RFID (and more broadly sensors which are already all around us) is boundless figuratively and literally. Here is why.
1) The industry started to really grow just a few years before the recession and many industries (if not viable) would have starved and become insignificant.
2) I find myself more than ever being involved in tangible real life solutions globally
3) The globalization our economy and everyday lives has presented us with more than ever a need for us to connect at any time and place with enriching information.
4) We have the internet for people and saw the impact this development has had on our economy and lives. We are building the internet of things and no other industry other than RFID has presented an answer on how these two technologies converge on one another.
How can we be successful?
1) We must all acknowledge and have an awareness of the world around us. The USA and Europe still have many key decision makers and large market capitals but the reality that is changing. The other reality is, even when a project is initiated from these markets the actual implementation, support and future development of the solution is happening globally.
2) Continue to work together, learn quickly from our mistakes and innovative solutions adding value today and have relevance towards the future. Many people speculate when will the industry come of age (is it this year, next year or 5 years from now). I believe we should be less focused on when and more focused on how. As I stated earlier it’s just a matter of timing and making sure you are still relevant when it happens. I was watching a program on CNN earlier last week discussing the state of our economy and the impact globalization has on our and future generations to come. The comment that caught my interest the most is “Average is no longer good enough”. We are all now competing with the global marketplace therefore we all need to think and work like artisans. This means we need to be so proud of your work you would be willing to engrave your name in the craft.
I’m sure there are many other opinions on why and how we can be successful in RFID and what challenges the crossing roads of the recession and globalization has presented us with. But this should shed some light on my opinion of the business principle with challenges are opportunities……….
by Mychal Capozzi (RIT Rifidi Coop/Undergrad Comp Sci) and Matt Dean (Rifidi Lead Software Engineer) This document will give an overview of some basic scalability and performance data for Rifidi Edge and Rifidi Box Appliance
Four tests were run on different levels of hardware to test the load that the Rifidi Edge v1.2 could handle both with and without business-end computational logic. The tests were set up as follows:
Two different hardware configurations were used to demonstrate scalability, the first being a Asus Model: EEBox B202 (a netbook like device similar to is bundled with the Rifidi Box appliance) and the second target machine is a Toshiba Satellite laptop Model: Portege r700-S1320 (the more powerful of the two machines running with an Intel Core i5 (Dual Core Hyper Threaded) @2.4ghz ). Two software configuration scenarios were set up on the machines, the first to demonstrate the performance of the Rifidi Edge Server’s ability to process tag events purely in memory and the second to demonstrate the Rifidi Edge Server’s ability to process tag events and persist to a database (in this case MySQL v5.1) on the same machine. In all the test scenarios a separate machine is used to execute the simulated the virtual LLRP readers and tag rate scenarios. The product used for simulation is Rifidi TagStreamer v1.1.1 and the machine TagStreamer executed on is an dual-core, dual threaded 2.4 GHz processor. The simulated environment contained 4 LLRP readers, each with a single antenna and single read zones. The throughput time from one reader to the next was set one one millisecond, to simulate each of the four readers receiving their load almost simultaneously. Various numbers of generation two GID96 tags were sent across all four reads in bursts over one second, with a one second cool down between bursts for one to two minutes while data was collected. The tests were designed to be limited by buffering of tags by either Rifidi Edge Server or MySQL, to verify that a given load could be sustained over long periods of time.
Note: All testing for these four scenarios were over a wired Ethernet 100 MB network. More readers could have been used but for simplicity in setting up the scenario 4 LLRP readers were used with a higher load and frequency of tags within the antenna range.
More details for both hardware configuartions can be found in the summary results table below.
The first machine used an Asus appliance, Atom n2700 single core dual-threaded processor, Ubuntu 10.4 operating system, 1 gig of ram, 160 gig hard drive and is the basic platform recommended for use with the Rifidi Box appliance. Without the database writes of every tag seen, the edge server on the aforementioned hardware was capable of seeing between 350 and 450 tags per second with minimal buffering. With the database write enabled, the Rifidi Edge was capable of receiving bursts of 75 to 125 tags every second.
The second machine, based around a consumer-level test, was a Toshiba Satellite laptop with an Intel Core i5 @2.4ghz with 4 gigabytes of ram running Linux Mint 10 (based on Ubuntu 10.10). When the database writes were disabled, Rifidi Edge was consistently reading 2200 – 2300 tags per second. With the database writes occurring, the read rate was closer to 600-700 tags per second.
As far as CPU consumption, on the Asus machine with the Rifidi Edge Server processing tag events in-memory, the CPU reached 65-70% consumption. When including the MySQL database, the Rifidi Edge was consuming much less; closer to 45% of the CPU. The database was consuming close to 25% while this test was running.
The Toshiba Satellite machine CPU in-memory test was 80%, but once the database test began, that consumption dropped to 65%, while the database was consuming no more than 35% of the CPU.
Calculating RAM Usage: RAM usage between the two was minimal, not surpassing 250 Mb. Additional readers were established to estimate how much RAM would be required to support each additional reader, and it is estimated to be .1 Mb (100 Kb). This value is platform independent. Additionally, we estimate that tag’s memory usage is variable depending on the tag type, for these tags it was negligible at less than 1KB each. This estimate was reached by firing 200 tags over 200 milliseconds at the Atom machine and measuring RAM consumption during the test until negligible fluctuations were measured, and then comparing that amount to the Rifidi Edge without receiving any tags.
Scalability with Retail RFID Business Case Scenarios:
Based on the load-tests described above, estimates can be extrapolated to account for various reader and tag rate environments. Given the following three retail scenarios described in detail below, we were able to size the necessary hardware requirements based on the scalability testing results above prior executing the simulation using Rifidi TagStreamer v1.1.1 on the same constant machine and Rifidi Edge Server v1.2 on the Toshiba Satellite laptop.
The Retail Scenarios: A Department store has recently been outfitted with RFID readers on it’s dock doors, shelving units, and at the sales counters. On an average day they process hundreds of thousands of individual items from the dock doors to the sales counters, and with the use of RFID tags, keeping track of inventory has become completely automated. There are three defined areas where tags should be seen and a defined flow of events, they are:
1) There are five loading dock doors, each receiving 1000 tagged items every 30 seconds to 3 minutes. 2) There are 35 shelving units each receiving 50 tagged items every 15 seconds to 2 minutes. 3)There are ten points of sale, each receiving 10, 25, or 50 tagged items every 30 seconds to 2 minutes.
So using the Rifidi Edge software to process the tags and Tag Streamer to generate the tags on a separate machine, the following data was collected:
Edge Server Data: -Top CPU usage: 75% -Top RAM usage: 20% -Avg CPU: 50% -Avg RAM: 15% -Network speed: 100 Mbps -Total LLRP Readers used in testing: 50 -Test Duration: 18 hours -Average tag events per second including database persistence: 107 -Peek bursts including database persistence (Tags events/per second): 336 -Total tag events processed by the Edge Server and persisted to MySQL in 18 hrs: 6,621,280
End results: Based on the performance of the Toshiba Satellite laptop under the strain of the simulated environment, we are able to conclude that the Rifidi Edge can handle the requirements for a real-world deployment, but performance could be notably increased by separating the Database from the Rifidi Edge onto two separate machines, as the Database ended up being a bottleneck during bursts of 1,000 or more tags.
Setting up the Retail Scenario in your Environment:
Hardware Requirements: Required: One computer (at least an i3 processor) to run three Rifidi TagStreamer instances One computer (at least equivalent to the Toshiba i5 above) to run the Rifidi Edge Server and MySQL Database
Optional: TagStreamer can be leveled across three computers each running one instance of TagStreamer for each test case scenario Note: The Rifidi Edge Server configuration will need to be configured to connect to three separate IPs. (The first 5 IPs will point to the Tag Streamer instance invoking the Loading Dock scenarios, the next 35 IPs will point to the Tag Streamer instance invoking the Item Level Shelves scenarios and the last 10 IPs will point to the Tag Streamer instance invoking the Point of Sale scenarios).
The MySQL Database can be installed on dedicated Database Server hardware. Note: This will require the Retail Application running on the Edge Server to point to the Database Server IP address. Also make sure you have at least 100MB network bandwidth and on the same sub-net as the Rifidi Edge Server
Software Installation Requirements MySQL v5.1 – www.MySQL.com Rifidi Edge Server v1.2 – www.rifidi.org Rifidi Tag Streamer v1.1.1 – www.rifidi.org Retail Rifidi Edge Application (Retail) Events MySQL table – events.sql – used to store tag events during scenario execution Rifidi Edge Server configuration (rifidi.xml) Rifidi Tag Streamer configurations (TS_Retail_5_LoadingDocks.xml, TS_Retail_35_ItemLevelShelves.xml, TS_Retail_10_PointOfSale.xml) Retail Scenario download: http://www.transcends.co/wp-content/uploads/2011/05/Retail.zip
Setting up the Scenario Note: More details on how to use the Rifidi platform can be found at wiki.rifidi.org
1) Start the first Rifidi Tag Streamer instance and click on File|Load Test Suite to load the TS_Retail_5_LoadingDocks.xml. Note: Make sure to change the IP addresses in the configuration file to the IP address of the computer running this Tag Streamer instance and File|Save Test Suite.
2) Start the second Rifidi Tag Streamer instance and click on File|Load Test Suite to load the TS_Retail_35_ItemLevelShelves.xml.Note: Make sure to change the IP addresses in the configuration file to the IP address of the computer running this Tag Streamer instance and File|Save Test Suite.
3) Start the second Rifidi Tag Streamer instance and click on File|Load Test Suite to load the TS_Retail_10_PointOfSale.xml. Note: Make sure to change the IP addresses in the configuration file to the IP address of the computer running this Tag Streamer instance and File|Save Test Suite.
4) On the computer running the Rifidi Edge sever, place the rifidi.xml configuration file in the [Rifidi_Edge_Home]/server/config directory. Note: Make sure to change the IP addresses in the configuration file to the IP address of the computers running this Tag Streamer instance and the equivalent scenarios.
5) Copy the Retail Application into the Rifidi Edge server’s [Rifidi_Edge_Home]/server/applications directory. In the [Rifidi_Edge_Home]/server/application/Retail/database.properties file verify the com.emaise.jdbc.url=jdbc:MySQL://[MySQL_IP_Address]/emaise is set the the ip address of the MySQL 5.5 DB server instance, jdbc.user=root is set to the correct MySQL user and jdbc.pass=rifidi2010 is set to the correct MySQL password.
6) Start the Rifidi Edge Server and verify the MySQL Database Server is running
7) On the MySQL Database Server instance, verify the Retail database has been created, the events table has been created and at the start of each test delete all the records from the events table. Note: For use of the MySQL 5.5 Database please refer to www.MySQL.com for user documentation. – Use events.sql script to create events table.
8 ) After the Rifidi Edge Server starts, on the Edge Server console type loadApp Retail to start the Retail Application
9) For each Rifidi Tag Streamer instance, click on Test Units then click on TestUnit1 and on the menu bar click the run icon to start the Test case scenario. Note: You will need to repeat these steps for each of the three Tag Streamer instance.
10) To verify that the Retail Scenario is operating correctly, first on the Edge Server console type and readers and all 50 LLRP reader adapters should be in processing status, second monitor the cpu and memory usage on all the computers to verify CPU does not exceed 50% – 90% and memory does not exceed 50% available.
11) After you decide to end the test as the test cases are configured to run indefinitely so you will need to stop execution manually, the results can be analyze by querying the Retail Application MySQL 5.5 database. DB name: Retail. Table name: events. Note: For instructions on how to use MySQL 5.5 please refer to the www.MySQL.com documentation.
Future Planned Rifidi Edge Server Testing: Future tests with the Rifidi Edge Server will include scalability and performance writing to a queue (JMS), web services, Software as a Service (SaaS) and in a Cloud.