I am working on a research about the performance evaluation about various RTOS for embedded system. But I found the information is not easy to get. I've read a paper which discusses the number of priority levels of different RTOS. Then I tried to find how many levels for AVIX operating system. But I can't find it. Are there any tips to search this kind of information?
Not only is performance data not always easy to obtain, but for commercial RTOS in many cases publication of performance data derived from comparative testing is explicitly prohibited in the licence agreement. So you will be restricted in what you can do with this information.
You can probably determine what you need from the API documentation. You have to register with AVIX to get access to their downloads section, but I would imagine the information is available there.
That said the number of priority levels has no bearing on performance.
Related
The Reliable Services Overview topic has a section, at the bottom, called When to use Reliable Services APIs. In there, one list item says:
Your application needs to maintain change history for its units of state*.
The star at the end is explained just a little bit further down:
* Features available at SDK general availability.
The SDK has reached general availability by now, but I cannot find any information about how to make use of the "Maintain change history for its units of state"-feature or even a suggestion of what that actually means.
I'm asking here, in hope that someone can shed any light on this. I'm interested in knowing whether this feature is indeed available, or if not when it is supposed to be available, or if it has been abandoned.
Some insights on the intended design and functionality of this feature would also be much appreciated.
It describes the scenarios in which you might use the reliable collections. It can be used to keep multiple versions of an object and build a history of changes. (like delta's or snapshots)
This way you can create an event source. (it would require some coding on your end though)
Unit of state: entry in the State manager
I have built a recommender systems which has tens of thousands of items and their feature descriptions, but no user profiles as of now. I am looking for pointers to approaches that can help me bootstrap the system, so I can do some evaluation. I would appreciate any pointers to papers/applications that have addressed this problem.
How to deal with the cold-start problem depends a lot on your specific application.
An easy way of dealing with the user cold-start problem is to present the new user with random items, or the most popular items, or hand-selected items, and start learning from them.
Another way is to present users with a questionnaire, and then present items to them according to the results. Or you directly show them items/products and let them rate/select the ones they like.
Also note that in web-based system you usually know some things about your users: Which operating system/browser they use, where they (roughly) come from, which language they speak.
All this information can be used.
Papers:
see the Wikipedia article on the topic
My answer to another question on StackOverflow lists some papers for dealing with new items - most of the methods would also be applicable to new users.
Another approach is to select products/items that will help you most for learning about the user. Just out of my head, you can find them by querying Google Scholar for "recommendation" and the terms "decision trees", "active learning", "user cold-start", and so on.
I want to build a web app similar to Reddit.com, where you have multy level of comments, lots of reads and writes. I was wondering if nosql and mongoDB in particular is the right tool for this?
Comments -- it's really thing for nosql database, no doubt. You avoiding multiple joins to itself. And it's means that your system can scale out!
With mongodb you can store all hierarchy within one document. Some peoples can say that here will be problems with atomic updates, but i guess that it's not a problem because of you can load and save back entire comments tree. In any way you can easy redesign your system later to support atomic updates and avoid issues with concurrency.
Reddit itself uses Cassandra. If you want something "similar to reddit.com," maybe you should look at their source -- https://github.com/reddit/reddit/wiki.
Here's what David King (ketralnis) said earlier this year about the Cassandra 0.7 release: "Running any large website is a constant race between scaling your user base and scaling your infrastructure to support it. Our traffic more than tripled this year, and the transparent scalability afforded to us by Apache Cassandra is in large part what allowed us to do it on our limited resources. Cassandra v0.7 represents the real-life operations lessons learned from installations like ours and provides further features like column expiration that allow us to scale even more of our infrastructure."
However, Rick Branson notes that Reddit doesn't take full advantage of Cassandra's features, so if you were to start from scratch, you'd want to do some things differently.
I am about to use Apache Hadoop, the headlines read:
The Apache Hadoop project develops
open-source software for reliable,
scalable, distributed computing.
I can relate "scalability" to programming, but I just don't know how this "distributing" can help me in my development. According to wikipedia:
A distributed system consists of
multiple autonomous computers that
communicate through a computer
network. The computers interact with
each other in order to achieve a
common goal
So does this mean I can deploy my web apps across multiple computers and do some sort of "intense computing"? The terms that come into my mind are Content Delivery Networks and Cloud Computing.
Web development has always been about distributed computing, since clients have been on different machines to the servers they talk to, web pages can pull in resources from many servers to build a page's content, and servers may talk to other machines to achieve their goals. CDNs make this more obvious than before, but really they're just an evolution, an introduction of a virtualization/indirection layer between what you ask for and the hardware used to provide it.
Clouds are about taking the concepts of virtualization and applying them to remote hosting, both of low-level OSes and higher-level software platforms. The really interesting thing about them is that this enables different business models on the part of customers (and with different risks too, but that's mostly not related to the fact that it's distributed computing but rather that it is not wholly under your control in your own jurisdiction).
I've found that the most effective use of distributed computing is when you think in terms of connecting together distinct services, each of which with different capabilities (which might be for technical reasons, or might not; sometimes, it's for business or legal reasons that things have to be divided up) and where each of those services may be provided by many components in multiple locations. There are, and continue to remain, issues with balancing the need for performance (which is a force that brings components together) and the need for robustness (which tends to lead to distribution and replication) within the overall context of the general capabilities map.
My goodness! That paragraph sounds like terrible piffle! What I'm trying to say is that it's all trade-offs, and you should be prepared for not getting it right first time.
(Hadoop is a mechanism for doing a distributed file store, and for efficiently applying certain classes of operation – those that fit well with MapReduce or other similar scatter-gather algorithms – across that whole dataset. If that shoe fits, use it. But it doesn't solve all problems, and thank goodness for that! Things that can do everything tend to look very much like things that can't actually do anything at all, and usefulness and comprehensibility come in the restrictions.)
Hadoop is typically used to process massive data sets by distributing the processing of that data set across multiple machines.
What this means is you probably don't want to use it to "deploy an application". You might use it to process stats on your application, however. For instance, you might have very large logs of user data. This would happen if your user data grows to become too large to fit on a single hard drive, and/or would take too long for one machine to process stats on (using standard methods like an SQL query).
Ygam. While the traditional role of "clients" and "servers" have been pretty stable from 1960 till about 2005.
I believe with every fiber of my being, that distributed computing is that we all carry processors around in our pockets.
Phones do computing work. Phones do NOT need centralized servers, but they DO benefit from them.
Phones , Smartphones, tablets are an example of where distributed computation is going.
You can make a wifi base-station out of an Android device now. So now a phone becomes a server of sorts for just that instant in the coffee shop that you turn it on for that cute person next to you without internet ....and now I digress.......
I am learning to program distributed computing system. And the system I need to work on would require to perform computation on graph data (social network data) in parallel environment.
After searching on the internet, I come down to the issue regarding to the task distribution. It seems that many of such kind systems are designed by worker requesting task from master e.g. volunteer computing [1] or hadoop map/reduce transmit heartbeat.
My question is - is there any task distribution/ assignment is designed with the style in that the master would proactive assign task to slaves? What issues may need to pay attention to when programming such mechanism?
I think I may be wrong in some concepts that I am not aware of. So I appreciate any suggestions.
Thanks for advice.
[1]. boinc.berkeley.edu/heien_09.pdf
No, you're exactly right -- the master-wokrer pattern is well established. For a certain flavour of it, take a look here for a message-queue based system, or look it up on wikipedia.
Tim,
Thanks for providing that link. Although it talks about Microsoft solution, the information in the article is very useful, which serves as good keywords for me to search further information.
Thanks again for your help!