Hi Lahiru,

Thanks for the prompt reply.

*+1 for*
*we can find the polynomial in each minute, considering 10 minutes of past
data, we can change this if required.*

If we are getting the health stats events uniformly for every 10 seconds.
my question is resolved. (I thought that we are getting in a random manner).

Can I add the things in my proposal regarding "Curve Fitting"?

Do you think that any other important things I need to add in my proposal?

*T. Pranavan*
*BSc Eng Undergraduate| Department of Computer Science & Engineering
,University of Moratuwa*
*Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
*Mobile| *0775136836

On 25 March 2015 at 10:09, Pranavan Theivendiram <[email protected]>
wrote:

> Hi Lahiru,
>
> Thanks for the prompt reply.
>
> *+1 for*
> *we can find the polynomial in each minute, considering 10 minutes of past
> data, we can change this if required.*
>
> If we are getting the health stats events uniformly for every 10 seconds.
> my question is resolved. (I thought that we are getting in a random manner).
>
> Can I add the things in my proposal regarding "Curve Fitting"?
>
> Do you think that any other important things I need to add in my proposal?
>
> *T. Pranavan*
> *BSc Eng Undergraduate| Department of Computer Science & Engineering
> ,University of Moratuwa*
> *Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
> *Mobile| *0775136836
>
> On 25 March 2015 at 09:59, Lahiru Sandaruwan <[email protected]> wrote:
>
>> Hi,
>>
>> +1 for using Common math library, as we already using it.
>>
>>    - Currently we have calculating numbers per minute, so it is not per
>>    specified number of events, but for a specified time.
>>    - IMO we can find the polynomial in each minute, considering 10
>>    minutes of past data, we can change this if required.
>>    - Normally, health stat events are received in each 10 seconds.
>>    - Therefore we will have 60 ( = 6 * 10) events per 10 minutes.
>>
>> On Wed, Mar 25, 2015 at 9:11 AM, Pranavan Theivendiram <
>> [email protected]> wrote:
>>
>>> Hi Lahiru and Raj,
>>>
>>> I have gone through the curve fitting materials that you have provided.
>>> I have understood the regression part and prediction of degree polynomials.
>>> We can use apache common math libraries to do this. I have a question below.
>>>
>>> How often we are going to find the polynomials?
>>>
>>> For example,
>>>
>>> If we have *3 samples* events during *10 minutes interval*, then we can
>>> produce a second degree polynomial. (We will get constants *a*,*b*, and
>>> *c*). If we are going to use this second degree polynomial for next *60
>>> minutes *(Suppose in this 60 minutes we are getting *200 samples *events).
>>> As we can see our *extrapolation
>>> <http://en.wikipedia.org/wiki/Extrapolation>* becomes a severe problem
>>> in this particular example.
>>>
>>
>> What do you mean by " our *extrapolation
>> <http://en.wikipedia.org/wiki/Extrapolation>* becomes a severe problem"?
>> Complexity of the calculation of predicted value?
>>
>> Thanks.
>>
>>> I do not know how earlier versions handle this scenario.
>>>
>>> Can you tell that are we going produce new polynomials for *a specified
>>> time* or *a specified number of events*?
>>>
>>> Please clear this issue.
>>>
>>> *T. Pranavan*
>>> *BSc Eng Undergraduate| Department of Computer Science & Engineering
>>> ,University of Moratuwa*
>>> *Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
>>> *Mobile| *0775136836
>>>
>>> On 24 March 2015 at 09:02, Lahiru Sandaruwan <[email protected]> wrote:
>>>
>>>> Thanks Pranavan,
>>>>
>>>> I'll have a look.
>>>>
>>>>
>>>> On Tue, Mar 24, 2015 at 8:52 AM, Pranavan Theivendiram <
>>>> [email protected]> wrote:
>>>>
>>>>> Hi Lahiru and Raj,
>>>>>
>>>>> This is my draft proposal which has been done up to 50%. I am going to
>>>>> add things about curve fitting as well. Still many things need to be 
>>>>> added.
>>>>> Please comment on my initial draft.
>>>>> I am expecting pros and cons regarding my proposal. Please find the
>>>>> link for the initial draft below.
>>>>>
>>>>>
>>>>> https://docs.google.com/a/cse.mrt.ac.lk/document/d/1TzHYI2o9bIdZWj4qAffNmH5FTgeTOV4TuSsxlISlU8c/edit?usp=sharing
>>>>>
>>>>> *T. Pranavan*
>>>>> *BSc Eng Undergraduate| Department of Computer Science & Engineering
>>>>> ,University of Moratuwa*
>>>>> *Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
>>>>> *Mobile| *0775136836
>>>>>
>>>>> On 22 March 2015 at 23:36, Pranavan Theivendiram <
>>>>> [email protected]> wrote:
>>>>>
>>>>>> Thanks Lahiru for the prompt reply. I have already started working on
>>>>>> the proposal. I will send it before tomorrow.
>>>>>>
>>>>>> *T. Pranavan*
>>>>>> *BSc Eng Undergraduate| Department of Computer Science & Engineering
>>>>>> ,University of Moratuwa*
>>>>>> *Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
>>>>>> *Mobile| *0775136836
>>>>>>
>>>>>> On 22 March 2015 at 23:31, Lahiru Sandaruwan <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>> Yes, You have found the information correctly and on right track. It
>>>>>>> would be great if we can incorporate CEP 4.0.0 changes as it would 
>>>>>>> minimize
>>>>>>> our customized function.
>>>>>>>
>>>>>>> I would like to suggest you starting the drafting of the proposal as
>>>>>>> you have some background now.
>>>>>>>
>>>>>>> Thanks.
>>>>>>>
>>>>>>> On Sun, Mar 22, 2015 at 9:48 PM, Pranavan Theivendiram <
>>>>>>> [email protected]> wrote:
>>>>>>>
>>>>>>>> Hi all,
>>>>>>>>
>>>>>>>> With the few days of research on the project "Introducing “curve
>>>>>>>> fitting” for statistics prediction algorithm of Autoscaler". I have 
>>>>>>>> found
>>>>>>>> followings regarding the project
>>>>>>>>
>>>>>>>>    1. ClusterMonitor class passes the calculated values from the
>>>>>>>>    CEP. This value passing happens after 
>>>>>>>> org.apache.stratos.messaging.event
>>>>>>>>             happens.
>>>>>>>>    2. RuleTasksDelegator class calculates the prediction values
>>>>>>>>    using the values(Ex gradient) from the CEP
>>>>>>>>    3. The classes in the package org.apache.stratos.cep.extension
>>>>>>>>    deals with the analysis of data in the real time and publish the 
>>>>>>>> relevant
>>>>>>>>    summarized health stats, which are needed for the autoscaling.
>>>>>>>>
>>>>>>>> So according to my understanding, I need to modify above mentioned
>>>>>>>> classes, in order to implement the curve fitting for statistics 
>>>>>>>> prediction.
>>>>>>>>
>>>>>>>> Furthermore,for this project, we can use the regression
>>>>>>>> implementation of CEP 4.0, which is expected to be released on May 15th
>>>>>>>> according to WSO2 public jira. I am planning to do a feasibility study 
>>>>>>>> for
>>>>>>>> the first two weeks of the project, where we can explore other better
>>>>>>>> options as well.
>>>>>>>>
>>>>>>>> Am I on a right track? Please share your thoughts on this.
>>>>>>>>
>>>>>>>> [1] https://wso2.org/jira/browse/CEP
>>>>>>>>
>>>>>>>> Thanks
>>>>>>>>
>>>>>>>> Regards
>>>>>>>> *T. Pranavan*
>>>>>>>> *BSc Eng Undergraduate| Department of Computer Science &
>>>>>>>> Engineering ,University of Moratuwa*
>>>>>>>> *Intern Software Engineer**| WSO2 Lanka (Pvt) Ltd.*
>>>>>>>> *Mobile| *0775136836
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> --
>>>>>>> Lahiru Sandaruwan
>>>>>>> Committer and PMC member, Apache Stratos,
>>>>>>> Senior Software Engineer,
>>>>>>> WSO2 Inc., http://wso2.com
>>>>>>> lean.enterprise.middleware
>>>>>>>
>>>>>>> phone: +94773325954
>>>>>>> email: [email protected] blog: http://lahiruwrites.blogspot.com/
>>>>>>> linked-in: http://lk.linkedin.com/pub/lahiru-sandaruwan/16/153/146
>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> --
>>>> Lahiru Sandaruwan
>>>> Committer and PMC member, Apache Stratos,
>>>> Senior Software Engineer,
>>>> WSO2 Inc., http://wso2.com
>>>> lean.enterprise.middleware
>>>>
>>>> phone: +94773325954
>>>> email: [email protected] blog: http://lahiruwrites.blogspot.com/
>>>> linked-in: http://lk.linkedin.com/pub/lahiru-sandaruwan/16/153/146
>>>>
>>>>
>>>
>>
>>
>> --
>> --
>> Lahiru Sandaruwan
>> Committer and PMC member, Apache Stratos,
>> Senior Software Engineer,
>> WSO2 Inc., http://wso2.com
>> lean.enterprise.middleware
>>
>> phone: +94773325954
>> email: [email protected] blog: http://lahiruwrites.blogspot.com/
>> linked-in: http://lk.linkedin.com/pub/lahiru-sandaruwan/16/153/146
>>
>>
>

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