the daily grind - 09/02/11

Worked on code to get the cumulative totalling of applications in the graphs. Not fully done yet, so not a fruitful day. Should've finished it, really. Been distracted.

But day isn't over yet. Will read up on gossip models and some associated literature, before going to bed.

Wonder how the HH manages to read so many papers/book chapters in one day.

7/2/11

Second successive day, lost to students and admin work!

Started off the morning with the tutorial that I had to give. Then worked on emails, for the plagiarism case that I detected.

The EPiCS meeting that I'm only 'guest attending' anyway, turned out to be two hours instead of one!

Gah! Not good at all. Shall try to finish a bit of coding before I sign off for the day.

3/2/2011

My day wasn't quite so productive. I spent it looking at the code and I think I know why things started working better. Remember I told you that there's buyers and sellers in my scheme of self-adaptation? Well, it turns out that in my code somewhere, I tried to be sophisticated and was making the sellers use a bi-modal distribution for creating their "asks", while the buyers were creating their "bids" using a normal distribution. Naturally, in the marketplace, the number of transactions were very limited! Also, to measure how much traders were deviating from the target, I was using an absolute number, which doesn't make sense. Deviation for each trader has to be measured relative to its own target. Once, I corrected that, the number of traders getting 'satisfaction' increased dramatically.

Hmmm...I started off thinking that I hadn't done much. But writing that down, makes me think that I did achieve something. It wasn't much, but at least there's some clarity and understanding of why things were working the way, they were.

I've still got to code up other composition types and verify that this scheme works for all of them, but I'm optimistic (hey! I'm a PhD student. I'm optimistic, by definition. Any sane person would've given up long ago ;-) ). Hopefully, I'll get at least something done tomorrow, though I don't have much hope, because I've got 3.5 hrs of student evaluation. Sigh.

1/2/2011

I don't understand it. I changed about three things and now the simulation works better than I expected!

If I spend a day figuring out why it works, this could be a breakthrough!

No further progress!

goals - 1/2/2011

I thought I'd follow Gemma's example and write down the set of short-term goals, I'd need to converge to a PhD.

So here goes:

1) Get code working for multiple composition types

2) Extend literature survey on self-adaptive services to qualify for a journal

#1. Write JouRNAL pAPer!!

3) Work on mathematical model for CDA-based adaptation

4) Write a qualitative review of CDA-based self-adaptation {contrast with other forms, perhaps}

5) Implement gossip algorithm for communication

#2. Write another paper - perhaps conference, perhaps journal

#3. Start writing thesis

6) thesis - Get literature review down

7) thesis - Description of CDA-based adaptation, design decisions

8) thesis - Evaluating this CDA-based adaptation

9) thesis - Introduction to thesis

31/1/2011

# Fixed the following bugs:

1) Sellers and buyers were using different distributions for generating asks/bids. Buyers were using normal distribution, while sellers were using a bimodal distribution. Now, both use normal distribution

2) Prevent sellers from bidding in auctions when there are no buyers present.

3) last_transaction is now set to None, at the beginning of a new trading round, rather than the end of the last trading round. This prevents buyers from getting a Null object while reformulating their bids. Behaviour seen since objects are not copied, objects are passed-by-value (python's consenting adults philosophy)

Not enough PROGRESS!! Some apps don't appear in the logs at all now. Very frustrating.

# Created a set of reading notes for MSc. student

# Created and delivered tutorial for tutees

# No response from James on algorithm. Perhaps I should wait for a couple of days and ping him.

the daily grind - 28/1/2011

Tried to figure out why buyers who weren't able to trade successfully, continued to be unsuccessful, even when successful buyers dropped out of the market.

Found bugs:

1) If no transaction happened, then modelling the buyer's next bid on the market's last transaction results in an empty bid

2) The sellers from previous successful transactions, drop out of the market, while the buyer's don't. This is the exact opposite of what we want.

Emailed James about help with describing the algorithm formally and doing some analysis (maybe probabilistic or game theoretic). Obviously, he won't read my paper immediately, but any critical response from him, over the next week, would be good.