Researchers unfortunately are usually researching outside of known frontiers. That’s why they call it “Research”. Just like the explorers of old, researchers go forth to prove their premise and as a result are awarded a Doctorate or a consulting contract.
Unfortunately, because Researchers work in uncharted territory, so much of their work has to be developed as they go.
A year ago, Chris asked me – “How can we measure the P2P on the Internet?” He wasn’t talking about the bits per second traffic across the backbone, he was referring to an as yet un-described ephemeral value proposition.
For example, if you decide to buy a second hand car there is the “Car-guide”, the “Red-book” valuation, the local mechanic, the blokes at the pub (who all have an opinion). So getting a feel for what a second hand car should be worth, what its fuel consumption is and it’s reliability or lack of, is rather an easy proposition for any serious purchaser.
On the other hand, on P2P networks, it is a rather different kettle of fish.
1. Is the listed file real or fake?
2. Is it the version that I wanted?
3. What is the quality of the listed file?
4. Will my “device” handle the codec or format once I have downloaded it?
5. Is there any malware or a virus in it?
6. How much of my monthly bandwidth allowance will I use up to download this file?
We researched published papers on the topic and came up short of what we perceived to be the required “Ratings” scheme for an expanded P2P interactive trading methodology.
Our research has attempted to give each of these items a value – thusly:
For individual File calculations:
1. F – for Fake = Number +/-
2. V – for perceived customer satisfaction
3. Q – for quality (bps and pixels) including L+/- for Lossy/Lossless
4. E – for encoding methodology
5. M – for malware/virus inclusion
6. B – Size of file
and we have added three additional factors;
7. N – Network storage cost
8. T -- Network Transmission/Transit cost
9. O –
For individual Peer review, we add Credibility and History. C & H
FVQ(L)EMBNTOCH
By monitoring downloads on the ED2K networks, we have been able to utilize the above as a P2P file scoring system.
There are two different applications for the scoring system as we currently apply it.
To calculate a value for the file
To calculate the popularity for the file
We recently reported on Michael Jackson’s Thriller video as
being the most popular Video in
That is not quite correct. If we compare it to the recently aired (Foxtel) program IOUSA, Thriller scores extremely low. However, amongst its peer group – i.e.: Popular Music Artists, Thriller scored extremely highly.
We consider that our research in this area has led to a unique scoring methodology that we have called PTVC (Peer Trust Value Cost).
We shall be talking about Peer Trust Value in the future and how it can impact all facets of internet utilisation, inclusive of content creators, content owners and of course the most important category, content consumers.
References:
Gnunet-peer-info trust value
Peertrust: supporting reputation-based trust for
peer-to-peer electronic communities. …
L Xiong, L Liu - IEEE Transactions on, 2004
Identifying local trust value with neural network in P2P
environment
Huang Baohua Hu Heping Lu Zhengding Coll. of Comput.
Sci. & Technol.,
A Time-Based Peer Trust Evaluation in P2P E-commerce
Environments
Yan Wang and Vijay Varadharajan
Department of Computing,
DynamicTrust: The Trust Development in Peer-to-Peer
Environments
Yan Wang and Vijay Varadharajan
Department of Computing,
Social Computing-Based Trust Establish in E-Commerce
Xincheng Wang1, Fengming Liu2, Rongrong Yang3, and Fu Xie4
College of Information Technology, Jinan Radio and TV
University, Jinan,College of Information Sciences and Technology, Donghua
University, Shanghai 201620, Department of Tourism Management, Jinan Technology
College, College of Information Sciences and Technology, Shandong Normal
University, Jinan, P. R. China
