Archive for July, 2010

Meeting with DC 28 July 2010

July 28th, 2010 No comments

Met with Davide to talk about where I currently am in my research.

I talked him through Ideas about Vector Clocks for Proximity and Location that I had recently transcribed into a document from my notebook, and we came up with some plans for the next few weeks whilst he is away, and agreed to meet when he is back at the end of August.

The following are some notes we made whilst discussing my idea:

Formal notation regarding node location overlaps.

Ovy < Owy  → message v,w

When the overlap of the set of locations that v visits in relations to y, is less than the set of locations that w visits in relations to y, then pass the message from v to w.

We discussed security withing DTNs and realised that neither of us has much knowledge of this, so Davide suggested I look up the work of Eiko Yoneki, who may have published in this area, as it is something we will have to consider.

We also discussed how to compare the graph generted from locations, and the graph genereted from proximity, and how we could combine them. Davide suggested looking at the work of Schlomo Havlin.

Finally we talked about where to go from here. I will look at some datasets, including CABSPOTTING, where there is fine grained location data, and try to test the hypothesis that I came up with. for example, look at the overlap of locations for individuals over certain timescales, and produce a probability distribution of overlap. Also, make a new graph whihc is formed by overlaps based on whether a node visits a location (with no ordering), and see whether this has any interesting properties. Overall, try to use the datasets to test out all of the hypothesis.

  • Look up the work of Eiko Yoneki
  • Look at the work of Schlomo Havlin.
  • Find datasets and form into graphs
  • Test all hypothesis questions
Categories: Uncategorized

Meeting with Paddy 8th July 2010

July 8th, 2010 No comments

Talked about the project so far, I said that I had started a workthrough of people’s movement patterns, and had come up with many ideas around it, and said that what I would like to do is present what I had found so far, in terms of node statistics at any given point in time, and some interesting aspects that came out.

I also listed some of the questions I had thought about during this exercsise, as follows:

  • How do we collect data about mobility
  • How do we define what a location is
    • What types of location are there?
  • What is a node?
    • A user? A phone? A user carrying a phone?
    • A location? A series of locations
  • How are edges defined?
    • users who meet (at a location, or are proximate)
    • Locations that are connected when a user travels between them
  • What can nodes learn about the network?
    • VC of proximity times (windows)
    • VC of location visits
    • Knowledge of location probabilities
    • Computed routes between nodes based on co-locations
    • Expected next delivery times for messages (+/- error)
  • How can nodes communicate?
    • Ask for expected delivery time to X
    • Share knowledge of routes to X
    • Share location and proximity probabilities over time
    • Use Agent like behaviour to decide when to pass messages
    • Feedback mechanism to re-enforce routes
  • How do we deal with privacy? (not main focus)
    • Share fine-grained location information only with trusted peers
    • Encrypted payloads

We agreed that the most interesting part is the forward prediction of location, and Paddy said that if I can do all of this, then it will be my PhD. Paddy also said that I should spend some time understanding the realms of computational complexity, just so I can recognise it when I see it.

Also spoke about funding. Paddy is looking at finaces this week.

I asked about getting a new 2nd supervisor, and Paddy suggested I look for a new primary supervisor, someone who I could knock on the door and ask for help – as he is still a visiting supervisor, he will be here a bit, but not much. I said that I had spoken to Padraig Cunningham, and he suggested I speak to Paddy about path to finishing, and then come and see him. Paddy intimated that he would be a good supervisor, but that I would have to be very concise when discussing PhD stuff with him, as he won’t like waffle!

New tasks:

  • Plan a presentation to Paddy and Invite Davide along
  • Look up Computational Complexity
  • Look up Graeme Stevensons Paper on LOCATE

Existing Tasks:

Project specific tasks

  • Plan short experiment to collect ground truth location data
  • Prepare to show Paddy the finished vector clock implementation (workthrough), picking out interesting parts and identifying next steps
  • Summarise findings from vector clock implementation (workthrough)

Other tasks

  • Implement vector clocks in simulator, based on location
  • Read Knox’s thesis.
  • Read Barabasi’s book.
  • Generate a rough outline of chapters for my thesis, and identify the main areas for the background section
  • Write down ideas about how to define locations (draft)
  • Dig out reviews on DTN’s- especially about patterns and finding important nodes
Categories: Uncategorized

Meeting with KM, SB and DC about Social Sensing data 7th July 2010

July 7th, 2010 No comments

Met with Kevin McCarthy, Steven Bourke and Davide Cellai about what the Social Sensing study data could be used for. We are all interested in movement patterns and prediction, and decided that we should work together.

The data itself is currently stored in a MongoDB, which is a document storage database, and is apparently very easy to query. The data itself is stored in approximately 200GB of seperate files. Kevin assured us that we would be able to access this data.

Steven suggested a number of sources of similar (location) data:

  • GeoLife, by Microsoft Research.
  • SimpleGeo
  • SpotRank by Skyhook

He also described how he collected location data from Gowalla, for ~2000 users in Dublin. His masters thesis was about DTN with sensors, and so his interests are in line with mine and DC’s.

We agreed to meet next week to brainstorm some ideas worthy of collaboration.