The inspiration for the approach implemented in the Proximity System is an observation that the concept of nearness is a generalization of set intersection. The idea follows from the notion of set description, which is a collection of the unique feature vectors (n-dimensional real-valued feature vectors representing characteristics of the objects) associated with all the objects in the set. Describing sets in this manner, at some level, matches the human approach to describing sets of objects. Furthermore, in comparing disjoint sets of objects, we must at some level be performing a comparison of the descriptions we associate with the objects within the sets. Thus, a natural approach for quantifying the degree of similarity (i.e. the nearness or apartness) between two sets would be to look at the intersection of the sets containing their unique feature vectors.
The sets considered in the Proximity System are obtained from digital images. For instance, Regions Of Interest (ROI) play an important role in discerning perceptual similarity within a single image, or between a pair of images. In this work, four different ROIs are considered. Namely, a simple set of pixels, a spatial neighbourhood, a descriptive neighbourhood, and a hybrid approach in which the neighbourhood is formed by spatial and descriptive characteristics of the objects. In terms of pixels, closeness between ROIs can be assessed in light of the traditional closeness between points and sets and closeness between sets using topology or proximity theory.
Finally, the code for the Proximity System was written by Garrett Smith and a technical report detailing the theory behind and the operation of the Proximity System is available at the University of Manitoba's Computational Intelligence Laboratory website (located at: http://wren.ee.umanitoba.ca/)
In order to incentivize users to contribute to the Portolan project, the app offers to the users several diagnostic network tools:
- Traceroute (with Multipath Detection Algorithm)
- AS (Autonomous System) path
- signal measurement
- it verifies if your Internet Service Provider limits BitTorrent traffic.
These tools are totally under user's control. Data collected by these tools is available to the user and is stored in
our servers, in a completely anonymous way.
This app sometimes runs background traceroute measurements and signal strength measurements. In order not to bother the user and not to affect the overall device's performance, measurements are limited to max 200 traceroutes per day, which means a peak traffic rate never higher than 1 KB/s and an average traffic rate never higher than 2 MB/day. Signal coverage measurements are completely costless in terms of energy or bandwidth, as the Portolan app passively collects signal strength samples only when other apps use the GPS. The application stops its background activity when the battery level decreases under 40%. The app does not send any personal data to our servers, and sends only the measurements results. Thus, it is not possible for us to connect measurements to the device that performed them. Finally, the user can monitor the amount of resources used by our application whenever he/she wants.
To add your devices, just run the integrated networkscanner.
It will save all computers with Hostname, IP-Adresse and MAC-Address.
Features in v1.4.8:
✓ Networkscanner to add new devices automatically
✓ Tasker / Locale-Plugin to automate wakeup of devices
✓ WAN-support to wake devices over internet (Please disable Broadcast in the expertsettings)
✓ Widget to start your computer right from your homescreen
✓ Online-status of your managed computers
✓ Manageable in groups
● "Wake on Lan" uses the WOL-Standard to wake up devices.
In order to use it, WOL must be enabled on each computer.
In order to wake devices over Internet, you have to configure adequate port-forwardings on your router.
● The networkscanner scans for all devices, which are currently online.
● Because of certain circumstances (like special network-topologies),
the networkscanner may find wrong MAC-Addresses.
If the wake-process fails, please check for a correct MAC-Address.
● Please search the web for more information about configuration.
There are several tutorials available.
● The online-status of a computer may be wrong because of several issues
like installed firewalls.
OpenMobileNetwork for Android (OMNApp) is a background service that actively collects mobile network data in a crowd-sourcing approach in order to estimate and derive base station and WiFi hotspot positions. It further acquires live measurement data, such as the total traffic produced on smartphones or service usage information, in order to enable the modeling and visualization of the current/historic state of the network.
By using this app, you contribute with your data in building an open-source semantic dataset for mobile networks within the OpenMobileNetwork research project. Please have a look at: http://www.openmobilenetwork.org/
OMNApp has been developed by Abdulbaki Uzun and Thilo Geismar. This app is part of the Service-centric Networking department of the Technische Universität Berlin, Germany.