Project Quero A fast distributed file searching network implementation Kenneth Philbrick -- Chia-Yang Hung -- Bret Sherman --

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Presentation transcript:

Project Quero A fast distributed file searching network implementation Kenneth Philbrick -- Chia-Yang Hung -- Bret Sherman -- David Carothers --

Overview Quero is a distributed file sharing system. Users can search for files on other computers and get high quality results quickly. Quero can not be blocked or shut down because there is no centralized control.

Basic Assumptions Non life-critical, widely duplicated data –Not necessary to return all results There is a set of nodes running Quero that are connected for long periods of time. –Several hours at least –Promotes network stability

Project Goals 1.Search: User's should be able to search for files, and view the results of their search. This does not guarantee that all matching files will be returned or even a majority of them. However, because we are assuming duplicated, non-life critical data this is acceptable performance. 2.File Transfer: Once the user receives search results, they can request file transfer from other users who have files they want. 3.Ease of use: Our program will be extremely easy to use, much like Napster. 4.User's aren't overburdened: Regardless of what role a node may play in the topology of our network, a user should never feel a significant performance drop on their CPU or network bandwidth. 5.Platform independence: Quero will run under environments that support Java™ and the Swing UI, such as Windows and Linux.

Distributed searching background Napster: the centralized server approach Central server A 1. Advertise files B 3. Results results 4. Download download query 2. Search

Distributed searching background FreeNet: the fully distributed approach client 1. Search search 2. Propagate forward 3. Results results 4. Download download

Quero Search Hierarchy Maser Browsers Leaf Nodes Top-Level Master Browsers A balance between the two extremes

Quero Searching Leaf node Master Browser Rest of network 1. Advertise files 2. Search search 3. Propagate 4. Results results 5. Download download

Quero Search Caching In order to improve performance search results from higher nodes are cached on lower nodes. Master Browser Leaf node 1. Advertise files Master Browser Leaf node 2. Search search results 3. Results Cache results 4. Another search Another search 5. Cache hit Cached result download 6. Download

Search Tree Building node How to turn this? Leaf node Master Browser Into this

Search Tree Building 1. One lonely node node 2. Will become a Master Browser Master Browser 3. New nodes can discover it node Leaf node 4. And advertise their files 5. What if the Master Browser Wants to go down?

Search Tree Building What if a Master Browser wants to leave the network? Master Browser Leaf node 1. Call for an election 2. Reply with heuristics 3. Choose best node 4. Reconnect

Bandwidth Splitting If a Master Browser becomes overburdened, it can promote one of its children and split the remaining children.

Resource Splitting Master Browsers are limited to the number of children and files they can have. Resource splitting alleviates this.

Questions?