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Quero: A Fast Distributed File Searching Network Implementation

Quero is a distributed file sharing system where users can search for files on other computers and get high-quality results quickly. It cannot be blocked or shut down due to its decentralized nature. The project aims to offer ease of use, platform independence, and efficient file transfers. It follows a distributed searching approach inspired by Napster and FreeNet, promoting network stability.

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Quero: A Fast Distributed File Searching Network Implementation

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  1. Project Quero A fast distributed file searching network implementation Kenneth Philbrick -- kphilbri@cs Chia-Yang Hung -- cyhung@cs Bret Sherman -- bret@cs David Carothers -- davidjc@cs

  2. 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.

  3. 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

  4. Project Goals • 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. • File Transfer: Once the user receives search results, they can request file transfer from other users who have files they want. • Ease of use: Our program will be extremely easy to use, much like Napster. • 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. • Platform independence: Quero will run under environments that support Java™ and the Swing UI, such as Windows and Linux.

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

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

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

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

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

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

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

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

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

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

  15. Questions?

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