Limitations

1

This talk will…

|Explain how the underlying structure of different

P2P systems affects querying

|Compare the relative advantages and

disadvantages of each

|Summarise issues in query processing

|Show current directions for research in P2P

search

Related: [3]

CAP Theorem Related: [3][4]

You can only have two of these three properties

The nature of the system is determined by this choice

CAP Theorem: Sacrifice Partitions

Classic Distributed Systems style

Examples: single site & clustered databases

CAP Theorem: Sacrifice Availability Pessimistic locking

Examples: distributed databases

CAP Theorem: Sacrifice Consistency

Optimistic, conflict resolution, expirations Examples: DNS, Web Caching, PIER

Querying the Network

Querying is limited by constraints on bandwidth and processing

Addressed by

Minimizing data sent over network

Applying economic cost models

On an internet scale this is not sufficient for distributed databases

Consistency is often sacrificed (CAP Theorem)

From [19]

29

PIER: Example 2

{Takes, {st-id, m-id}}{Module, 1002}{Module, 2001}{Takes, {1, 1002}}{Takes, {4, 1002}}{Takes, {2, 2001}}{Takes, {3, 2001}}

PIER: Example 2 (Problems)

name from

(student innerjoin takes on student.st_id = takes.st_id )where mid =“1002”

A measurement study of Napster and

. In Biennial Conference on Innovative Data Systems Research . ACM Symposium on Operating Systems Principles

A game theoretic framework for incentives