CSE 599c Hot Topics in Data Management Systems

Lecture 14: Federated Databases.

Autonomy and Incentives

Magdalena Balazinska

Winter 2006

Today's Paper

M. Stonebraker, P. M. Aoki, W. Litwin, A. Pfeffer, A. Sah, J. Sidell, C. Staelin, and A. Yu. Mariposa: A Wide-area Distributed Database System. VLDB Journal (5)1, 1996.

Outline

Motivation for economic-based dist. DBMS

Overview of Mariposa

Discussion

Benefits and challenges of economic model

Practicality of the solution

Alternate designs

Design Goals

Wide-area network deployment

Scalability to a large number of sites

Data mobility

No global synchronization

Total local autonomy

Easily configurable policies

Interestingly,

They do not address incentives directly

Mariposa Overview

Users assign budget to each query

Bid curve

Broker holds auctions for query hunks

Sites bid for query hunks

Sites also bid for data fragments

Design Assumption

There exists a network bank

Users and servers have accounts

Questions

Who sets-up the bank?

How much money should be in the bank?

How do users earn money?

How do users assign budget to query?

How to prevent users from inventing money?

Mariposa Architecture

Tailored with Rules

From [Stonebraker96]

Bid Selection Algorithm

Start with smallest total delay combination

For each bid, compute cost-gradient

D cost / D time

Try substituting one at the time

Check if “difference” is higher

B(D') – C' > B(D) – C

Mariposa Architecture

Tailored with Rules

From [Stonebraker96]

Computing Bids

Bid: (Cost, Delay, Expiration)

Cost = billing rate * resources needed

Delay = expected delay * load * safety

Expiration = delay + constant

How about network bandwidth?

Policies

Per fragment billing rate adjust for load

Reject bids when billing rate below threshold

Relation between “hot” fragments and queries

Mariposa Architecture

Tailored with Rules

From [Stonebraker96]

Storage Manager

Collect revenue history for fragments

Compute net present value of revenue

Buy on demand or prefetch

Offer price = value – value alternates + price received for alternates

Owner conducts auction for fragments

When value of fragment A greater at site 1 than site 2?

Conclusion

Economic-based approach promising

Use local info to reach globally good decisions

Paper lacks analysis of agent strategies

Approach intertwines incentives and policies

Main limitation: complexity and overhead

Other: price volatility and frequent moves

Did not demonstrate power of rules

2006-01-01T23:16:26