Ocean Store - Distributed Operating Systems - Lecture Slides, Slides of Operating Systems

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OceanStore

Global-Scale Persistent Storage

OceanStore Context:

Ubiquitous Computing (I)

• Computing everywhere:
  • Desktop, Laptop, Palmtop, Cars, Cellphones
  • Shoes? Clothing? Walls?
• Connectivity everywhere:
  • Rapid growth of bandwidth in the interior of the net
  • Broadband to the home and office
  • Wireless technologies such as CDMA, Satellite, laser

What do we need for personal information

management?

Questions about information:

• Where is persistent information stored?
  • 20

th

• century tie between location and content outdated
• How is it protected?
• Can disgruntled employee of ISP sell your secrets?
• Can ’ t trust anyone (how paranoid are you?)
• Can we make it indestructible?
• Want our data to survive “the big one”!
• Highly resistant to hackers (denial of service)
• Wide-scale disaster recovery
• Is it hard to manage?
• Worst failures are human-related
• Want automatic (introspective) diagnosis and repair

Second Observation:

Need wide-scale deployment

• Many components with geographic separation
  • System not disabled by natural disasters
  • Can adapt to changes in demand and regional outages
• Wide-scale use and sharing also requires wide-scale

deployment

• Bandwidth increasing rapidly, but latency bounded by speed of

light

• Handling many people with same system leads to

economies of scale

OceanStore:

Everyone’s data, One big Utility

“The data is just out there”

• Separate information from location
  • Locality is only an optimization (an important one!)
  • Wide-scale coding and replication for durability
• All information is globally identified
  • Unique identifiers are hashes over names & keys
  • Single uniform lookup interface
  • No centralized namespace required

Utility-based Infrastructure

• Service provided by confederation of companies
  • Monthly fee paid to one service provider
  • Companies buy and sell capacity from each other

Pac

Bell

Sprint

IBM

AT&T

Canadian

OceanStore

IBM

Outline

• Motivation
• Properties of the OceanStore
• Specific Technologies and approaches:
  • Naming and Data Location
  • Conflict resolution on encrypted data
  • Replication and Deep archival storage
  • Introspective computing for optimization and repair
  • Economic models
• Conclusion

OceanStore Technologies I:

Naming and Data Location

• Requirements:
  • System-level names should help to authenticate data
  • Route to nearby data without global communication
  • Don’t inhibit rapid relocation of data
• OceanStore approach:

Two-level search with embedded routing

• Underlying namespace is flat and built from secure cryptographic

hashes (160-bit SHA-1)

• Search process combines quick, probabilistic search with slower

guaranteed search

Universal Location Facility

• Takes 160-bit unique identifier (GUID) and Returns the nearest object that matches

Universal Name

Name OID

Root Structure

Update OID:

Archive versions:

Version OID

1

Version OID

2

Version OID

3

Global Object

Resolution

Floating

Replica

Active Data

Commit

Logs

Checkpoint

Global Object OID

Resolution

Version OID

Archival copy

or snapshot

Archival copy

or snapshot

Archival copy

or snapshot

Global Object

Resolution

Global Object

Resolution

Erasure

Coded:

Probabilistic Routing Algorithm

n

3

n

4

n

2

n

1

X

(0,1,3)

z

(0,2,4)

11011

01234 bit

11010

01234 bit

11010 11001

11011

10101

00011

11100

11100

11011

11011

00011

1st

2nd

11100

11100 1st

11011 2nd

00011

11011

Y

(0,1,4)

1st

1st

Query for X (11010)

M

(1,3,4)

11000

00100

11010

1st

2nd

3rd

reliable factors

10

10

reliable factors

100

100

100

self-optimizing

on the depth of the

attenuated bloom filter

array

self-protecting

Bloom filter on each node;

Attenuated Bloom filter on each directed edge.

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Hierarchical Routing Algorithm

• Based on Plaxton scheme
• Every server in the system is assigned a random

node-ID

• Object’s root
  • each object is mapped to a single node whose node-ID

matches the object’s GUID in the most bits (starting from the

least significant)

• Information about the GUID (such as location)

were stored at its root

4

2

3

3

3

2

2

1

2

4

1

2

3

3

1

3

4

1

1

4 3

2

4

Basic Plaxton Mesh

Incremental suffix-based routing

NodeID

0x43FE

NodeID

0x13FE NodeID

0xABFE

NodeID

0x

NodeID

0x239E

NodeID

0x73FE

NodeID

0x423E

NodeID

0x79FE

NodeID

0x23FE

NodeID

0x73FF

NodeID

0x555E

NodeID

0x035E

NodeID

0x44FE

NodeID

0x

NodeID

0xF

NodeID

0x993E

NodeID

0x04FE

NodeID

0x43FE

GUID

0x43FE

a

c

b

d

e

Use of Plaxton Mesh

Randomization and Locality