WebOS, PlanetLab, Starfish: Difference between revisions
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[http://homeostasis.scs.carleton.ca/~soma/distos/2008-03-17/anderson-planetlab-learning.pdf Thomas Anderson and Timothy Roscoe, "Learning from PlanetLab" (2006)] | [http://homeostasis.scs.carleton.ca/~soma/distos/2008-03-17/anderson-planetlab-learning.pdf Thomas Anderson and Timothy Roscoe, "Learning from PlanetLab" (2006)] | ||
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== WebOS == | |||
=== Key features === | |||
* High Availability | |||
* Lower Latency | |||
* Fault Tolerance | |||
Consensus: WebOS isn't really an distributed OS | |||
=== Main components === | |||
* Smart Client | |||
* WebFS | |||
* Global naming scheme based on URLs | |||
* Process control system | |||
* CRISIS authentication/authorization system (Certificates with ACLs) | |||
=== Key ideas that were/were not not adopted from WebFS === | |||
Adopted: | |||
* General idea of wide area dynamic distribution -> Akamai (but primarily for static content) | |||
* Global naming using URLs | |||
Not Adopted: | |||
* CRISIS | |||
* WebFS (Although WebDAV could be said to be related) | |||
* Smart client (for web sites) | |||
=== What are the pros and cons of using smart clients to do load balancing? === | |||
Pro: | |||
* Distributes computation | |||
* More flexible | |||
Con: | |||
* Vulnerable to Denial of Service or other forms of attacks | |||
* Extra network overhead to locate a service | |||
== Starfish == | |||
=== Key features === | |||
===== MPI ===== | |||
* Fast message passing | |||
* Allows the programmers more control | |||
===== OCaml ===== | |||
====== Pros ====== | |||
* Recursive algorithms | |||
* Uses Bytecodes - portable in theory | |||
* Same code on heterogenous hardware | |||
* Well known language | |||
====== Cons ====== | |||
* Slow performance? | |||
* Not entirely portable, maybe Just-In-Time? | |||
==== Checkpointing ==== | |||
* Save / resume state | |||
* Provides process migration | |||
* Maybe better suited to be implemented in the application, not OS? | |||
==== Management ==== | |||
* Had a Java interface which allowed any node to login and see full system status | |||
* Used the distributed nature of daemons to communicate this information | |||
== Experiences Building PlanetLab == | |||
=== Key ideas === | |||
* Global platform to distribute/test network services | |||
* Scale | |||
* Should be able to monitor and stop disruptive traffic | |||
=== Challenges === | |||
* Resource allocation is significant, especially in a distributed system such as PlanetLab | |||
* Providing a global platform for long-term services | |||
* Implementing a trust relationship between node owners and service developers (users) | |||
=== PLC === | |||
==== Summary ==== | |||
* Fulfills the trust mechanism required for the network | |||
* Acts as a middle man / mediator between node owners and users | |||
* If someone breaks into the PLC however, entire system is compromised | |||
==== Implementation ==== | |||
* Nodes are split into slices using VServers, lightweight process groups | |||
==== Criticisms ==== | |||
* Bandwidth allocation was slice-based, not node based | |||
== Learning from PlanetLab== | |||
=== Centralized Trusts === | |||
==== Pro ==== | |||
* Easier to manage, one entity to trust | |||
==== Con ==== | |||
* One point of control, no competition as to who to trust | |||
=== Centralized resource control === | |||
==== Pro ==== | |||
* All resources are controlled by PLC | |||
==== Con ==== | |||
* No incentive for users or administrators to conservce resources | |||
=== Decentralized management === | |||
==== Pro ==== | |||
* Provide bare-bones management, try to foster competition between 3rd party services | |||
==== Con ==== | |||
* No motivation to do so, it's hard work | |||
=== Treat bandwidth as free === | |||
==== Pro ==== | |||
* Free bandwidth! | |||
==== Con ==== | |||
* No incentive to conserve bandwidth | |||
=== Provide only best-effort service === | |||
==== Pro ==== | |||
* No limit on the number of processes which can be run | |||
==== Con ==== | |||
* Other processes may crowd out computation of other processes (cpu/disk hogging) | |||
=== Linux is the execution environment === | |||
==== Pro ==== | |||
* Provides a familiar programming environment | |||
==== Con ==== | |||
* Weak isolation between experiments | |||
* No global allocation for resources | |||
* Having a homogenous test-bed is poor for distributed experimentation | |||
=== Don't provide distributed OS services === | |||
==== Pro ==== | |||
* | |||
==== Con ==== | |||
* | |||
=== Evolve the API === | |||
==== Pro ==== | |||
* Adaptable API, ground-up | |||
==== Con ==== | |||
* Never had a good API, inconsistent, ever changing, unstable programming environment | |||
=== Focus on the machine room === | |||
==== Pro ==== | |||
* Allocate big machine here, other there, etc... | |||
==== Con ==== | |||
* Bad for distributed OSes |
Latest revision as of 19:55, 19 March 2008
Readings
Amin Vahat et al., "WebOS: Operating System Services for Wide Area Applications" (1998)
Larry Peterson et al., "Experiences Building PlanetLab" (2006)
Thomas Anderson and Timothy Roscoe, "Learning from PlanetLab" (2006)
WebOS
Key features
- High Availability
- Lower Latency
- Fault Tolerance
Consensus: WebOS isn't really an distributed OS
Main components
- Smart Client
- WebFS
- Global naming scheme based on URLs
- Process control system
- CRISIS authentication/authorization system (Certificates with ACLs)
Key ideas that were/were not not adopted from WebFS
Adopted:
- General idea of wide area dynamic distribution -> Akamai (but primarily for static content)
- Global naming using URLs
Not Adopted:
- CRISIS
- WebFS (Although WebDAV could be said to be related)
- Smart client (for web sites)
What are the pros and cons of using smart clients to do load balancing?
Pro:
- Distributes computation
- More flexible
Con:
- Vulnerable to Denial of Service or other forms of attacks
- Extra network overhead to locate a service
Starfish
Key features
MPI
- Fast message passing
- Allows the programmers more control
OCaml
Pros
- Recursive algorithms
- Uses Bytecodes - portable in theory
- Same code on heterogenous hardware
- Well known language
Cons
- Slow performance?
- Not entirely portable, maybe Just-In-Time?
Checkpointing
- Save / resume state
- Provides process migration
- Maybe better suited to be implemented in the application, not OS?
Management
- Had a Java interface which allowed any node to login and see full system status
- Used the distributed nature of daemons to communicate this information
Experiences Building PlanetLab
Key ideas
- Global platform to distribute/test network services
- Scale
- Should be able to monitor and stop disruptive traffic
Challenges
- Resource allocation is significant, especially in a distributed system such as PlanetLab
- Providing a global platform for long-term services
- Implementing a trust relationship between node owners and service developers (users)
PLC
Summary
- Fulfills the trust mechanism required for the network
- Acts as a middle man / mediator between node owners and users
- If someone breaks into the PLC however, entire system is compromised
Implementation
- Nodes are split into slices using VServers, lightweight process groups
Criticisms
- Bandwidth allocation was slice-based, not node based
Learning from PlanetLab
Centralized Trusts
Pro
- Easier to manage, one entity to trust
Con
- One point of control, no competition as to who to trust
Centralized resource control
Pro
- All resources are controlled by PLC
Con
- No incentive for users or administrators to conservce resources
Decentralized management
Pro
- Provide bare-bones management, try to foster competition between 3rd party services
Con
- No motivation to do so, it's hard work
Treat bandwidth as free
Pro
- Free bandwidth!
Con
- No incentive to conserve bandwidth
Provide only best-effort service
Pro
- No limit on the number of processes which can be run
Con
- Other processes may crowd out computation of other processes (cpu/disk hogging)
Linux is the execution environment
Pro
- Provides a familiar programming environment
Con
- Weak isolation between experiments
- No global allocation for resources
- Having a homogenous test-bed is poor for distributed experimentation
Don't provide distributed OS services
Pro
Con
Evolve the API
Pro
- Adaptable API, ground-up
Con
- Never had a good API, inconsistent, ever changing, unstable programming environment
Focus on the machine room
Pro
- Allocate big machine here, other there, etc...
Con
- Bad for distributed OSes