Transcript Distributed Operating System

Transparency in Distributed
Operating Systems
Vijay Akkineni
Operating Systems Generations
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Centralized Operating systems
Network Operating Systems
Distributed Operating Systems
Cooperative Autonomous Systems
Cloud Computing
Partitioning of COS
Applications
Finance
Word processing
Web Application
Subsytems
Programming Envrionment
Database Systems
Utilities
Compiler
Command
Interpreter
library
System Services
File System
Memory Manager
Scehduler
Kernel
CPU Multiplexing, Interrupt Handling, Device Drivers,
Synchronization primitives, Interprocess communication
Network Operating System
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Peer to Peer communications.
Seven layer OSI architecture.
Examples Remote Login, File Transfer,
Messaging, Network Browsing, Remote
Execution.
Distributed Operating System
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Loosely coupled systems.
Sharing or resources and coordination of
resources.
Transparency – Key difference between
NOS and DOS.
Distributed resources and activities are
to be managed and controlled.
Distributed Operating Systems
Cooperative Autonomous
Systems
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Characterized by Service Integration.
Middleware – Cobra, JMS, RMI.
Transparency
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Hide
irrelevant
system
dependent
details from the users
Higher Implementation Complexities
Single System Image
Minimal Knowledge
Location Transparency
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User has no awareness of object
locations,objects
are
mapped
and
referred to by logical names.
WebServices UDDI, Federated Services SOA
Access Transparency
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Ability to access local and remote
system objects in uniform way.
The physical separation of system
objects is concealed from the user.
Examples – Accessing a file from the
local file system and from a cloud drive.
Migration Transparency
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Logical
Resources
and
Physical
processes migrated by the system, from
one location to another in an attempt to
maximize
efficiency,
reliability,
availability or security should be
automatically controlled by the system
Example – Application Servers using
JNDI
Replication Transparency
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Exhibit consistency of multiple instances
of files and data.
System elements are copied to remote
points in the system in an effort to
possibly increase efficiencies through
better proximity or provide increased
reliability through duplication.
Examples – Google's Big Table, HDFS.
Concurrency Transparency
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Sharing of Objects without interference.
Similar to Time sharing.
An important challenge when designing
distributed systems is how to deal with
concurrent accesses.
Example – An important design goal for
distributed database. Transactional Integrity
and ACID properties during multiple
transactions happening concurrently.
Failure Transparency
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Failure Transparency tries to mask
failures so that they are not seen or
noticed by the users.
It is difficult to identify between a
resource that has failed and a resource
which is performing badly (slowly).
Consider opening a webpage - is it dead
or painfully slow, how long should the
browser wait?
Examples - Map Reduce Frameworks,
DFS Replication on Data Nodes.
Performance Transparency
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Attempt to achieve a consistent and
predictable performance level even with
changes to system structure or load
distribution.
When parts of the system experience
significant delay or load imbalance, the
system is responsible for the automatic,
rapid, and accurate detection and
orchestration of a remedy.
Examples - Load balancing, Speculative
execution in Map Reduce.
Size/Scale Transparency
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A system's geographic reach, number of
nodes, level of node capability, or any
changes therein should exists without
any
required
user
knowledge
or
interaction.
Research Area - Currently there is lot of
ongoing research on running Map
Reduce job across the data centers.
Partition compute jobs based on
geographical locality.
Revision transparency
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System occasionally have need for
system-software version changes and
changes to internal implementation of
system infrastructure.
Examples - Linux Kernel Upgrades and
how it should not effect the existing
software applications on the OS.
Revision transparency
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System occasionally have need for
system-software version changes and
changes to internal implementation of
system infrastructure.
Examples - Linux Kernel Upgrades and
how it should not effect the existing
software applications on the OS.
Parallelism Transparency
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The most difficult aspect of transparency,”Holy Grail”
of distributed system designers.
Systems parallel execution of processes throughout
the system should occur without any required user
knowledge.
Examples – Parallel Algorithms on multicore
processors and Map Reduce tasks on multiple
systems.
Transparency Summarized
Access
Hide differences in data representation and how a
resource is accessed
Location
Hide where a resource is located
Migration
Hide that a resource may move to another location
Relocation
Hide that a resource may be moved to another location
while in use
Replication
Hide that a resource may be shared by several competitive
users
Concurrency
Hide that a resource may be shared by several competitive
users
Failure
Hide the failure and recovery of a resource
Persistence
Hide whether a (software) resource is in memory or on
disk
Major Research Areas
Areas
Transparencies
Communication Networks
Synchronization
Distributed Algorithms
Interaction and Control Transparency
Process Scheduling
Deadlock Handling
Load balancing
Performance Transparency
Resource Scheduling
File Sharing
Concurrency Control
Resource Transparency
Failure Handling
Configuration
Redundancy
Failure Transparency
Towards Cloud OS
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Permit autonomous management of its resources on
behalf of its users and applications.
Cloud OS operations must continue despite loss of
nodes, entire clusters, and network partitioning.
The Cloud OS must be operating system and
architecture agnostic.
The Cloud must support multiple types of
applications, including legacy.
Cloud
OS
management
system
must
be
decentralized, scalable, have little overhead per user
and per machine and be cost effective
Logical Model of Cloud OS
Cloud Middleware
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Heterogeneous Nature of Cloud hindering adoption of
Cloud Technologies.
IBM is researching into
Altocumulus middleware,
which offers a uniform API for using Amazon EC2,
Eucalyptus, Google AppEngine, and IBM HiPODS
Cloud, aiming to provide an API which is Cloud
agnostic.
http://www.almaden.ibm.com/asr/projects/cloud/
References
“HP performance-optimized datacenter
(POD).” Data Sheet, 2008.
 “Amazon EC2.” [Online]
http://aws.amazon.com/ec2.
 Apache hadoop Map Reduce
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