Transcript The Application Layer

Distributed systems
Overview
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Layers
•Communication is logically
on the application layer
•Only that has to be considered
•except for speed,
reliability, security and cost
•Error correction (and security)
might (will) be on application
layer, but is usually also on
lower layers
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Client-Server and Peer-to-Peer
Server always on; Client and Peers not
P2P: Skype, BitTorrent; IM: partly, messages yes, setup+addr. not
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Problems
•No throughput guaranties:
•problems with bandwidth-sensitive application, like many
multimedia applications
•some may use adaptive coding techniques (reducing
quality) to match available throughput
•No timing (delay or jitter) guaranties
•problems for real-time streaming multimedia
•like telephony, multi-layer games, teleconferencing
•no solution for this except special networks
•non-real time streaming multimedia (like a movie replay)
can buffer at the receiver
•No security
•this can be cured by SSL(secure socket layer)
•also by network layer security methods
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Distributed systems
A collection of independent computers
that appears to its users (people or programs)
as a single coherent system.
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Goals: sharing, transparent
• making resources accessible
– economics: printers, storage systems, supercomputers
– information exchange: mail, audio, video
– collaboration: groupware, videoconferencing, virtual
organizations
• distribution transparency
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Goals: openness
• Openness
– offer services according standard rules
• describing syntax and semantics of services
• computer networks: protocols
• distributed systems: interfaces described in an IDL
(Interface Definition Language)
– to achieve interoperability and portability
– extensible: add new components or replace existing
• collection of relatively small component
• separate policies and mechanism
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Goals: scalable
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size: easily add more users and resources
geographically: increasing distances
administration: easy to manage if it increases limitations
•
decentralized algorithm:
– no machine has complete information about the system state
– each machines makes decisions based only on local information
– failure of one machine does not ruin the algorithm
– no implicit assumption a global clock exists
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Distributing Computing Systems
Cluster Computing Systems: high performance computing
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Grid Computing Systems
high degree of heterogeneity: resource from different
organizations are brought together in a virtual organization.
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Distributed Information Systems
Transaction Processing System
•Atomic: To the outside world, the transaction happens indivisibly.
•Consistent: The transaction does not violate system invariants.
•Isolated: Concurrent transactions do not interfere with each other.
•Durable: Once a transaction commits, the changes are permanent.
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Nested Transaction
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TP monitor
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Distributed Pervasive Systems
• consisting of mobile and embedded computing devices
– small, battery-powered, mobile, wireless connections
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Sensor Networks
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Important topics
1. architecture: software and system
2. processes: treads, virtual machines, client-server
organization, code migration
3. communication: layered protocols, Remote Procedure
Calls, Message Passing Interface
4. naming: names, identifiers, addresses
5. synchronization: (logical) clocks, mutual exclusion,
election algorithms
6. consistency and replication
7. fault tolerance
8. security
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Architecture (1)
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layered
object-based
data-centered
event-based
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Architecture (2)
Processes communicate
through a common (passive
or active) repository.
Events may carry data
Publish/subscribe systems
Loosely coupled processes
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Application layering
• user-interface
• processing
• data
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Using an Internet search engine
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Alternative client-server organization
Thin - fat clients
easier – difficult to manage
application and database on different servers
Vertical distribution: placing logically different components on
different machines
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Peer-to-peer systems
Horizontal distribution:
client or server physically
split up in equivalent parts,
operating on its own share
of the data set
Distributed Hash Tables
data items with key k
mapped on node with
id: smallest id >= k
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Collaborative Distributed Systems
for a node to join often a client-server scheme is used
an example is BitTorrent
a Tracker keeps an account of active nodes (currently downloading some
file) having (chunks of) the requested file
the client node becomes than active, providing also (chunks of) files
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Processes and treads
• a way to do more things at the same time
• illusion that each one has it own virtual CPU
• used in clients (e.g. browser to start downloading parts of a
website at the same time) and servers
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Virtual Machines
• not only virtualization of CPU but also of other resources
• many different OS’s working concurrently on 1 machine
• old technique from the 1960’s
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Process virtual machine
same OS, different runtime-systems (with applications)
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Virtual machine manager
Virtual
multiple different OS’s concurrently on same hardware
Applications
Applications
Guest OS
(Windows NT)
Guest OS
(Windows 2000)
Virtual Machine
Virtual Machine
Applications
Guest OS
(Windows 2003)
Virtual Machine
Physical
Virtual Machine Manager
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Host Operating System
System Hardware
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Virtual private servers
• bridge the gap between shared web hosting services and
dedicated hosting services
• also for workstations
• examples VMware, VirtualPC
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Communication
• send and receive over TCP streams using socket interface
for networks
• message passing, higher level of abstraction
– representation of integers, floats, structures, etc
– usable for shared memory communication and highspeed interconnect busses on parallel machines
• RPC, Remote Procedure Call
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Naming
• Names are used to refer to entities (anything that can be
operated on)
• The naming system may be itself be implemented in a
distributed fashion.
• We need to resolve a name to the entity it refers to.
• How to organize a human friendly name system?
E.g. files systems, World Wide Web
• How to locate from a name the entity it refers to in a
way that is independent of their current location.
• How to resolve names by means of entity attributes?
• Internets Domain Name System as an example
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Synchronization
• Synchronization of distributed processes is more difficult
than that of processes in uni/multi-processor systems.
• using physical clocks on systems is not accurate enough,
need for logical clocks
• distributed global states
• distributed mutual exclusion
• the bully election algorithm
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