Lecture 9

transcript

Lecture 9

Other models:Monitoring modelsReliability and fault-tolerance modelsPerformance models. Scheduling policies.Security models

Student presentations and midterm

I expect a progress report the week after the Spring break (March 18 – 24).

The final project report is due the week before last.

Midterm: two weeks from today – Material – Chapters 1,2, and 3 up to the last

lecture.Open book.3 questions: 30 minutes

Monitoring models

A monitor could be a process responsible to establish the global state of a System.Intrusion – Heissenber’s uncertainty for quantum processes.Run: a total ordering of all events in the global history of a process.Cut: a subset of the local history of all processes.Frontier of a cut: the last event of every process in the cut.

Consistent and inconsistent cuts

Consistent cut: a cut that agrees with causality.

Inconsistent cut: violates causality.

Causal history of an event: the smallest cut including the event.

The snapshot algorithm of Chandy and Lamport.

Checkpointing in parallel and distributed computing.

Consistent and inconsistent cuts

C1 C 2

Causal history

The snapshot protocol (Chandy&Lamport) p0 p1

Reliability and fault-tolerance models

A failure at time t is un undesirable event characterized by its:Manifestation – incorrect timing or value of

variablesConsistency – the system may fail in a

consistent or in an inconsistent state.Effects – benign/ malignOccurrence mode: singular or repeated

Failure modes for processes [P] and for communication channels [C]

Crash - [P&C]

FailStop - [P]

Send Omissions - [P]

Receive omissions - [P]

General omissions – [P&C]

Byzantine – [P&C]

Arbitrary with message authentication - [P]

Timing – [P]

Collective communication

Broadcast and multicast.

Applications:Routing in mobile ad hoc networks.Routing in the Internet to disseminate topological

information – flooding algorithms.Used to achieve consensus.Multicasting of audio and video streams to

reduce the bandwidth.Parallel algorithms – barrier synchronization.

Collective communication

ApplicationProcess

CollectiveCommunication

Process

ApplicationProcesspj

Process

RoutingProcess

Process

Channel Channel

Properties of a broadcast algorithm (I)

Validity – if a correct cc-process broadcasts a message m all correct cc-processes eventually deliver m.

Agreement - if a correct cc-process delivers message m all correct cc-processes eventually deliver m.

Integrity – every correct cc-process delivers m once and only once and only if the message was broadcast by a cc-process

Properties of a broadcast algorithm (II)FIFO order – if a correct cc-process broadcasts a message m before m’ then no correct cc-processes delivers m’ unless it has previously delivered m.

Causal order - if a correct cc-process broadcasts m that causally precedes m’ then no correct cc-processes delivers m’ unless it has previously delivered m.

Total order – if two correct cc-processes p and q both deliver messages m and m’ then p delivers m before m’ if and only if q delivers m before m’.

Broadcast primitives and their relationships

Total Order

ReliableBroadcast

FIFOBroadcast

CausalBroadcast

FIFO Order

Causal Order

AtomicBroadcast

FIFO AtomicBroadcast

Causal AtomicBroadcast

FIFO Order

Causal Order

Performance modelsResource sharing!!!

Arrival process – distribution of inter-arrival times or arrival rates.

Service process – distribution of service times or inter-departure times.

Number of servers

Quantities of interest: Time in system, T Waiting time W Number in system, N

Little’s law: N = T

0 1 2 k k+1k-1.............. ..............

Performance models

Types of systemsDeterministic D/D/1Markov arrival, Markov service - M/M/1 Markov arrival, general service – M/G/1Batch arrival.

Server utilization : ratio of arrival rate to service rate.Stability: <= 1 necessary but not sufficient Time in system is finiteNumber in system is finite

Performance models

When utilization tends to 1 time in system becomes unbounded.

Network congestion.

C/2C/2

throughput perconnection

input data rateper connection

d e fa

Internet

(b) (c)

H1, H2 - hosts;a, f - edge routers;b,c,d,e - internal routers;chin1- communication channel from b to d;chin2- communication channel from c to d;chout - communication channel from d to e, with capacity C;two conections: - one from b to e, through d; - one from c to e, through d;

Scheduling policies/algorithmsStatic/Dynamic algorithms

Centralized/Distributed

Policies:FCFSLCFSPriorityRound-RobinWeighted Fair Queuing

Service policies for the server with vacation model

Exhaustive

Semi-gated

K-limitted

Scheduling on a grid

Resources under the control of different administrative authorities.

Resource reservations.

Market-based scheduling algorithms.

Scheduling on a grid

Internet

ResourceAgent

Resource

ResourceAgent

Resource

ResourceAgent

Resource

ResourceAgent

Resource

ResourceAgent

Resource

Process Process Process ProcessProcessProcessProcess

Scheduler

Security models

Problems and solutions:Confidentiality encriptionAuthentication authentication servicesAuthorization (controlled access to system

resources) access control

Secret key and public key cryptographyPlaintext

Ciphertext

Encrypt withsecret key

Decrypt withsecret key

Encrypt withpublic key of the

recipient

Decrypt with theprivate key of the

recipient

Plaintext

Ciphertext

Plaintext

Major challenges in distributed systems

Concurrency

Mobility

28Observational

ModelsDenotational

Models

InterleavedModels

TrueConcurrency

Models

LinearModels

BranchingTime

Models

VirtualMobilityModels

PhysicalMobilityModels

Observability

Type ofConcurrency

Description

Distributed SystemsModels

Concurrency Mobility

Lecture 9

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