DISTRIBUTED OPERATING

SYSTEMS

Sandeep Kumar PooniaHead of Dept. CS/IT

B.E., M.Tech., UGC-NET

LM-IAENG, LM-IACSIT,LM-CSTA, LM-AIRCC, LM-SCIEI, AM-UACEE

ISSUES IN CLIENT-SERVER COMMUNICATION

Addressing

Blocking versus non-blocking

Buffered versus unbuffered

Reliable versus unreliable

Server architecture: concurrent versus

sequential

Scalability

ADDRESSING ISSUES

Question: how is the server

located?

Hard-wired address

Machine address and process

address are known a priori

Broadcast-based

Server chooses address from a

sparse address space

Client broadcasts request

Can cache response for future

Locate address via name

server

user server

user server

user serverNS

BLOCKING VERSUS NON-BLOCKING

Blocking communication (synchronous)

Send blocks until message is actually sent

Receive blocks until message is actually received

BLOCKING VERSUS NON-BLOCKING

Non-blocking communication (asynchronous)

Send returns immediately

Return does not block

BUFFERING ISSUES

Unbuffered communication

Server must call receive before client can call send

BUFFERING ISSUES

Buffered communication

Client send to a mailbox

Server receives from a mailbox

RELIABILITY

Unreliable channel

Need acknowledgements (ACKs)

Applications handle ACKs

ACKs for both request and reply

RELIABILITY

Reliable channel

Reply acts as ACK for request

Explicit ACK for response

SERVER ARCHITECTURE Sequential

Serve one request at a time

Can service multiple requests by employing events and

asynchronous communication

Concurrent

Server spawns a process or thread to service each request

Can also use a pre-spawned pool of threads/processes

(apache)

Thus servers could be

Pure-sequential, event-based, thread-based, process-based

SCALABILITY

Question:How can you scale the server

capacity?

Buy bigger machine!

Replicate

Distribute data and/or algorithms

Ship code instead of data

Cache

TO PUSH OR PULL ?

Client-pull architecture

Clients pull data from servers (by sending requests)

Example: HTTP

Pro: stateless servers, failures are each to handle

Con: limited scalability

Server-push architecture

Servers push data to client

Example: video streaming

Pro: more scalable,

Con: stateful servers, less resilient to failure

REMOTE PROCEDURE CALLS

Goal: Make distributed computing look like centralized

computing

Allow remote services to be called as procedures

Transparency with regard to location, implementation,

language

Issues

How to pass parameters

Bindings

Semantics in face of errors

Two classes: integrated into programming language

and separate

CONVENTIONAL PROCEDURE CALL

a) Parameter passing in a

local procedure call: the

stack before the call to

read

b) The stack while the called

procedure is active

PARAMETER PASSING

Local procedure parameter passing

Call-by-value

Call-by-reference: arrays, complex data structures

Remote procedure calls simulate this through:

Stubs – proxies

Flattening – marshalling

Related issue: global variables are not allowed

in RPCs

CLIENT AND SERVER STUBS

Principle of RPC between a client and server program.

STUBS

Client makes procedure call (just like a local

procedure call) to the client stub

Server is written as a standard procedure

Stubs take care of packaging arguments and

sending messages

Packaging parameters is called marshalling

Stub compiler generates stub automatically

from specs in an Interface Definition Language

(IDL)

Simplifies programmer task

A PAIR OF STUBS

Client-side stub

Looks like local server

function

Same interface as local

function

Bundles arguments into

message, sends to

server-side stub

Waits for reply, un-

bundles results

returns

Server-side stub

Looks like local client

function to server

Listens on a socket for

message from client

stub

Un-bundles arguments

to local variables

Makes a local function

call to server

Bundles result into reply

message to client stub

STEPS OF A REMOTE PROCEDURE CALL

1. Client procedure calls client stub in normal way

2. Client stub builds message, calls local OS

3. Client's OS sends message to remote OS

4. Remote OS gives message to server stub

5. Server stub unpacks parameters, calls server

6. Server does work, returns result to the stub

7. Server stub packs it in message, calls local OS

8. Server's OS sends message to client's OS

9. Client's OS gives message to client stub

10. Stub unpacks result, returns to client

EXAMPLE OF AN RPC

2-8

RPC – ISSUES

How to make the “remote” part of RPC invisible

to the programmer?

What are semantics of parameter passing?

E.g., pass by reference?

How to bind (locate & connect) to servers?

How to handle heterogeneity?

OS, language, architecture, …

How to make it go fast?

RPC MODEL

A server defines the service interface using an

interface definition language (IDL)

the IDL specifies the names, parameters, and types

for all client-callable server procedures

A stub compiler reads the IDL declarations and

produces two stub functions for each server

function

Server-side and client-side

RPC MODEL (CONTINUED)

Linking:–

Server programmer implements the server’s

functions and links with the server-side stubs

Client programmer implements the client program

and links it with client-side stubs

Operation:–

Stubs manage all of the details of remote

communication between client and server

RPC STUBS A client-side stub is a function that looks to the client

as if it were a callable server function

I.e., same API as the server’s implementation of the function

A server-side stub looks like a caller to the server

I.e., like a hunk of code invoking the server function

The client program thinks it’s invoking the server

but it’s calling into the client-side stub

The server program thinks it’s called by the client

but it’s really called by the server-side stub

The stubs send messages to each other to make the RPC happen transparently

MARSHALLING ARGUMENTS

Marshalling is the packing of function

parameters into a message packet

the RPC stubs call type-specific functions to

marshal or unmarshal the parameters of an RPC

Client stub marshals the arguments into a message

Server stub unmarshals the arguments and uses them to

invoke the service function

on return:

the server stub marshals return values

the client stub unmarshals return values, and returns to

the client program

MARSHALLING

Problem: different machines have different data formats

Intel: little endian, SPARC: big endian

Solution: use a standard representation

Example: external data representation (XDR)

Problem: how do we pass pointers?

If it points to a well-defined data structure, pass a copy and the server

stub passes a pointer to the local copy

What about data structures containing pointers?

Prohibit

Chase pointers over network

Marshalling: transform parameters/results into a byte stream

ISSUE #1 — REPRESENTATION OF DATA

Big endian vs. little endian

Sent by Pentium Rec’d by SPARC After inversion

REPRESENTATION OF DATA (CONTINUED)

IDL must also define representation of data on

network

Multi-byte integers

Strings, character codes

Floating point, complex, …

…

example: Sun’s XDR (external data representation)

Each stub converts machine representation to/from

network representation

Clients and servers must not try to cast data!

ISSUE #2 — POINTERS AND REFERENCES

read(int fd, char* buf, int nbytes)

Pointers are only valid within one address space

Cannot be interpreted by another processEven on same machine!

Pointers and references are ubiquitous in C, C++

Even in Java implementations!

POINTERS AND REFERENCES —

RESTRICTED SEMANTICS

Option: call by value

Sending stub dereferences pointer, copies result to

message

Receiving stub conjures up a new pointer

Option: call by result

Sending stub provides buffer, called function puts

data into it

Receiving stub copies data to caller’s buffer as

specified by pointer

POINTERS AND REFERENCES —

RESTRICTED SEMANTICS (CONTINUED)

Option: call by value-result

Caller’s stub copies data to message, then copies result back to client buffer

Server stub keeps data in own buffer, server updates it; server sends data back in reply

Not allowed:–

Call by reference

Aliased arguments

RPC BINDING

Binding is the process of connecting the client

to the server

the server, when it starts up, exports its interface

identifies itself to a network name server

tells RPC runtime that it is alive and ready to accept calls

the client, before issuing any calls, imports the

server

RPC runtime uses the name server to find the location of

the server and establish a connection

The import and export operations are explicit in

the server and client programs

BINDING: COMMENTS

Exporting and importing incurs overheads

Binder can be a bottleneck

Use multiple binders

Binder can do load balancing

RPC - BINDING

Static binding hard coded stub

Simple, efficient

not flexible

stub recompilation necessary if the location of the server changes

use of redundant servers not possible

Dynamic binding name and directory server

load balancing

IDL used for binding

flexible

redundant servers possible

RPC - DYNAMIC BINDING

client

procedure call

client stubbind

(un)marshal

(de)serialize

Find/bind

send

receive

com

munic

ation m

odule

com

munic

ation m

odule

server

procedure

server stubregister

(un)marshal

(de)serialize

receive

send

dispatcher

selects stub

client process server process

name and directory server

2

4

5 6

7

8

9

1

12

11 10

12

13

12

3

Wolfgang Gassler, Eva

Zangerle

FAILURE SEMANTICS

Client unable to locate server: return error

Lost request messages: simple timeout mechanisms

Lost replies: timeout mechanisms

Make operation idempotent

Use sequence numbers, mark retransmissions

FAILURE SEMANTICS

Server failures: did failure occur before or after

operation?

At least once semantics- Keep trying until a reply has been

received

At most once- Gives up immediately and report back failure

No guarantee- RPC may have been carried out any where

from 0 to a large number of times

Exactly once: desirable but difficult to achieve

FAILURE SEMANTICS

Client failure: what happens to the server

computation?

Referred to as an orphan

Extermination: log at client stub and explicitly kill orphans

Overhead of maintaining disk logs

Reincarnation: Divide time into epochs between failures

and delete computations from old epochs

Gentle reincarnation: upon a new epoch broadcast, try to

locate owner first (delete only if no owner)

Expiration: give each RPC a fixed quantum T; explicitly

request extensions

Periodic checks with client during long computations

IMPLEMENTATION ISSUES

Choice of protocol [affects communication costs]

Use existing protocol (UDP) or design from scratch

Packet size restrictions

Reliability in case of multiple packet messages

Flow control

Copying costs are dominant overheads

Need at least 2 copies per message

From client to NIC and from server NIC to server

As many as 7 copies

Stack in stub – message buffer in stub – kernel – NIC – medium –NIC – kernel – stub – server

Scatter-gather operations can reduce overheads

RPC PROTOCOL

CRITICAL PATH

CASE STUDY: SUNRPC

One of the most widely used RPC systems

Developed for use with NFS

Built on top of UDP or TCP

TCP: stream is divided into records

UDP: max packet size < 8912 bytes

UDP: timeout plus limited number of retransmissions

TCP: return error if connection is terminated by server

Multiple arguments marshaled into a single structure

At-least-once semantics if reply received, at-least-zero semantics if no reply. With UDP tries at-most-once

Use SUN’s eXternal Data Representation (XDR)

Big endian order for 32 bit integers, handle arbitrarily large data structures

BINDER: PORT MAPPER

Server start-up: create port

Server stub calls svc_register

to register prog. #, version #

with local port mapper

Port mapper stores prog #,

version #, and port

Client start-up: call

clnt_create to locate server

port

Upon return, client can call

procedures at the server

SUMMARY

RPCs make distributed computations look like

local computations

Issues:

Parameter passing

Binding

Failure handling

Case Study: SUN RPC

GROUP COMMUNICATION

One-to-many communication: useful for

distributed applications

Issues:

Group characteristics:

Static/dynamic, open/closed

Group addressing

Multicast, broadcast, application-level multicast (unicast)

Atomicity

Message ordering

Scalability

PUTTING IT ALL TOGETHER: EMAIL

User uses mail client to compose a message

Mail client connects to mail server

Mail server looks up address to destination

mail server

Mail server sets up a connection and passes

the mail to destination mail server

Destination stores mail in input buffer (user

mailbox)

Recipient checks mail at a later time

EMAIL: DESIGN CONSIDERATIONS

Structured or unstructured?

Addressing?

Blocking/non-blocking?

Buffered or unbuffered?

Reliable or unreliable?

Server architecture

Scalability

Push or pull?

Group communication