DISTRIBUTED COMPUTING

MODULE 5

# Consensus and agreement algorithms

A consensus algorithm is a process that achieves agreement on a single data value among distributed processes or
systems. Consensus algorithms necessarily assume that some processes and systems will be unavailable and that
some communications will be lost. Hence these algorithms must be fault-tolerant. Examples of consensus
algorithm: (1) Deciding whether to commit a distributed transaction to a database. (2) Designating node as a
leader for some distributed task. (3) Synchronizing state machine replicas and ensuring consistency among them.

Assumptions in Consensus algorithms:

• Failure models:
Some of the processes may be faulty in distributed systems. A faulty process can behave in any manner allowed by
the failure model assumed. Some of the well known failure models includes fail-stop, send omission and receive−
omission, and Byzantine failures. Fail stop model: a process may crash in the middle of a step, which could be the
execution of a local operation or processing of a message for a send or receive event. it may send a message to
only a subset of the destination set before crashing. Byzantine failure model: a process may behave arbitrarily. The
choice of the failure model determines the feasibility and complexity of solving consensus.
• Synchronous/asynchronous communication:
If a failure-prone process chooses to send a message to process but fails, then− intended process cannot detect
the non-arrival of the message. This is because scenario is indistinguishable from the scenario in which the
message takes a very long time in transit. This is a major hurdle in asynchronous system. In a synchronous system,
a unsent message scenario can be identified by the intended− recipient, at the end of the round. The intended
recipient can deal with the non-arrival of the expected message by assuming the arrival of a message containing
some default data, and then proceeding with the next round of the algorithm.
• Network connectivity:
The system has full logical connectivity, i.e., each process can communicate with any− other by direct message
passing.
• Sender identification:
A process that receives a message always knows the identity of the sender process. When multiple messages are
expected from the same sender in a single round, a scheduling algorithm is employed that sends these messages in
sub-rounds, so that each message sent within the round can be uniquely identified.
• Channel reliability:
The channels are reliable, and only the processes may fail.
• Authenticated vs non-authenticated messages:
With unauthenticated messages, when a faulty process relays a message to other processes (i) it can forge the
message and claim that it was received from another process, (ii) it can also tamper with the contents of a received
message before relaying it. When a process receives a message, it has no way to verify its authenticity. This is
known as un authenticated message or oral message or an unsigned message. Using authentication via techniques
such as digital signatures, it is easier to solve the agreement problem because, if some process forges a message or
tampers with the contents of a received message before relaying it, the recipient can detect the forgery or
tampering. Thus, faulty processes can inflict less damage.
• Agreement variable:
The agreement variable may be boolean or multivalued, and need not be an integer. This simplifying assumption
does not affect the results for other data types, but helps in− the abstraction while presenting the algorithms.

The Byzantine agreement and other problems:

• The Byzantine agreement problem
The Byzantine agreement problem requires a designated process, called the source process, with an initial value, to
reach agreement with the other processes about its initial value, subject to the following conditions:
Agreement All non-faulty processes must agree on the same value.

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 Validity If the source process is non-faulty, then the agreed upon value by all the non-faulty processes
must be the same as the initial value of the source.
Termination Each non-faulty process must eventually decide on a value.
If the source process is faulty, then the correct processes can agree upon any value. It is irrelevant what the faulty
processes agree upon – or whether they terminate and agree upon anything at all.
• The consensus problem
The consensus problem differs from the Byzantine agreement problem in that each process has an initial value and
all the correct processes must agree on a single value. Formally:
Agreement All non-faulty processes must agree on the same (single) value.
Validity If all the non-faulty processes have the same initial value, then the agreed upon value by all the
non-faulty processes must be that same value.
Termination Each non-faulty process must eventually decide on a value.
• The interactive consistency problem
The interactive consistency problem differs from the Byzantine agreement problem in that each process has an
initial value, and all the correct processes must agree upon a set of values, with one value for each process The
formal specifications are:
Agreement: All non-faulty processes must agree on the same array of values A[v1, …,vn].
Validity: If process i is non-faulty and its initial value is vi, then all non faulty processes agree on vi as the
ith element of the array A. If process j is faulty, then the non-faulty processes can agree on any value for
A[j].
Termination: Each non-faulty process must eventually decide on the array A. The difference between the
agreement problem and the consensus problem is that, in the agreement problem, a single process has
the initial value, whereas in the consensus problem, all processes have an initial value.

# Agreement in (message-passing) synchronous systems with failures

Consensus algorithm for crash failures (synchronous system):

• The consensus algorithm for n processes where up to f processes where f < n may fail in a fail stop failure
model.
• Here the consensus variable x is integer value; each process has initial value xi. If up to f failures are to be
tolerated than algorithm has f+1 rounds, in each round a process i sense the value of its variable xi to all
other processes if that value has not been sent before.
• So, of all the values received within that round and its own value xi at that start of the round the process
takes minimum and updates xi occur f + 1 rounds the local value xi guaranteed to be the consensus value.
• If one process is faulty, among three processes then f = 1. So the agreement requires f + 1 that is equal to
two rounds.
• If it is faulty let us say it will send 0 to 1 process and 1 to another process i, j and k. Now, on receiving one
on receiving 0 it will broadcast 0 over here and this particular process on receiving 1 it will broadcast 1
over here.
• So, this will complete one round in this one round and this particular process on receiving 1 it will send 1
over here and this on the receiving 0 it will send 0 over here.

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 • The agreement condition is satisfied because in the f+ 1 rounds, there must be at least one round in which
no process failed.
• In this round, say round r, all the processes that have not failed so far succeed in broadcasting their
values, and all these processes take the minimum of the values broadcast and received in that round.
• Thus, the local values at the end of the round are the same, say xri for all non-failed processes.
• In further rounds, only this value may be sent by each process at most once, and no process i will update
its value xri.
• The validity condition is satisfied because processes do not send fictitious values in this failure model.
• For all i, if the initial value is identical, then the only value sent by any process is the value that has been
agreed upon as per the agreement condition.
• The termination condition is seen to be satisfied.

Complexity: The complexity of this particular algorithm is it requires f + 1 rounds where f < n and the number of
messages is O(n2 )in each round and each message has one integers hence the total number of messages is O((f
+1)· n 2 ) is the total number of rounds and in each round n 2 messages are required.

Lower bound on the number of rounds: At least f + 1 rounds are required, where f < n. In the worst-case scenario,
one process may fail in each round; with f + 1 rounds, there is at least one round in which no process fails. In that
guaranteed failure-free round, all messages broadcast can be delivered reliably, and all processes that have not
failed can compute the common function of the received values to reach an agreement value.

# Distributed File System

• A file system is a subsystem of the operating system that performs file management activities such as
organization, storing, retrieval, naming, sharing, and protection of files.
• A distributed file system(DFS) is a method of storing and accessing files based in a client/server
architecture.
• Files contain both data and attributes.
• The data consist of a sequence of data items, accessible by operations to read and write any portion of
the sequence.
• The attributes are held as a single record containing information such as the length of the file,
timestamps, file type, owner’s identity and access control lists. The shaded attributes in the Fig. are
managed by the file system and are not normally update by user programs.

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 • A distributed file system contains the following set of modules:

Distributed file system requirements:

1. Transparency: The file service is usually the most heavily loaded service in an intranet, so its functionality
and performance are critical. The following forms of transparency are partially or wholly addressed by
current file services:
• Access transparency: Client programs should be unaware of the distribution of files. A single set of
operations is provided for access to local and remote files. Programs written to operate on local files are
able to access remote files without modification.
• Location transparency: Client programs should see a uniform file name space. Files or groups of files may
be relocated without changing their pathnames, and user programs see the same name space wherever
they are executed.
• Mobility transparency: Neither client programs nor system administration tables in client nodes need to
be changed when files are moved. This allows file mobility – files or, more commonly, sets or volumes of
files may be moved, either by system administrators or automatically.
• Performance transparency: Client programs should continue to perform satisfactorily while the load on
the service varies within a specified range.
• Scaling transparency: The service can be expanded by incremental growth to deal with a wide range of
loads and network sizes.
2. Concurrent file updates Changes to a file by one client should not interfere with the operation of other
clients simultaneously accessing or changing the same file.
3. File replication In a file service that supports replication, a file may be represented by several copies of its
contents at different locations. This has two benefits – it enables multiple servers to share the load of
providing a service to clients accessing the same set of files, enhancing the scalability of the service, and it
enhances fault tolerance. Few file services support replication fully, but most support the caching of files
or portions of files locally, a limited form of replication.
4. Hardware and operating system heterogeneity The service interfaces should be defined so that client
and server software can be implemented for different operating systems and computers. This
requirement is an important aspect of openness.
5. Fault tolerance The central role of the file service in distributed systems makes it essential that the
service continue to operate in the face of client and server failures. To cope with transient communication
failures, the design can be based on at-most-once invocation semantics or it can use the simpler at-least-
once semantics. Tolerance of disconnection or server failures requires file replication.
6. Consistency Conventional file systems such as that provided in UNIX offer one-copy update semantics. If
any changes made to one file, that changes must do in other replicated copies.
7. Security In distributed file systems, there is a need to authenticate client requests so that access control
at the server is based on correct user identities and to protect the contents of request and reply messages
with digital signatures and (optionally) encryption of secret data.
8. Efficiency A distributed file service should offer facilities that are of at least the same power and
generality as those found in conventional file systems and should achieve a comparable level of
performance.

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# File Service Architecture
An architecture that offers a clear separation of the main concerns in providing access to files is obtained by
structuring the file service as three components – a flat file service, a directory service and a client module.

Client module A client module runs in each client computer, integrating and extending the operations of the flat
file service and the directory service under a single application programming interface that is available to user-level
programs in client computers.
Directory service The directory service provides a mapping between text names for files and their UFIDs. Clients
may obtain the UFID of a file by quoting its text name to the directory service.
Flat file service The flat file service is concerned with implementing operations on the contents of files. Unique file
identifiers (UFIDs) are used to refer to files in all requests for flat file service operations. UFIDs are long sequences
of bits chosen so that each file has a UFID that is unique among all of the files in a distributed system. When the
flat file service receives a request to create a file, it generates a new UFID for it and returns the UFID to the
requester.

Access control: An access check is made whenever a file name is converted to a UFID. A user identity is submitted
with every client request, and access checks are performed by the server for every file operation.
File groups • A file group is a collection of files located on a given server. A server may hold several file groups, and
groups can be moved between servers, but a file cannot change the group to which it belongs. In a distributed file
service, file groups support the allocation of files to file servers.
File group identifiers must be unique throughout a distributed system. Since file groups can be moved and
distributed systems that are initially separate can be merged to form a single system, the only way to ensure that
file group identifiers will always be distinct in a given system is to generate them with an algorithm that ensures
global uniqueness. For example, whenever a new file group is created, a unique identifier can be generated by
concatenating the 32-bit IP address of the host creating the new group with a 16-bit integer derived from the date,
producing a unique 48-bit integer.
file group identifier: 32 bits 16 bits
IP Address date

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# SUN NETWORK FILE SYSTEM (NFS)

Sun Network File System- Sun NFS

Network File System (NFS) is a distributed file system protocol originally developed by Sun Microsystems (Sun)
NFS allow a user on a client computer to access files from remote server.
NFS client and server modules communicate using remote procedure calls (RPC).

Virtual file system (VFS)

• Virtual file system (VFS) module, is added to the UNIX kernel to distinguish between local and remote
files.The file identifiers used in NFS are called file handles.

• The file system identifier field is a unique number that is allocated to each file system when it is created.
• The i-node number is needed to locate the file in file sysytem and also used to store its attribute and i-
node numbers are reused after a file is removed.
• The i-node generation number is needed to increment each time i-node numbers are reused after a file is
removed
• The virtual file system layer has one VFS structure for each mounted file system and one v-node per open
file. The v-node contains an indicator to show whether a file is local or remote.

Client Integration
• The NFS client module cooperates with the virtual file system in each client machine.
• If the file is local, access the unix file system for the local file.
• If the file is remote, NFS client send request to NFS server
• It operates in a similar manner to the conventional UNIX file system, transferring blocks of files to and
from the server and caching the blocks in the local memory whenever possible.

Access control and authentication

The NFS server is stateless and does not keep files open on behalf of its clients. So the server must check the user’s
identity against the file’s access permission attributes on each request, to see whether the user is permitted to
access the file in the manner requested.

NFS server interface

The file and directory operations are integrated in a single service; the creation and insertion of file names in
directories is performed by a single create operation, which takes the text name of the new file and the file handle
for the target directory as arguments. The other NFS operations on directories are,

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Mount services:
• Mount the remote directories to the local directories.
• Mount is to make a group of files in a file system structure accessible to a user or user group.
• Mount operation: mount(remotehost, remotedirectory, localdirectory)

• Client with two remotely mounted file stores. The nodes people and users in file systems at Server 1 and
Server 2 are mounted over nodes students and staff in Client’s local file store. The meaning of this is that
programs running at Client can access files at Server 1 and Server 2 by using pathnames such as
/usr/students/jon and /usr/staff/ann.
• Mount can be of 3 types:
1. Soft mount: a time bound is there. (send failure message)
2. Hard mount: no time bound. (retry the request until it is satisfied)
3. Auto mount: mount operation done on demand.
Server caching
The use of the server’s cache to hold recently read disk blocks does not raise any consistency problems but when a
server performs write operations, extra measures are needed to ensure that clients can be confident that the
results of the write operations are persistent, even when server crashes occur. The write operation offers two
options for this :
• Data in write operations received from clients is stored in the memory cache at the server and written to
disk before a reply is sent to the client. This is called write- through caching.
• Data in write operations is stored only in the memory cache. It will be written to disk when a commit
operation is received for the relevant file.
Client caching • The NFS client module caches the results of read, write, getattr, lookup and readdir operations in
order to reduce the number of requests transmitted to servers. A timestamp-based method is used to validate
cached blocks before they are used. Each data or metadata item in the cache is tagged with two timestamps:
• Tc is the time when the cache entry was last validated.
• Tm is the time when the block was last modified at the server.

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# ANDREW FILE SYSTEM

Andrew File System (AFS)

AFS is a distributed file system which uses a set of trusted servers to access file.
AFS uses a local cache to reduce the workload and increase the performance of a distributed computing
environment.
Implementation and Distribution of processes in AFS
• AFS is implemented as two software components that exist at UNIX processes called Vice and Venus.
• Vice is the name given to the server software that runs as a user-level UNIX process in each server
computer
• Venus is a user-level process that runs in each client computer and corresponds to the client module in
our abstract model.
• The set of files in one server is referred to as a volume.
• The files available to user processes running on workstations are either local or shared.
• Local files are handled as normal UNIX files.
• Shared files are stored on servers, and copies of them are cached on the local disks of workstations.
• Step 1: A first request for data to a server from a workstation is satisfied by the server and placed in a
local cache.

• Step 2: A second request for the same data is satisfied from the local cache.

• Stateful servers in AFS allow the server to inform all clients with open files about any updates made to
that file by another client, through what is known as callback.
• Callbacks to all clients with a copy of that file is ensured as a callback promise that is issued by the server
to a client when it requests for a copy of a file.
Cache consistency
• When Vice supplies a copy of a file to a Venus process it also provides a callback promise – a token issued
by the Vice server that is the custodian of the file, guaranteeing that it will notify the Venus process when
any other client modifies the file.
• Callback promises are stored with the cached files on the workstation disks and have two states: valid or
cancelled.

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 • Whenever Venus handles an open on behalf of a client, it checks the cache. If the required file is found in
the cache, then its token is checked. If its value is cancelled, then a fresh copy of the file must be fetched
from the Vice server, but if the token is valid, then the cached copy can be opened and used without
reference to vice.
• When a server performs a request to update a file it notifies all of the Venus processes to which it has
issued callback promises by sending a callback to each – a callback is a remote procedure call from a
server to a Venus process.
• When the Venus process receives a callback, it sets the callback promise token for the relevant file to
cancelled.
• When a workstation is restarted after a failure or a shutdown, Venus generates a cache validation request
containing the file modification timestamp to the server.
• If the timestamp is current, the server responds with valid and the token is reinstated. If the timestamp
shows that the file is out of date, then the server responds with cancelled and the token is set to
cancelled.

AFS has two unusual design characteristics:

• Whole-file serving: The entire contents of directories and files are transmitted to client computers by AFS
servers (in AFS-3, files larger than 64 kbytes are transferred in 64-kbyte chunks).
• Whole-file caching: Once a copy of a file or a chunk has been transferred to a client computer it is stored in a
cache on the local disk. The cache contains several hundred of the files most recently used on that computer. The
cache is permanent, surviving reboots of the client computer. Local copies of files are used to satisfy clients’ open
requests in preference to remote copies whenever possible.

Operation of AFS
1. When a user process in a client computer issues an open system call for a file in the shared file space and
there is not a current copy of the file in the local cache, the server holding the file is located and is sent a
request for a copy of the file.
2. The copy is stored in the local UNIX file system in the client computer. The copy is then opened and the
resulting UNIX file descriptor is returned to the client.
3. Subsequent read, write and other operations on the file by processes in the client computer are applied
to the local copy.
4. When the process in the client issues a close system call, if the local copy has been updated its contents
are sent back to the server. The server updates the file contents and the timestamps on the file. The copy
on the client’s local disk is retained in case it is needed again by a user-level process on the same
workstation.

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