Hu3513551364

P K Reddy. M et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1355-1364

RESEARCH ARTICLE

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OPEN ACCESS

Performance Comparison of Physical Clock Synchronization
Algorithms
D.Adithya Chandra Varma, Praveen Kumar Reddy.M, Prof.Gopinath.
School of Computing Science Engineering, VIT University, Vellore - 632014, TamilNadu, India.

Abstract
This project mainly focuses on comparing and analyzing clock synchronization algorithms in distributed system.
Clock synchronization is required for transaction processing applications, process control applications etc. This
generates transmission delays and synchronization errors for processes and the clock synchronization algorithms
try to synchronize the clocks in the system under the effect of these barriers. Two centralized clock
synchronization algorithms are used for testing Cristian’s and Berkeley clock synchronization algorithms, and
the third, the distributed clock synchronization algorithm, Network time protocol for synchronization of clocks
in the internet.
Keywords: Clock Synchronization, Coordinator, Distributed System, Global Time, Transmission Delay, Time
Server.

I.

INTRODUCTION

The three clock synchronization algorithms
used for experiment in this report are Cristian’s and
Berkeley clock synchronization algorithms and
Network Time Protocol. A distributed system consists
of set of processes and these processes communicate
by exchanging messages. In distributed system
synchronization between processes is required for
various purposes, for example in transaction
processing and process control operations. For
processes to be synchronized and have a common
view of global time, clock synchronization algorithms
are applied for ensuring that physically dispersed
processes have a common knowledge of time. The
clock synchronization algorithms are of following
types:
1) Distributed Algorithm: NTP (Network Time
Service Protocol)
2) Centralized Algorithm:
a) Cristian’s clock synchronization algorithm.
b) Berkeley clock synchronization algorithm.

II.

synchronize frequently. NTP has synchronization
models, multicast mode, procedure call mode,
symmetric mode. NTP calculates offset for each pair
of messages, delay and filter dispersion.
In this report we will analyze and compare
performances of Cristian’s and Berkeley clock
synchronization algorithms on a set of processes
having same set of variables and instructions and are
asynchronous (each process execute actions with
arbitrary speeds). The synchronization algorithms try
to minimize effect of these delays and errors. The
experiment is done on the basis of these parameters on
varying number of processes in the system. Algorithm
runs for a finite number of iterations in order to
minimize the effect of delays and errors.
Cristianʼs algorithm:

LITERATURE SURVEY

Clock Synchronization Problem:
Cristian’s algorithm and Berkeley algorithm
are for the relative clock synchronization. Cristian’s
algorithm suffers from implementations using single
server. In Cristian’s algorithm we use centralized time
server where as in Berkeley’s, we can’t establish it,
and synchronizes all clocks to average and machines
run time daemon. In Berkeley’s master send offset by
which each clock needs adjustment to each slave.
When skew is too great, we ignore readings
from those clocks. The third one to synchronize the
physical clocks, NTP, having goals of enable clients
across Internet to be accurately synchronized to UTC
despite message delays, enabling clients to
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Figure 1: Cristian algorithm client-server model
The simplest algorithm for setting the time
would be to simply issue a remote procedure call to a
time server and obtain the time. That does not account
for the network and processing delay. We can attempt
to compensate for this by measuring the time (in local
system time) at which the request is sent (T0) and the
time at which the response is received (T1). Our best
guess at the network delay in each direction is to
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assume that the delays to and from are symmetric (we
have no reason to believe otherwise). The estimated
overhead due to the network delay is then (T1- T0)/2.
The new time can be set to the time returned by the
server plus the time that elapsed since the server
generated the timestamp:

Cristian's algorithm suffers from the problem
that afflicts all single-server algorithms: the server
might fail and clock synchronization will be
unavailable. It is also subject to malicious interference.
Berkeley algorithm
The Berkeley algorithm, developed by
Gusella and Zatti in 1989, does not assume that any
machine has an accurate time source with which to
synchronize. Instead, it opts for obtaining an average
time from the participating computers and
synchronizing all machines to that average.
The
machines
involved
in
the
synchronization each run a time daemon process that
is responsible for implementing the protocol. One of
these machines is elected (or designated) to be the
master. The others are slaves. The server polls each
machine periodically, asking it for the time. The time
at each machine may be estimated by using Cristian's
method to account for network delays. When all the
results are in, the master computes the average time
(including its own time in the calculation).

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server now averages the three timestamps: the two it
received and its own, computing (3:00+3:25+2:50)/3 =
3:05. Now it sends an offset to each machine so that
the machine's time will be synchronized to the average
once the offset is applied. The machine with a time of
3:25 gets sent an offset of -0:20 and the machine with
a time of 2:50 gets an offset of +0:15. The server has
to adjust its own time by +0:05.
The algorithm also has provisions to ignore
readings from clocks whose skew is too great. The
master may compute a fault-tolerant average –
averaging values from machines whose clocks have
not drifted by more than a certain amount. If the
master machine fails, any other slave could be elected
to take over.
Network Time Protocol (NTP)
The Network Time Protocol [1991, 1992] is
an Internet standard (version 3, RFC 1305) whose
goals are to:
1. Enable clients across the Internet to be accurately
synchronized to UTC (universal coordinated time)
despite message delays. Statistical techniques are
used for filtering data and gauging the quality of
the results.
2. Provide a reliable service that can survive lengthy
losses of connectivity. This means
having redundant paths and redundant servers.
3. Enable clients to synchronize frequently and
offset the effects of clock drift.
4. Provide
protection
against
interference;
authenticate that the data is from a trusted source.

Figure 2: Berkley algorithm design
The hope is that the average cancels out the
individual clock's tendencies to run fast or slow.
Instead of sending the updated time back to the slaves,
which would introduce further uncertainty due to
network delays, it sends each machine the offset by
which its clock needs adjustment. The operation of
this algorithm is illustrated in Figure 7. Three
machines have times of 3:00, 3:25, and 2:50. The
machine with the time of 3:00 is the server (master).
It sends out a synchronization query to the
other machines in the group. Each of these machines
sends a timestamp as a response to the query. The
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Figure 3: NTP Protocol server strata
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The NTP servers are arranged into strata. The
first stratum contains the primary servers, which are
machines that are connected directly to an accurate
time source. The second stratum contains the
secondary servers. These machines are synchronized
from the primary stratum machines. The third stratum
contains tertiary servers that are synchronized from the
secondary servers, and so on. Together, all these
servers form the synchronization subnet. A machine
will often try to synchronize with several servers,
using the best of all the results to set its time. The best
result is a function of a number of qualities, including:
round-trip delay, consistency of the delay, round-trip
error, and server’s stratum, the accuracy of the server’s
clock, the last time the server’s clock was
synchronized, and the estimated drift on the server.
Because a system may synchronize with multiple
servers, its stratum is dynamic: it is based on the
server used for the latest synchronization. If you
synchronized from a secondary NTP server then you
are in the third stratum. If, next time, you used a
primary NTP server to synchronize, you are now in the
second stratum.
Machines synchronize in one of the following modes:
1. Symmetric active mode:
In this mode, a host sends periodic messages
regardless of the reachability state or stratum of its
peer
2. Symmetric passive:
This mode is created when a system receives
a message from a peer operating in symmetric active
mode and persists as long as the peer is reachable and
operating at a stratum less than or equal to the host.
This is a mode where the host announces its
willingness to synchronize and be synchronized by the
peer. This mode offers the highest accuracy and is
intended for use by master servers. A pair of servers
exchanges messages with each other containing timing
information. Timing data are retained to improve
accuracy in synchronization over time.
3. Procedure call mode:
This call mode is similar to Cristian’s
algorithm; a client announces its willingness to by
synchronize by the server, but not to synchronize the
server.
4. Multicast mode:
This mode is intended for high speed LANs;
relatively low accuracy but fine for many applications.
All messages are delivered unreliably via UDP. In
both the procedure call mode and symmetric mode,
messages are exchanged in pairs. Each message has
the following timestamps:

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Ti-2: local time when previous NTP message was
received.
Ti-1: local time when current NTP message was sent.
The server notes its local time, Ti. For each
pair, NTP calculates the offset (estimate of the actual
offset between two clocks) and delay (total transit time
for two messages). In the end, a process determines
three products:
1. Clock offset: this is the amount that the local clock
needs to be adjusted to have it correspond to a
reference clock.
2. Roundtrip delay: this provides the client with the
capability to launch a message to arrive at the
reference clock at a particular time; it gives us a
measure of the transit time of the mesge to a particular
time server.
3. Dispersion: this is the “quality of estimate” (also
known as filter dispersion) based on the accuracy of
the server’s clock and the consistency of the network
transit times. It represents the maximum error of the
local clock relative to the reference clock.
By performing several NTP exchanges with
several servers, a process can determine which server
to favor. The preferred ones are those with a lower
stratum and the lowest total filter dispersion. A higher
stratum (less accurate) time source may be chosen if
the communication to the more accurate servers is less
predictable.
The Simple Network Time Protocol, SNTP
(RFC 2030), is an adaptation of the Network Time
Protocol that allows operation in a stateless remote
procedure call mode or multicast mode. It is intended
for environments when the full NTP implementation is
not needed or is not justified. The intention is that
SNTP be used at the ends of the synchronization
subnet (high strata) rather than for synchronizing time
servers.
SNTP can operate in either a unicast,
multicast, or anycast modes:
- in unicast mode, a client sends a request to a
designated server
- in multicast mode, a server periodically sends a
broadcast or multicast message and expects no
requests from clients
- in anycast mode, a client sends a request to a local
broadcast or multicast address and takes the first
response received by responding servers.
From then on, the protocol proceeds as in unicast
mode. NTP and SNTP messages are both sent via
UDP (there is no point in having time reports delayed
by possible TCP retransmissions).

Ti-3: local time when previous NTP message was sent.

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III.

RELATED WORK
METHODOLOGY

JAVA RMI
Java RMI is actually the extension of Java
Object Model to support distributed objects. In
particular it allows objects to invoke methods on
remote objects using the same syntax for local
invocations. The object making remote invocation

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must handle Remote Exception and must implement
Remote interface. Java implements the RMI
functionality in the java.rmi package. RMI uses object
serialization to marshal and un-marshal parameters
and does not truncate types, supporting true objectoriented polymorphism.
Java RMI Architecture:

Fig.4. Java RMI Architecture Overview
The design goal for the RMI architecture was
to create a Java distributed object model that integrates
naturally into the Java programming language and the
local object model. RMI architects have succeeded in
creating a system that extends the safety and
robustness of the Java architecture to the distributed
computing world.

Interfaces:
The heart of RMI is the definition of behavior
(method) which is called as the Interface. RMI
considers interface and implementation as separate
concepts. RMI allows the code that defines the method
and the code that implements the method to remain
separate and to run on separate JVMs.

Fig 5: Java RMI Interfaces
In RMI, the definition of a remote service is
coded using a Java interface. The implementation of
the remote service is coded in a class. Therefore, the
key to understanding RMI is to remember that
interfaces define behavior and classes define
implementation.

A Java interface does not contain executable
code. RMI supports two classes that implement the
same interface. The first class is the implementation of
the behavior, and it runs on the server. The second
class acts as a proxy for the remote service and it runs
on the client.

Figure 6. Java RMI Overview
A client program makes method calls on the
proxy object, RMI sends the request to the remote
JVM, and forwards it to the implementation. Any
return values provided by the implementation are sent
back to the proxy and then to the client's program.

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Java RMI Detailed Architecture:

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Figure 7: Java RMI Detailed Architecture
RMI implementation is built from three
layers. First Stub or Skeleton layer which lies beneath
the user layer.
Stub:A stub for a remote object acts as a client's
local representative or proxy for the remote object.
The caller invokes a method on the local stub which is
responsible for carrying out the method call on the
remote object. In RMI, a stub for a remote object
implements the same set of remote interfaces that a
remote object implements.
When a stub's method is invoked, it does the
following:
 initiates a connection with the remote JVM
containing the remote object,
 marshals (writes and transmits) the parameters to
the remote JVM,
 waits for the result of the method invocation,
 un-marshal (reads) the return value or exception
returned, and
 Returns the value to the caller.
The stub hides the serialization of parameters
and the network-level communication in order to
present a simple invocation mechanism to the caller.
Skeleton:
In the remote JVM, each remote object may
have a corresponding skeleton. The skeleton is
responsible for dispatching the call to the actual
remote object implementation. When a skeleton
receives an incoming method invocation it does the
following:
-marshal (reads) the parameters for the remote
method,
implementation, and
value or exception) to the caller.
Stubs and skeletons are generated by the rmic
compiler.

IV.

PROJECT SETUP Cristian
Algorithm:

In Cristian’s algorithm each process sends a
request and a delay is generated at each process, after
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which the request will be delivered to the message
queue. The simulation engine removes the message
from queue head, calculates a random transmission
delay and sends a reply message to the destination
message by adding destination identifier to the
message and message delay. The calculated delay is
represented as delay_at_rqst_queue in the equation.
Each process makes 30 requests to the Time
Server and then averages the delay values which it
gets in each “reply message” from the time server. A
difference between the current process and the global
time (Time Server) is calculated. These differences are
displayed in the results.
The run () method for Cristian’s Algorithm:
1. The messages are delivered in the increasing order
of delay, to Time Server.
2. Time Server computes message_queue_delay (states
for which the message was in queue) sends a reply
message to requesting process.
3. Process sends 30 requests to the Time Server and
gets a value for delay at request queue.
4. Calculates the average on 30 delay values and
calculates its local time.
In Cristian’s Algorithm, all the process send
request for synchronizing its time. All processes suffer
transmission delay. Each process makes 30 requests
to Time Server. There are no faulty processes in the
system (Time Server never crashes). Processes are
asynchronous and delays are generated randomly. A
process sends request after waiting random amount of
time. In Berkeley Algorithm, all the processes get
message in each iteration, they are asynchronous. The
Coordinator never crashes. The error calculated by
Coordinator is between 1-2 milliseconds and generated
randomly.
Berkley’s Algorithm:
In Berkeley algorithm the Simulation Engine
(Coordinator) polls processes and measures the clock
difference between its time and time of other process
in the system. It selects a largest set of processes that
do not differ from its value by more than a fixed value
(in the experiment fixed value is selected as 20
milliseconds). It then averages the differences of these
processes. It also calculates a synchronization error for
each process clock. The Coordinator asks each process
to correct its clock by a quantity equal to the
difference between the average value and the
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previously measured difference between the clock of
the Coordinator and that of a process. The run ()
method for Berkeley Algorithm:
1. Coordinator calculates time difference between
itself and other processes in the system.
2. Coordinator polls processes with a bound on
difference (in experiment this value is 20
milliseconds)
3. Calculates the average
4. Calculates an error which represents error in
approximation of other clocks in the system.
5. Inform all the processes about the correction.
6. Does 10 iterations of above step.

V.

PROJECT EVALUATION AND
RESULTS

Christian Algorithm:
We can implement using RMI
3 files should be there. Chat.java, Client.java,
Server.java in a directory

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STEP 1: START--> cmd --> (OPEN 2 COMMAND
PROMPTS , ONE FOR CLIENT AND ONE FOR
SERVER)
In the command Prompt, first go to the
directory of files present
STEP 2:
javac *.java
ENTER
OR
javac Chat.java Client.java Server.java (all
three executing once)
STEP 3: start rmiregistry ENTER
STEP 4: In one command prompt, java
Server
ENTER (Now server is Up and Running)
STEP 5: In another command prompt java Client
ENTER Request for time (to server): i.e. give
any string and ENTER Server response time we can
get Give another string for milliseconds and
OVERHEAD etc
Milli seconds
We get another response from the server that
is number of milli seconds and overhead etc

Figure 8: Christian Algorithm using RMI – server and client

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Berkley Algorithm:
We can implement using RMI
3 files should be there. Chat.java, Client.java,
Server.java in a directory
STEP 1: START--> cmd --> (OPEN 2 COMMAND
PROMPTS, ONE FOR CLIENT AND
ONE FOR SERVER)
In the command Prompt, first go to the
directory of files present
STEP 2 :
:> javac *.java ENTER
OR
:> javac Chat.java Client.java Server.java (all
three executing once)

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:> start rmiregistry
ENTER
STEP 4: In one command prompt,
:>java Server
ENTER (Now server is Up
and Running)
STEP 5: In another command prompt
:>java Client
ENTER
Request for time (to server): i.e. give any
string
:>Time please and ENTER
Server response time we can get
Give another string for milliseconds and
OVERHEAD etc
:> milli seconds ENTER
Another Server response time we can get.

STEP 3:

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Figure 9: Berkley Protocol using RMI – Server and 3 Clients
NTP (Network Time Protocol):
STEP1:
OPEN 2 COMMAND PROMPTS
:> javac *.java
STEP2:
java Primary1.java
(RETURNS
ITS
TIME)
PRIMARY
SERVER'S TIME
STEP3:
In One Window,
java Primary2

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(waiting for secondary server)
In another Window
java Secondary1
ENTER YOUR MESSAGE:
TIME
PLEASE
First window (primary server) receives the
request and gives its response back to secondary
server.
(ITS COMPLETE TIME)
After getting that time, Secondary server synchronizes
to it.

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Figure 10: NTP Protocol using Client Server model
The experiment is conducted on 5, 10, 20 and
30 processes in the system. In Cristian algorithm each
process makes 30 requests to the Time Server and then
calculates an average on these delay values. In results
all the processes of the system are shown and the
difference between them and global time are also
shown. In Berkeley algorithm an average is calculated
by the coordinator on the basis of equation (2). The
graph is generated for one process by showing its
difference at each iteration.

Note: For all diagrams, the Berkeley curve shows the
difference curve for one process on which 10 iterations
of Berkeley algorithm was performed. The value of
the 4 processes on which Berkeley Algorithm were
performed is shown in Table 1. Cristian curve shows
the difference of all the processes in the system from
the global time. Also in a system of five processes one
process is Time Server, therefore only four processes
are
shown
in
the
curve.

Comparison of Christian and Berkley in real-time:

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Observations:
5 processes:
Observation: In Cristian curve shows
tendency to converge as the global time increases.
Berkeley algorithm converge a process at a very fast
rate with every iteration.
10 processes:
Observation: Cristian curve shows that as the
number of processes increase the difference of each
process from global time varies in a very small
interval. In Berkeley Algorithm the process gets closer
to global time value.

Clock synchronization is required for internal
and external synchronization of clocks for various
transaction processes and process controls. A more
efficient algorithm will lead to a better convergence.

REFERENCES
[1]

[2]

[3]
20 processes:
Observation: There is randomness in
processes of Cristian Curve due to variable
transmission delay. But this randomness is in a finite
range. Berkeley curve shows that clock of the process
converges closer to the global time after 10 iterations.
30 processes:
Observation: Cristian curve shows that as the
number of processes increase the difference of each
process from global time varies in a very small
interval. Berkeley curve shows that number of
iterations brings clock value closer to global time.

VI.

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[4]

[5]

F.
Cristian
Probabilistic
clock
synchronization. In Distributed Computing,
volume 3, pages 146-158. Springer Verlag,
1989
R. Gusella and S. Zatti, "TEMPO-A network
time controller for a distributed Berkeley
UNIX system."IEEE Distributed Processing
Tech.Comm. Newslett., vol. 6, no. S1-2, pp.
7-15, June 1984.
J.Y. Halpern et al., "Fault-Tolerant Clock
Synchronization,"Proc. Third Ann. ACM
Symp. Principles of Distributed Computing,
ACM, New York, 1984, pp. 89-102.
T. Clouser, R. Thomas, M. Nesterenko
"Emuli: Emulated Stimuli for Wireless
Sensor Network Experimentation", technical
report TR-KSU-CS-2007-04, Kent State
Univesity.
Distributed Systems ©2000-2009 by Paul
Krzyzanowski, Rutgers University

CONCLUSION

Considering the results by having from RMI
and simulation engine, we can conclude that for
internal clock synchronization, cristian’s algorithm as
well as Berkley algorithm used, in those if we are
using less number of processes (clients) then Berkley
algorithm shows much difference in global time to
synchronize where as cristian’s algorithm not shows
that much. So when less number of clients are there in
out subnet cristian’s algorithm is best where as for
more number of clients are present Berkley algorithm
much efficient. And finally NTP protocol, which is
used for internet clocks synchronization, is best in its
own conditions.
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