Prepared By: Muhammad Aslam Malik KAY RO¨ MER, PHILIPP BLUM, and LENNART MEIER Supervisor: Ivan Stojmenovic Date Presented: 18th March-2010

Introduction Related Works System Model Communication Model Proposed Systems Synchronization Techniques Multiple Nodes Synchronization Techniques Measurement Techniques Classes of Calibration Project Milestone Conclusion

Outline

Sensor Networks are being used to monitor real world phenomena

Physical plays a pivotal role in sensor networks Achievement of synchronization of physical time is

complex task, due to many different challenging characteristics of sensor networks

Improvement in energy efficiency due to frequent switching of sensor nodes or components

Sensor networks also separate the sensor samples due to short time occurrence

Introduction

Through multiple sensors it is possible to detect the proximity of an object, also further higher level of information (like speed, size, and shape)

Time synchronization for sensor networks is an active field of research

Calibration is very general and complex problem The challenges for the future research is the

development of methods and tools for the evaluation of time synchronization and calibration in large scale sensor networks

Introduction (Cont)

The physical time is the essential requirement of many sensor network applications, on the other hand many traditional applications of time also depends upon sensor network

Rough classification of applications of physical time are a- Interaction between sensor network and external

observer b- Among nodes of the sensor network c- Interaction between sensor network with real world

(Related Works) Physical Time Importance

Interface among observer, sensor network and environments

Physical Time Applications

Time Synchronization and Calibration in Sensor Network

Synchronization

When a system operates with all parts in synchrony status is called as synchronization

Sensor NetworkSensor Network plays the role of an observer

interfacing to external observer and environment

Physical TimeTime of occurrence of any physical event is referred

asPhysical Time

NodesNodes are required to send, receive or to store the

data

Energy Efficiency

Nodes helping in improving the energy efficiency due to frequent switching and components

NTP was designed for large-scale networks preferably static topology

Nodes are externally synchronized to a global reference time These are injected into the network at many places through a

set of master nodes These master nodes are synchronized out of band for

instance via GPS (which provides global time with a precision at a great extent below 1µ sec)

Nodes participating in NTP, leaf nodes are called clients, inner nodes are called Stratum L servers

L is considered as level of node in the hierarchy Parents of each node must be specified in configuration files

due to which nodes frequently exchange synchronization messages with their parents and then use achieved information to adjust their clocks by regularly

incrementing them

Network Time Protocol (NTP)

Sensor nodes can be mobile, may be died due to the weakness of batteries or due to influence of environ-

ments & new sensor nodes can be added at any point at any time

This operation happen in frequent manner and any unpredictable changes in the network topology can took place, even network partitions

Mobile nodes make the transportation of messages across partition boundaries by storing received messages and further transporting it as soon as a new partition is entered

End-to-end delay of such type of message path is very unstable and hard to predict as well

Network Dynamics

All modelling are carried out in terms of discrete time and events

Any event represent the communication between nodes, a sensor measurement, the injection of time information at a node, and so on

Clock Models Digital clocks measure time intervals, they particularly

having a counter “h” which can counts time steps of an ideally fixed length

We denote the reading of the counter at real time “t” as h(t), counter is incremented by an oscillator with a

rate(freq) “f”, so Rate f at time t is given as the first derivation of h(t ):f(t)=dh(t)/dt

System Model

Any ideal clock having rate 1 at all times, but the rate of a real clock fluctuations over the time is due to changes in the supply voltages, temperature and so on

If fluctuation allowed to be arbitrary, the clocks reading obviously give no information at all

It is limited by known boundary, different types of boundary on the rate fluctuation lead to different types of clock models

Constant-Rate Model In this model rate is considered as constant It is justified if required precision is small compared to the rate fluctuation

Clock Model

A synchronization algorithms can either directly modify local clock “h” or otherwise

Construction of a software clock ”c” A software clock is a function which take a local clock

value h(t) as input and transforming it to time c (h(t)) This time is the final result of synchronization & therefore

it is called as synchronized time C(h(t))= +h(t)-h( ) Software clock which starts with correct real time t0 then

runs with the same speed as local clock ‘h’

Software Clocks

t0 t0

Communication is required to achieve and maintain synchronization, different parameters, which may affect time synchronization are

Unicast-verses Multicast In this scenario, a message is sent by one network node

and is received by at most one other network nodes, we referred it as unicast or point-to-point communication

On the other hand in Multicast Communication occurs when a message is sent by one network node and it is received by an arbitrary number of other network nodes

Broad Cast The situation in which all nodes within transmission

range are recipients are called as Broad Cast

Communication Models

Symmetrical The scenario in which a node “A” is able to receive the

messages sent by node “B” if and only if node B can receive messages sent by node “A”, then this link between node A & B is called symmetrical

Asymmetrical Asymmetrical link is between a base station with high

transmit power and a mobile device with low transmit power , beyond a certain distance between two, only communication in direction from the base station to the mobile device is possible

Symmetrical Verses Asymmetrical Links

The delay has also the great importance, during message transfer between nodes gaining the time information

Send Time The time when message command is sent is termed as

send time The (medium) access time When node starts transmitting message is called access

time The Propagation Time Time duration between sender to receiver is called as

propagation time Receive Time It is the time lasting from the reception of the signal to the arrival of the data at the application

Delay Uncertainty

Clock synchronization algorithms has to face two problems, clock drift and message delay uncertainty

Influence of clock drift may dominate over that of message delays, the scenario in which communication is infrequent

Due to decrease in frequency of communication, the uncertainty due to clock drift increases

Uncertainty due to message delay remains constant

Sources of Synchronization Errors

“Making clock show the same time” is termed as synchronization

Internal Vs External The time supplied from outside the network is termed as

external synchronization, NTP performs external synchronization and sensor nodes synchronizing clocks to master nodes

Internal Synchronization Internal synchronization is the synchronization of all

clocks in the network, without a predetermined master time, goal was consistency among network nodes

Classes of Synchronization

Life Time Life time of synchronization is period of time during

which synchronization is required to hold Continuous Synchronization is continuous, the network nodes exerts

force to maintain synchronization at all times On-Demand On-Demand synchronization can be as good as

continuous synchronization with respect to synchronization quality but with much efficient way during that time between events, no synchronization and communication is required, and thus energy

consumption can be kept at minimum level

Life Time: Continuous Vs On-Demand

Event Triggered In this scenario sensor nodes needs a synchronized

clock only immediately after the occurrence of event, to compute time stamp for the moment in recent past when event took place (e.g. post facto synchronization)

Time Triggered On-Demand Synchronization In this scenario data is collected during specific time from multiple sensor nodes For successful anticipated synchronization, it is sufficient

to maintain a synchronization quality, which can guarantees that target time is not missed

Kinds of On-Demand Synchronization

Scope: All Nodes Vs Subsets It defines which nodes in the network has to be

synchronized Depending on applications scope determines weather all

nodes or only subsets of nodes has to be synchronized Rate synchronization Vs Offset synchronization Means that nodes measure all identical time-interval

length in sensor networks, in this scenario sensor nodes measure time of appearance and disappearance of an object

Off-Set Synchronization Nodes measure identical point in time, that is at some

time “t” the software clocks of all nodes in the scope show “t”

Classes of Synchronization (cont)

Scope and life defines where and when synchronization is required Scope N1 N3

N4 Scope Time N5

Scope and Life Time

ScopeN2N1 N2 N3 N4 N5

Two ways of time synchronization In 1st method We can synchronize clocks, making all

clocks displaying the same time at any given time For achieving synchronization, we have to perform rate

and off-set synchronization 2nd Method is to transform timescales, meaning to

transform local times of one node into local times of another node, both nodes are same in sense

Time scale Transformation Vs Clock Synchronization

Rate and Off-Set Synchronization

Time Instant It determines the specific time instant like “t=5” Time-Interval It determines the time with specific time intervals, like (“t ϵ [4.5, 5.5]”) In both cases the time information can be refined by

adding a statement about its quality For example the time information may be guaranteed to

be correct with a certain probability or even probability distribution for the time can be given

For sensor networks, guaranteed time interval is better

Time Instants Vs Time Intervals

Taking One Sample The simple model showing the two nodes and which can exchange messages and synchronization between these nodes mean that they have established the relationship between their local clocks and

Synchronization Technique(Proposed Systems)

N i

N j

and

hi

hj

N jN i

hi hj

The unidirectional Scenario

Unidirectional synchronization

N i N j

hi hj

hi

a hj

a

hj

b

d

hi

b

The time synchronization contains or as estimating If priori bounds are known for message delay , which is

≤ d ≤ , then estimation will be

≈ -1/2( + )

Alternatively minimizing in the worst case scenario is

≈ +1/2( + )

- and - - are lower and upper bounds on

+ and + are bounds on

Unidirectional Synchronization

hi

a hj

b

d min d max

hi

a hj

b d min d max

hj

b hi

a d min d max

hj

b d min hj

b d max hj

a

hi

a d min hi

a d max hi

b

Bidirectional Scenario

Round Trip Synchronization

hi hj

N iN j

hj

a

hj

c

d

d

Dhi

b

hi

c

In round trip scenario If priori bounds about the message delays are known, which is ≤ d ≤ The node now knows that delay d is bounded by Max(D- , ) and min( ,D- ) The estimation ≈ -D/2, minimizing the worst case

synchronization errors -(D- ) and - are lower and upper bounds for Round trip synchronization is better due to the reason as it provide

the lower and upper bound synchronization error, it is called as probabilistic time synchronization, it continues till the synchronization error is below the specified threshold value

The only disadvantage is that number of messages are increased than unidirectional

Round Trip Synchronization

d min d max

N j

d mind max d max d min

hj

c

hj

b

d min hj

c d min

hj

c

hj

b

Round Trip Scenario

Round Trip Synchronization

N iN j

hi hj

d1

d

1

d

2

d 2

Di D

j

Fig shows the reference broadcasting

In this technique a beacon is involved as well, delay d and are almost equal, Node sends time stamp to

, and it measure D= - between arrival of two messages, then estimate to ≈ +D

main advantage is broad cast message received concurrently, so better than all others

Reference Broadcasting

N k

d

N i hi

a

N j hj

b

hi

b hi

a

hj

a

Multiple nodes synchronization is desired, which help in adding of additional layer of complexity, due to which it can be avoided easily by using an overlay network providing virtual, single-hop communication from sensor node to a single master node

Synchronization error directly depends upon the message delay, and it is very difficult to control on logical link having many physical hops

Hence performance schemes have to be dealt with the multi-hop problem absolutely

Synchronization of Multiple Nodes

There are four approaches of multihop synchronization Out-of-Band-Synchronization

Synchronization of Multiple Nodes

Clustering

Synchronization of Multiple Nodes

A

B

C

Tree hierarchy scenario is most common solution of multihop synchronization problem

Synchronization of Multiple Nodes

Unstructured Scenario This type of synchronization, do not solve the problem perfectly and

then perform pairwise synchronization Symmetrical synchronization is carried out It is having local approach can not use for global reference time

Multiple Nodes Synchronization

Measurements Techniques

Measurements

Three fundamental different measurements strategies has been shown in figure

In fig a, single-hop RBS scheme is used to measure precision The precision is achieved by the FTSP multi-hop algorithms Through these techniques, having advantage that every node can

evaluate and log its own precision In fig b, sensor nodes generate some directly observable event

Advantage of this scenario is that the precision of measurement is not limited by the resolution of node’s clocks

In fig c, it proposes to measures the precision achieved by one client node, a client node synchronizes over several hops to a master node

Master and client nodes are virtual nodes successfully implemented on a single physical node, and intermediate nodes are all separate

physical nodes

Measurements Techniques

Internal vs. External: For internal calibration all software sensor ‘i’ should give the same output value ( ( (t)), if they are present in identical stimulus q(t) ( note that if for instance q(t)= C, then ( ( (t))= ( (t ))= C would mean that sensors 1 and 2 are inter-calib

For external calibration, the output of all software sensor must be presented to a specified scale( e.g. if q(t)= C, then

( (t))= ( (t)= C is required) Life-Time Continuous Vs on-demand: Some of the parameters which

influence ‘h’ may change over time, calibration have to be repeated to be suitable to accept these parameters and calibration can be performed continuously or on-demand

Scope, All Nodes Vs Subsets: All nodes or subset might participate in calibration

For instance, only some nodes might be equipped with a specific type of sensor or some sensor might be used by some nodes

Classes Calibration

ci

hi

250

c1

h125

0

c1

h1

c2

h2

250

100

c2

h2

Project Milestone

Background Studies Related Work Sudies

Problem Identification

Proposed Systems Results Analysis

Time Synchronization has declared special case of calibration, and many observations about time synchronization can be transferred to calibration

Time synchronization has been declared as great active field of research, while calibration still has not been responded very well by the researcher

Calibration is more complex than the synchronization The future challenges in research is to develop the methods and

tools for the evaluation of time synchronization and calibration for large sensor networks

Model-Based Calibration analysis will be presented in paper in detail, at present due to shortage of time has not been discussed in deatail

Conclusions

Kay Romer, Philipp Blum and Lennart Meier on Time Synchronization and Calibration in Sensor Network

Jeremy Eric Elson, on Time Synchronization in Wireless Sensor network, 2003

J . Feng, S.Megerion, M. Potkonjak on Model-Based Calibration for Sensor Network

References

Q1- How energy efficiency can be achieved in sensor networks. Ans- Through frequent switching of sensor nodes and components

(Sleep Nodes). Q2-In which aspect the on-demand synchronization and continuous

synchronization are equally good Ans- Both are equally good with respect to synchronization quality Q-3 Why wired networks have less delay uncertainties as compared

with wireless sensor networks Ans-Due to lower link reliability and bandwidth

Question and Answer