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DATA AGGREGATION IN WIRELESS SENSOR
                         NETWORKS
                          A Seminar Report

                             Submitted by

                        P.PRAVEEN KUMAR

                             (09751A0581)

   in partial fulfillment of the requirements for the award of the degree
                                 Of


           BACHELOR OF TECHNOLOGY

                                 IN

         COMPUTER SCIENCE AND ENGINEERING

                                 At




  SREENIVASA INSTITUTE OF TECHNOLOGY AND
                                                                            1
MANAGEMENT STUDIES, CHITTOOR-517127
                              DEC-2012


S NO.                            TITLE                     PAGE NO.
1          Introduction                                         5
2          Goal & Problem Definition in Data Aggregation        7
                          TABLE OF CONTENTS




3          Data Aggregation: An Overview                        8

             3.1 In-Network Aggregation

             3.2 Tree-Based Approach

             3.3 Cluster-Based Approach

             3.4 Multi-path Approach


4          Query Processing                                     15

             4.1 Query Models

             4.2 Query Language in Tiny DB

             4.3 Queries and Aggregates



5          Simulation and Experimental Analysis                 20

6          Security Challenges                                  25

7          Advantages and Disadvantages                         29

8          Future Scope &Applications                           30
                                                                      2
9                 Conclusion                                                                31

10                References                                                                32




                                         ABSTRACT



Sensor networks are collection of sensor nodes which co-operatively send sensed data             to
base station. As sensor nodes are battery driven, an efficient utilization of power is essential in
order to use networks for long duration hence it is needed to reduce data traffic inside sensor
networks, reduce amount of data that need to send to base station. The main goal of data
aggregation algorithms is to gather and aggregate data in an energy efficient manner so that
network lifetime is enhanced. Wireless sensor networks (WSN) offer an increasingly Sensor
nodes need less power for processing as compared to transmitting data. It is preferable to do in
network processing inside network and reduce packet size. One such approach is data
aggregation which attractive method of data gathering in distributed system architectures and
dynamic access via wireless connectivity.


Wireless sensor networks have limited computational power and limited memory and battery
power, this leads to increased complexity for application developers and often results in
applications that are closely coupled with network protocols. In this paper, a data aggregation
framework on wireless sensor networks is presented. The framework works as a middleware for
aggregating data measured by a number of nodes within a network.


The aim of the proposed work is to compare the performance of TAG in terms of energy
efficiency in comparison with and without data aggregation in wireless sensor networks and to
assess the suitability of the protocol in an environment where resources are limited.




                                                                                                 3
1. INTRODUCTION


Sensor Networks:
The wireless sensor network is ad-hoc network. It consists small light weighted wireless nodes
called sensor nodes, deployed in physical or environmental condition. And it measured physical
parameters such as sound, pressure, temperature, and humidity. These sensor nodes deployed in
large or thousand numbers and collaborate to form an ad hoc network capable of reporting to
data collection sink (base station). Wireless sensor network have various applications like habitat
monitoring, building monitoring, health monitoring, military survivallance and target tracking.
However wireless sensor network is a resource constraint if we talk about energy, computation,
memory and limited communication capabilities. All sensor nodes in the wireless sensor network
are interact with each other or by intermediate sensor nodes.


With advance in technology, sensor networks composed of small and cost effective sensing
devices equipped with wireless radio transceiver for environment monitoring have become
feasible. The key advantage of using these small devices to monitor the environment is that it
does not require infrastructure such as electric mains for power supply and wired lines for
Internet connections to collect data, nor need human interaction while deploying. These sensor
nodes can monitor the environment by collecting information from their surroundings,and work
cooperatively to send the data to a base station, or sink, for analysis.




                                                                                                 4
Figure 1 Architecture of the Sensor network




A sensor nodes that generates data, based on its sensing mechanisms observation and transmit
sensed data packet to the base station (sink). This process basically direct transmission since the
base station may located very far away from sensor nodes needs. More energy to transmit data
over long distances so that a better technique is to have fewer nodes send data to the basestation.
These nodes called aggregator nodes and processes called data aggregation in wireless sensor
network.




                                                                                                  5
2. GOALS AND PROBLEM DEFINITION




GOAL:


The main goal of data aggregation algorithms is to gather and aggregate data in an energy
efficient manner so that network lifetime is enhanced. Wireless sensor networks (WSN) offer an
increasingly attractive method of data gathering in distributed system architectures and dynamic
access via wireless connectivity.




PROBLEM DEFINITION:


Data aggregation protocols aims at eliminating redundant data transmission and thus improve the
lifetime of energy constrained wireless sensor network. In wireless sensor network, data
transmission took place in multi-hop fashion where each node forwards its data to the neighbor
node which is nearer to sink. Since closely placed nodes may sense same data, above approach
cannot be considered as energy efficient. An improvement over the above approach would be
clustering where each node sends data to cluster-head (CH) and then cluster-head perform
aggregation on the received raw data and then send it to sink. Performing ag homogeneous
sensor network cluster-head will soon die out and again re-clustering has to be done which again
cause energy consumption.




                                                                                               6
3. DATA AGGREGATION:AN OVERVIEW


Data aggregation is a process of aggregating the sensor data using aggregation approaches. The
general data aggregation algorithm works as shown in the below figure. The algorithm uses the
sensor data from the sensor node and then aggregates the data by using some aggregation
algorithms    such   as   centralized   approach,   LEACH(low   energy   adaptive   clustering
hierarchy),TAG(Tiny Aggregation) etc. This aggregated data is transfer to the sink node by
selecting the efficient path




                                                                                             7
Fig:General architure of algorithm




3.1 In-Network Aggregation:

In-network aggregation is the global process of gathering and routing information through a
multi-hop network, processing data at intermediate nodes with the objective of reducing resource
consumption (in particular energy), thereby increasing network lifetime.


                There are two approaches for in-network aggregation:


                                  1) with size reduction
                                  2) without size reduction.




With size reduction:
                  In-network aggregation with size reduction refers to the process of combining
and compressing the data packets received by a node from its neighbors in order to reduce the
packet length to be transmitted or forwarded towards sink




Without size reduction:
In-network aggregation without size reduction refers to the process merging data packets
received from different neighbors in to a single data packet but without processing the value of
data.




                                                                                               8
3.2 Tree Based Approach:




The tree based approach is defining aggregation from constructing an aggregation tree. The form
of tree is minimum spanning tree, sink node consider as a root and source node consider as a
leaves. Information flowing of data start from leaves node up to root means sink(base
station).Disadvantage of this approach, as we know like wireless sensor network are not free
from failure .in case of data packet loss at any level of tree, the data will be lost not only for
single level but for whole related sub tree as well.This approach is suitable for designing optimal
aggregation techniques data centric protocol know as Tiny aggregation (TAG) approach.




                     Fig:Tree-based aggregation in wireless sensor networks



                                                                                                  9
The working of TAG is depending on two phases:


                                            1) distributed phase


                                            2) collection phase




Distributed Phase:

In distributedphase, in which aggregate queries are pushed down into the network.




Collection Phase:
A collectionphase, where the aggregate values are continually routed up from children to parents.
Recall that our query semantics partition time into epochs of duration ,and that we must produce
a single aggregate value (when not grouping) that combines the readings of all devices in the
network during that epoch.




                                                                                              10
3.3 Cluster-Based Approach:

In energy-constrained sensor networks of large size, it is inefficient for sensors to transmit the
data directly to the sink In such scenarios, Cluster based approach is hierarchical approach. In
cluster-based approach, whole network is divided in to several clusters. Each cluster has a
cluster-head which is selected among cluster members. Cluster-heads do the role of aggregator
which aggregate data received from cluster members locally and then transmit the result to base
station (sink). Recently, several cluster-based network organization and data-aggregation
protocols have been proposed for the wireless sensor network.




       Fig:Cluster Based sensor networks.Arrow indicates wireless communication links




                                                                                               11
The cluster heads can communicate with the sink directly via long range transmissions or multi
hopping through other cluster heads.




K. Dasgupta in proposed a maximum lifetimedata aggregation (MLDA) algorithm which finds
datagathering schedule provided location of sensors node andbase-station, data packet size, and
energy of each sensornode. A data gathering schedule specifies how data packetare collected
from sensors node and transmitted to basestation for each round. A schedule can be thought of as
acollection of aggregation trees. They proposedheuristic-greedy clustering-based MLDA based
on MLDAalgorithm. In this they partitioned the network in to clusterand referred each cluster as
super-sensor. They thencompute maximum lifetime schedule for the super-sensorsand then use
this schedule to construct aggregation treesfor the sensors. W. Choi et present a two-
phaseclustering (TPC) scheme. Phase I of this scheme createsclusters with a cluster-head and
each node within thatcluster form a direct connects with cluster-head. Phase I thecluster-head
rotation is localized and is done based on the remaining energy level of the sensor nodes which
minimizetime variance of sensors and this lead to energy savingfrom unnecessary cluster-head
rotation. In phase II, eachnode within the cluster searches for a neighbor closer thancluster-head
which is called data relay point and setup up adata relay link.


Now the sensor nodes within a clustereither use direct link or data relay link to send their data
tocluster head which is an energy efficient scheme. The datarelay point aggregates data at
forwarding time to another data relay point or cluster head. In case of high networkdensity, TPC
phase II will setup unnecessary data relaylink between neighbors as closely deployed sensor
willsense same data and this lead to a waste of energy.




                                                                                               12

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A seminar report on data aggregation in wireless sensor networks

  • 1. DATA AGGREGATION IN WIRELESS SENSOR NETWORKS A Seminar Report Submitted by P.PRAVEEN KUMAR (09751A0581) in partial fulfillment of the requirements for the award of the degree Of BACHELOR OF TECHNOLOGY IN COMPUTER SCIENCE AND ENGINEERING At SREENIVASA INSTITUTE OF TECHNOLOGY AND 1
  • 2. MANAGEMENT STUDIES, CHITTOOR-517127 DEC-2012 S NO. TITLE PAGE NO. 1 Introduction 5 2 Goal & Problem Definition in Data Aggregation 7 TABLE OF CONTENTS 3 Data Aggregation: An Overview 8 3.1 In-Network Aggregation 3.2 Tree-Based Approach 3.3 Cluster-Based Approach 3.4 Multi-path Approach 4 Query Processing 15 4.1 Query Models 4.2 Query Language in Tiny DB 4.3 Queries and Aggregates 5 Simulation and Experimental Analysis 20 6 Security Challenges 25 7 Advantages and Disadvantages 29 8 Future Scope &Applications 30 2
  • 3. 9 Conclusion 31 10 References 32 ABSTRACT Sensor networks are collection of sensor nodes which co-operatively send sensed data to base station. As sensor nodes are battery driven, an efficient utilization of power is essential in order to use networks for long duration hence it is needed to reduce data traffic inside sensor networks, reduce amount of data that need to send to base station. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. Wireless sensor networks (WSN) offer an increasingly Sensor nodes need less power for processing as compared to transmitting data. It is preferable to do in network processing inside network and reduce packet size. One such approach is data aggregation which attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. Wireless sensor networks have limited computational power and limited memory and battery power, this leads to increased complexity for application developers and often results in applications that are closely coupled with network protocols. In this paper, a data aggregation framework on wireless sensor networks is presented. The framework works as a middleware for aggregating data measured by a number of nodes within a network. The aim of the proposed work is to compare the performance of TAG in terms of energy efficiency in comparison with and without data aggregation in wireless sensor networks and to assess the suitability of the protocol in an environment where resources are limited. 3
  • 4. 1. INTRODUCTION Sensor Networks: The wireless sensor network is ad-hoc network. It consists small light weighted wireless nodes called sensor nodes, deployed in physical or environmental condition. And it measured physical parameters such as sound, pressure, temperature, and humidity. These sensor nodes deployed in large or thousand numbers and collaborate to form an ad hoc network capable of reporting to data collection sink (base station). Wireless sensor network have various applications like habitat monitoring, building monitoring, health monitoring, military survivallance and target tracking. However wireless sensor network is a resource constraint if we talk about energy, computation, memory and limited communication capabilities. All sensor nodes in the wireless sensor network are interact with each other or by intermediate sensor nodes. With advance in technology, sensor networks composed of small and cost effective sensing devices equipped with wireless radio transceiver for environment monitoring have become feasible. The key advantage of using these small devices to monitor the environment is that it does not require infrastructure such as electric mains for power supply and wired lines for Internet connections to collect data, nor need human interaction while deploying. These sensor nodes can monitor the environment by collecting information from their surroundings,and work cooperatively to send the data to a base station, or sink, for analysis. 4
  • 5. Figure 1 Architecture of the Sensor network A sensor nodes that generates data, based on its sensing mechanisms observation and transmit sensed data packet to the base station (sink). This process basically direct transmission since the base station may located very far away from sensor nodes needs. More energy to transmit data over long distances so that a better technique is to have fewer nodes send data to the basestation. These nodes called aggregator nodes and processes called data aggregation in wireless sensor network. 5
  • 6. 2. GOALS AND PROBLEM DEFINITION GOAL: The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. Wireless sensor networks (WSN) offer an increasingly attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. PROBLEM DEFINITION: Data aggregation protocols aims at eliminating redundant data transmission and thus improve the lifetime of energy constrained wireless sensor network. In wireless sensor network, data transmission took place in multi-hop fashion where each node forwards its data to the neighbor node which is nearer to sink. Since closely placed nodes may sense same data, above approach cannot be considered as energy efficient. An improvement over the above approach would be clustering where each node sends data to cluster-head (CH) and then cluster-head perform aggregation on the received raw data and then send it to sink. Performing ag homogeneous sensor network cluster-head will soon die out and again re-clustering has to be done which again cause energy consumption. 6
  • 7. 3. DATA AGGREGATION:AN OVERVIEW Data aggregation is a process of aggregating the sensor data using aggregation approaches. The general data aggregation algorithm works as shown in the below figure. The algorithm uses the sensor data from the sensor node and then aggregates the data by using some aggregation algorithms such as centralized approach, LEACH(low energy adaptive clustering hierarchy),TAG(Tiny Aggregation) etc. This aggregated data is transfer to the sink node by selecting the efficient path 7
  • 8. Fig:General architure of algorithm 3.1 In-Network Aggregation: In-network aggregation is the global process of gathering and routing information through a multi-hop network, processing data at intermediate nodes with the objective of reducing resource consumption (in particular energy), thereby increasing network lifetime. There are two approaches for in-network aggregation: 1) with size reduction 2) without size reduction. With size reduction: In-network aggregation with size reduction refers to the process of combining and compressing the data packets received by a node from its neighbors in order to reduce the packet length to be transmitted or forwarded towards sink Without size reduction: In-network aggregation without size reduction refers to the process merging data packets received from different neighbors in to a single data packet but without processing the value of data. 8
  • 9. 3.2 Tree Based Approach: The tree based approach is defining aggregation from constructing an aggregation tree. The form of tree is minimum spanning tree, sink node consider as a root and source node consider as a leaves. Information flowing of data start from leaves node up to root means sink(base station).Disadvantage of this approach, as we know like wireless sensor network are not free from failure .in case of data packet loss at any level of tree, the data will be lost not only for single level but for whole related sub tree as well.This approach is suitable for designing optimal aggregation techniques data centric protocol know as Tiny aggregation (TAG) approach. Fig:Tree-based aggregation in wireless sensor networks 9
  • 10. The working of TAG is depending on two phases: 1) distributed phase 2) collection phase Distributed Phase: In distributedphase, in which aggregate queries are pushed down into the network. Collection Phase: A collectionphase, where the aggregate values are continually routed up from children to parents. Recall that our query semantics partition time into epochs of duration ,and that we must produce a single aggregate value (when not grouping) that combines the readings of all devices in the network during that epoch. 10
  • 11. 3.3 Cluster-Based Approach: In energy-constrained sensor networks of large size, it is inefficient for sensors to transmit the data directly to the sink In such scenarios, Cluster based approach is hierarchical approach. In cluster-based approach, whole network is divided in to several clusters. Each cluster has a cluster-head which is selected among cluster members. Cluster-heads do the role of aggregator which aggregate data received from cluster members locally and then transmit the result to base station (sink). Recently, several cluster-based network organization and data-aggregation protocols have been proposed for the wireless sensor network. Fig:Cluster Based sensor networks.Arrow indicates wireless communication links 11
  • 12. The cluster heads can communicate with the sink directly via long range transmissions or multi hopping through other cluster heads. K. Dasgupta in proposed a maximum lifetimedata aggregation (MLDA) algorithm which finds datagathering schedule provided location of sensors node andbase-station, data packet size, and energy of each sensornode. A data gathering schedule specifies how data packetare collected from sensors node and transmitted to basestation for each round. A schedule can be thought of as acollection of aggregation trees. They proposedheuristic-greedy clustering-based MLDA based on MLDAalgorithm. In this they partitioned the network in to clusterand referred each cluster as super-sensor. They thencompute maximum lifetime schedule for the super-sensorsand then use this schedule to construct aggregation treesfor the sensors. W. Choi et present a two- phaseclustering (TPC) scheme. Phase I of this scheme createsclusters with a cluster-head and each node within thatcluster form a direct connects with cluster-head. Phase I thecluster-head rotation is localized and is done based on the remaining energy level of the sensor nodes which minimizetime variance of sensors and this lead to energy savingfrom unnecessary cluster-head rotation. In phase II, eachnode within the cluster searches for a neighbor closer thancluster-head which is called data relay point and setup up adata relay link. Now the sensor nodes within a clustereither use direct link or data relay link to send their data tocluster head which is an energy efficient scheme. The datarelay point aggregates data at forwarding time to another data relay point or cluster head. In case of high networkdensity, TPC phase II will setup unnecessary data relaylink between neighbors as closely deployed sensor willsense same data and this lead to a waste of energy. 12