Querying in Wireless Sensor Networks

By,Anil MoolaVaishnav KidambiPratapa Sanaga Reddy

Querying Sensor Networks

Why querying? To retrieve the information To save energy in WSN

Design goals for querying methods Scalability Efficiency Reliability Fault tolerance

CSN (chord for Sensor Networks)

Based on DHT

Why not DHT

Bounded Look up time

Hierarchical Clustering approach

CSN over comes implosion and overlap

CSN (chord for Sensor Networks)

Hierarchical clustering approach

Initial set up: Ring Problem

2 NP Complete problems!!

Chain Method

Set Average Method

CSN (chord for Sensor Networks)

Chain Method

Chain Method for level 0(Base Station β , Set of all Sensorsπ0, Maximum no.of Sensors per Cluster λ0)1. cluster head ω = min(β )2. if (π0 == δ0) exit, where initially δ0 = /03. sensor αi = ω4. put αi in sets τ and δ0, where initially |τ | = 05. while(|τ| ≤λ0)6. αi.successor = min(αi)7. αi = αi.successor8. put αi in sets τ and δ09. αi.successor = ω10. ω = min(αi)11. goto 2

CSN (chord for Sensor Networks)

Set Average MethodSet-Average Method for level 0 (Base Station β , Set of allSensors π0, Maximum no.of Sensors per Cluster λ0)1. cluster head ω = min(β )2. if (π0 == δ0) exit, where initially δ0 = /03. list ν1 = min(ω,λ0), and let m =λ04. for k = 2,3, . . . ,m:5. νk = min(kth element of ν1,λ0)6. let ν be a set of lists7. ν = {ν1,ν2, . . . ,νm} 8. now, 1 ≤ occurrence of a sensor αi in ν ≤λ0)9. let set ε = / 0, and variable x =λ010. while(x ≥ 1 AND |ε| ≤λ0),11. for all sensors in ν :

CSN (chord for Sensor Networks)

12. if (occurrence of sensor αi in ν = x)13. insert sensor αi in set ε14. decrement x15. redefine min(X) to only return a sensor belongs to ε16. do step 3 to step 10 of the chain method17. goto 2

CSN (chord for Sensor Networks)

Incremental set up/ parallel set up Energy efficient mode vs Robust Mode Naming sensor Nodes and data

Incremental / parallel Naming Hashing Nodes and keys: Look up Operation

Multi-Dimensional Range Queries

List all events that have temperature between 10C and 20C with humidity between 70% and 80%

It help user efficiently drill down their search for event of interest

It enables application software to correlate events

Traditional Indexing

Data is stored at a central point and uses indices which are computed when during insertion.

Not feasible for sensor networks due to energy and bandwidth constraint.

DIM (Distributed Index for Multi dimensional data)

Foundations of DIMA locality preserving geographic hash -

Consistently maps events to the some location with in the sensor network. Events whose attributes are closer are placed beside each other.

User underlying geographic routing scheme such as GPSR to route events and queries to the corresponding node.

In short..

Each node in the network self organizes to own some attribute space for itself called zone, so events falling in that space are routed and stored in that node.

Building zones

Assumption 1 : all nodes knowthe approximate geographic boundaries of the network.

Sensor Node

WSN boundary

Building zones cont…

If i is odd then parallel to Y-Axis else parallel to X-Axis

Zone of node

Level 2

Level 3

Level 4

Code : 00

Code : 010

Code : 011

Code : 100

Code : 101

Code : 110

Code : 1110

Code : 1111

Assumption 2: Each node knows its geographic location

When a new event is generated..

Hashing an event to a zone : Use an algorithm which maps the event to a code.

Routing an event to its owner : Uses GPSR to send the event to its prospective owner.

Routing Queries

Node

Drawback of DIM

ScalabilityEach node has to aware of it boundaryEach node has to aware of its

geographic location

Bloom filters in Hierarchical Clustering approach

Hierarchical clustering for data aggregation and reporting.

ClusterHead – Summarize and forwards up data to application and guides queries down the hierarchy for appropriate data

Bloom filter are integrated with hierarchical clusters.

Bloom filters

Traditionally used it database and internet application.

Conventional hash coding VS Bloom filters

Space efficient

Construction of bloom filter

Suppose we have n elements in set S and m bits of memory

For each of n elements generate k different indices using k hash functions

…………………

0 1 2 3 M-2 M-1

Cluster Formation

Cluster formation cont…

Cluster formation cont..

Top level sensor send beacon so some cluster heads will rebind to the cluster head on the shortest path to top.

Remaining free sensors will go into hibernation

Data Discovery

Data retrieval by explicitly naming the node. Clusterhead maintains a set of bloom filters

One represents all sensors Another represents the data that maybe found.

To find the region of filters which has Temperature from 40 to 50 Moisture level from 20 to 30 etc…

Mobility!!!

What if the inquirer or the target are mobile?

Two algorithms – Two Tier Data Dissemination. Energy Efficient Data Dissemination.

Two Tier Data Dissemination(TTDD)

Source based grid structure.Grid creation.(grid points, dissemination

nodes…)Two Tier –

Source -> Dissemination NodeDissemination Node -> Dissemination Node

Grid Maintenance – Grid lifetime.

TTDD Contd…

TTDD Contd…

Aggregation and Routing.Query forwardingData forwarding

TTDD Contd…

TTDD Contd…

Mobile Sink??? – Trajectory Data Forwarding.

Primary Agent, Immediate Agent

TTDD Contd…

Energy Efficient Data Dissemination(EEDD)

2 Disadvantages of TTDDSource based grid needs to be changed

everytime the target moves.No emphasis on Energy Conservation!

EEDD Contd…

Each sensor is aware of it’s location after deployment(virtual origin).

Nodes are stationary while targets and inquirers can move.

EEDD Contd…

Working Node Selection Working mode, detecting mode. Egridhead, Nnode,Tsleep.

Grid Head Election Grid ID(a,b), Rtrans. A sensor node can calculate its grid ID (a, b) from

its location (x, y) as: a =[ x−x0/grid size ] and b = [ y−y0/grid size ],

where (x0, y0) is the location of the virtual origin. And grid size is set to less than 1/2√2 R∗ trans. Energy(S).

EEDD Contd…

EEDD Contd…

Grid MaintenanceBroadcast a request to reelect.Node with Max(energy(S))>Egridhead wins. If there is no node with energy(S)???

EEDD Contd…

Data Dissemination Target Location Aware

diagonally route to the target grid head and broadcast in the grid for the source node.

Source node sends the data packet to grid head and it’ll choose another path to the sink’s grid head, thus reducing collisions in two directions.

Data – Acknowledgement method. Resend after a delay. Forwarding enty = true, forward the packet, else broadcast

in the grid to reach the sink node. 2)Target Area Aware

route to the starting of the area and broadcast in the area to all nodes.

3)Broadcast over the entire network.

EEDD Contd…

EEDD Contd…

Inquirer Mobility issueThe inquirer will register with the new

grid head the details of the query made and the original grid ID.

Forwarding loop problem.

EEDD Contd…

Target Mobility issue Normal/SMART. MaxSmartness for each node controlled by the

inquirer. A Normal sensor node will generate data

packets if detected has been inquired. A Smart sensor node will search for the

relevant query with the effort corresponding to it’s intelligence level if it is not inquired for the event.

Questions please…

Thank you