querying in wireless sensor networks by, anil moola vaishnav kidambi pratapa sanaga reddy
TRANSCRIPT
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