Docstoc

Adaptive Protocols for Information Dissemination in Wireless Sensor

Document Sample
Adaptive Protocols for Information Dissemination in Wireless Sensor  Powered By Docstoc
					    Adaptive Protocols for Information
Dissemination in Wireless Sensor Networks



   W.R.Heinzelman, J.kulik, H.Balakrishnan




         CS 599 Intelligent Embedded Systems   1
Outline
   Introduction
   SPIN
   Other Data Dissemination Algorithms
   Sensor Network Simulations
   Conclusions
   Strengths and Weaknesses


                 CS 599 Intelligent Embedded Systems   2
Introduction
   Wide deployment of Wireless sensor networks
   Wireless sensor networks
       Can aggregate sensor data to provide multi-
        dimensional view
       Improve sensing accuracy
       Focus on critical events (e.g. intruder entering)
       Fault tolerant network
       Can improve remote access to sensor data – sink
        nodes

                      CS 599 Intelligent Embedded Systems   3
Introduction contd.
   Limitations of Wireless sensor networks
       Energy
       Computation
       Communication




                  CS 599 Intelligent Embedded Systems   4
Sensor Protocols for Information via Negotiation (SPIN)


   Classic flooding limitations
     Implosion
     Overlap
     Resource blindness




                    CS 599 Intelligent Embedded Systems   5
Implosion Problem




           CS 599 Intelligent Embedded Systems   6
Overlap problem




           CS 599 Intelligent Embedded Systems   7
SPIN contd..
   SPIN overcomes these deficiencies
       Negotiation
       Resource-adaptation
   Each sensor node has resource manager
       Keeps track of resource consumption
       Applications probe the manager before any activity
       Cut down activity to save energy
   Motivated by principle of ALF
       Common data naming (meta-data)


                      CS 599 Intelligent Embedded Systems    8
SPIN Meta-Data
   Sensors use meta-data to describe the
    sensor data briefly
       If x is the meta-data descriptor for data X
        sizeof (x) < sizeof (X)
       If x==y
        sensor-data-of (x) = sensor-data-of (y)
       If X==Y
        meta-data-of (X) = meta-data-of (Y)
       Meta-data format is application specific

                      CS 599 Intelligent Embedded Systems   9
SPIN Messages

   ADV – new data advertisement
   REQ – request for data
   DATA – data message

ADV and REQ messages contain only meta-
  data so they are smaller in size.

                CS 599 Intelligent Embedded Systems   10
SPIN-1 and SPIN-2
   SPIN-1
       Simple 3-stage handshake protocol
       Data aggregation is possible
       Can adapt to work in lossy or mobile network
       Can run in a completely unconfigured
        network



                    CS 599 Intelligent Embedded Systems   11
Node B sends a REQ listing all of the data it would
like to acquire.
                    CS 599 Intelligent Embedded Systems   12
If node B had its own data, it could aggregate this
with the data of node A and advertise.
                     CS 599 Intelligent Embedded Systems   13
Nodes need not respond to every message
                  CS 599 Intelligent Embedded Systems   14
SPIN-2
     SPIN-1 with a Low-Energy Threshold
     When energy below energy threshold – stop
      participating in the protocol
     Can just receive data avoiding ADV-REQ phase




                   CS 599 Intelligent Embedded Systems   15
Other data dissemination algos.
   Classic Flooding
       Converges in O(d), d-diameter of the network
   Gossiping
       Forward data to a random neighbor
       Avoids implosion
       Disseminates at a slow rate
       Fastest rate = 1 node/round


                    CS 599 Intelligent Embedded Systems   16
CS 599 Intelligent Embedded Systems   17
Ideal dissemination
   Every node sends sensor data along shortest path
   Receives each piece of distinct data only once
   Implementation
       Network level multicast (source specific)
       To handle losses, reliable multicast has to be
        deployed
       SPIN is a form of application-level multicast




                       CS 599 Intelligent Embedded Systems   18
CS 599 Intelligent Embedded Systems   19
Sensor Network Simulations
   Simulated using ns
    simulator
   Extended ns to
    create a Resource-
    Adaptive Node




                   CS 599 Intelligent Embedded Systems   20
Simulation Testbed




           CS 599 Intelligent Embedded Systems   21
SPIN-1 Results
     Higher throughput than gossiping
     Same throughput as flooding
     Uses substantially less energy than other protocols
     SPIN-2 delivers more data per unit energy than
      SPIN-1
     SPIN-2 performs closer to Ideal dissemination
     Nodes with higher degree tend to dissipate more
      energy than nodes with lower degree



                    CS 599 Intelligent Embedded Systems     22
Data Acquired Over Time




           CS 599 Intelligent Embedded Systems   23
Energy Dissipated Over Time




           CS 599 Intelligent Embedded Systems   24
Energy Dissipated Over Time




           CS 599 Intelligent Embedded Systems   25
Unlimited Energy Simulations




           CS 599 Intelligent Embedded Systems   26
Limited Energy Simulations




           CS 599 Intelligent Embedded Systems   27
Limited Energy Simulations contd..




             CS 599 Intelligent Embedded Systems   28
Best-Case Convergence Times
   For overlapping sensor data
       Convergence times for ideal and flooding are the
        same
   For non-overlapping sensor data
       Flooding converges faster than SPIN-1


   To understand these results, we develop
    equations that predict convergence times of
    each of these protocols.

                      CS 599 Intelligent Embedded Systems   29
     Convergence Time – no overlap
Transmission time per data
packet = 8s/d

Since SPIN-1 has to process
ADV, REQ, DATA so
processing time = 3(d+r)
                 8s                                   8s
        ld ( d     )  CIdeal, CFlood  ld (d  r      )
                 b                                    b
                  8s                                  8s
        ld (3d       )  CSPIN  1  ld (3(d  r )     )
                  b                                    b
                           CS 599 Intelligent Embedded Systems   30
Convergence Time – overlapping data
           8s                                          8s
  llp ( d    )  C Ideal, C Flood  llp ( d  r  k    )
           b                                            b
            8s                                         8s
  llp (3d      )C   SPIN  1  llp (3( d  r )  k     )
            b                                          b
            8s                         8s
  llp (3d      )  llp ( d  r  k       )
            b                           b
                  4s r
  d  ( k  1)      
                   b     2



                       CS 599 Intelligent Embedded Systems    31
   For the testbed network parameters
             0.063  C Ideal, C Flood  0.154
             0.133  C SPIN  1  0.294

   Simulation results
       Flooding converges in 135ms
       Ideal converges in 125ms
       SPIN-1 converges in 215ms


   Convergence times of flooding and ideal are
    closer to their upper bound unlike SPIN-1
                       CS 599 Intelligent Embedded Systems   32
Conclusions
   SPIN solves the implosion and overlap problems.
   SPIN-1 and SPIN-2 are simple protocols for
    wireless sensor networks.
   SPIN outperforms gossiping.
   SPIN-1 consumes only 25% energy w.r.t flooding
   SPIN-2 distributes 60% more data per unit energy
    w.r.t flooding.


                   CS 599 Intelligent Embedded Systems   33
Strengths and Weaknesses
   Implosion problem still exists in the REQ
    stage
   The paper doesn’t consider the collisions in
    the REQ stage
   No justification for the network parameters
    chosen

i

                  CS 599 Intelligent Embedded Systems   34
Questions ?




 CS 599 Intelligent Embedded Systems   35

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:1
posted:3/10/2012
language:English
pages:35