CS 599 Intelligent Embedded Systems1 Adaptive Protocols for Information Dissemination in Wireless Sensor Networks W.R.Heinzelman, J.kulik, H.Balakrishnan

CS 599 Intelligent Embedded Systems2 Outline  Introduction  SPIN  Other Data Dissemination Algorithms  Sensor Network Simulations  Conclusions  Strengths and Weaknesses

CS 599 Intelligent Embedded Systems3 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 Systems4 Introduction contd.  Limitations of Wireless sensor networks  Energy  Computation  Communication

CS 599 Intelligent Embedded Systems5 Sensor Protocols for Information via Negotiation (SPIN)  Classic flooding limitations  Implosion  Overlap  Resource blindness

CS 599 Intelligent Embedded Systems6 Implosion Problem

CS 599 Intelligent Embedded Systems7 Overlap problem

CS 599 Intelligent Embedded Systems8 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 Systems9 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 Systems10 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 Systems11 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 Systems12 Node B sends a REQ listing all of the data it would like to acquire.

CS 599 Intelligent Embedded Systems13 If node B had its own data, it could aggregate this with the data of node A and advertise.

CS 599 Intelligent Embedded Systems14 Nodes need not respond to every message

CS 599 Intelligent Embedded Systems15 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 Systems16 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

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CS 599 Intelligent Embedded Systems18 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

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CS 599 Intelligent Embedded Systems20 Sensor Network Simulations  Simulated using ns simulator  Extended ns to create a Resource- Adaptive Node

CS 599 Intelligent Embedded Systems21 Simulation Testbed

CS 599 Intelligent Embedded Systems22 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 Systems23 Data Acquired Over Time

CS 599 Intelligent Embedded Systems24 Energy Dissipated Over Time

CS 599 Intelligent Embedded Systems25 Energy Dissipated Over Time

CS 599 Intelligent Embedded Systems26 Unlimited Energy Simulations

CS 599 Intelligent Embedded Systems27 Limited Energy Simulations

CS 599 Intelligent Embedded Systems28 Limited Energy Simulations contd..

CS 599 Intelligent Embedded Systems29 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 Systems30 Transmission time per data packet = 8s/d Since SPIN-1 has to process ADV, REQ, DATA so processing time = 3(d+r) Convergence Time – no overlap

CS 599 Intelligent Embedded Systems31 Convergence Time – overlapping data

CS 599 Intelligent Embedded Systems32  For the testbed network parameters  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 Systems33 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 Systems34 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 Systems35 Questions ?