Leach protocol
Upcoming SlideShare
Loading in...5
×
 

 

Statistics

Views

Total Views
715
Views on SlideShare
715
Embed Views
0

Actions

Likes
0
Downloads
39
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Leach protocol Leach protocol Presentation Transcript

  • LEACH protocol for WIRELESS SENSOR NETWORK CALCUTTA INSTITUTE OF ENGINEERING AND MANAGEMENT 24/1A, CHANDI GHOSH ROAD, KOLKATA-700040 2012-2013 Presented by: RAMESH VERMA ANIL KUMAR PRAVIND KUMAR C.S.E.4th Year
  • Overview-LowEnergyAdaptiveClusteringHierarchy (LEACH)  Introduction to leach protocol  Two phases of leach  Set-up phase/ thresold algorithm  Set-up phase/advertisement  Set-up to steady state phase  Weakness in leach  DECSA(Distance Energy Cluster Structure Algorithm )  Initialization stage  Stable working stage  comparision
  • IntroductiontoLEACHprotocol  Falls under hierarchical networks  Self-organizing, adaptive clustering protocol that uses randomization to distribute energy load evenly  Dense network of sensor nodes grouped into clusters.  All nodes are assumed to be homogenous + energy constrained.  Base station is fixed + away from sensors.  Cluster member elect cluster head to avoid excessive energy consumption.  Incorporates data aggregation.
  • LEACH two phases  It has two phases  The set-up phase and the steady- state phase  The set-up phase where cluster heads are chosen  The steady state phase the cluster head is maintained where data is transmitted between nodes
  • Set-up phase/ Thresold algorithm  Cluster-heads can be chosen stochastically (randomly based) on this algorithm: T(n) =P/1-P*(r mod/p) if n€G 0 , otherwise Where n is a random no. between 0 and 1 and P is cluster head probability and G is the set of nodes that were not cluster head in the last round.  If n <T(n), then that node becomes a cluster head  The algorithm is designed so that each node becomes a cluster-head at least once
  • Algorithm - Setup Phase | Advertisement  Each node that elected itself a cluster-head for current round broadcasts advertisement message to rest of nodes  All cluster-heads transmit advertisement using same transmit energy  Non-cluster-head nodes must keep receivers on during this phase to hear advertisements  now they decide which cluster to belong to for this round by choosing cluster-head that requires minimum communication energy  In case of ties, random cluster-head chosen
  • Algorithm - Setup to Steady Phase  After node picks cluster, must inform cluster- head  Cluster-head now knows number of members  cluster-head then creates a TDMA schedule telling each node when it can transmit  allows radio components of each non-cluster- head node to be turned off during its transmit time, thus minimizing energy dissipated in individual sensors  cluster-head now has all data from the nodes in its cluster, aggregates data & transmits to base
  • Weakness in LEACH LEACH assumes that  all nodes can communicate with each other and are able to reach the sink (therefore, it is only suitable for small size networks)  all nodes have data to send and so assign a time slot for a node even though some nodes might not have data to transmit.  all nearby nodes have correlated data which is not always true  all nodes are continuously listening ( this is not realistic in a random distribution of the sensor nodes, for example, where cluster-heads would be located at the edge of the network),
  • DECSA (Distance Energy Cluster Structure Algorithm)  DECSA is improvement over LEACH.  It considers both the distance and residual energy information of nodes.  Three level hierarchy structure of DECSA consists of BS(Base Station), BCH(Base Station Cluster Head), CH( ordinary Cluster head), SN(sensor nodes)
  • Initialization Stage  The process of cluster head select consists of following 2 parts: election of ordinary cluster head node (CH) and election of Base Station Cluster head (BCH)  First round cluster head is called false-cluster-head  All nodes compare their k(i) with the false cluster head.  If k(i) < false cluster head’s k(i), then false cluster head becomes CH otherwise the node. k(i)=En(i)/do(i) k(i)=thresold of elected CH En(i)=residual energy of node i do(i)=average distance of node I from all other nodes in the network
  • Initialization Stage Selection of BCH 1.TBCH of all CH is calculated and compared with predefinedTBCH0 2. CH whoseTBCH are larger than the predefined thresholdTBCH0 becomes the base-station cluster- head( BCH). TBCH(i)=(En(i)/Eo)+(En(i)/d(i)) En(i)=current residual energy of node I Eo is the initial energy of node in the network d(i)= distance between node I and the base station
  • Stable working Stage  base station broadcasts the message to the entire network forming a communication path.  Common nodes (SN) in the cluster will transmit data packet to their closest cluster-head  luster-head will collect and fusion those data and transmit them to the base-station cluster- head, rather than transmit them to the base station directly  then, base-station-cluster-head will communicate with the base station
  • Comparison  DECSA prolongs 31% of the lifetime, reduces 40% of the energy consumption and has a better performance than the original LEACH protocol.  . Residual energy relationship of nodes between DECSA and LEACH
  • Conclusion  DECSA considering both the distance and residual energy of nodes  It improved the process of cluster head election and the process of data transmission of network  Reduces the adverse effect on the energy consumption of the cluster head  prolongs 31% of the lifetime, reduces 40% of the energy consumption.
  • Bibiliography  “Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection”; M.J.Handy, M. Haas, D.Timmermann; 2002; http://www.vs.inf.ethz.ch/publ/se/IEEE_MWCN2 002.pdf  “Probabilistic Modeling of Leach Protocol and Computing Sensor Energy Consumption Rate in Sensor Networks”; Song, Dezhen; February 22,2005; http://www.cs.tamu.edu/academics/tr/tamu-cstr- 2005-2-2