Presentation on theme: "POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS"— Presentation transcript:
1 POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS Presented by - S.ATCHUTHANSupervised by – Prof Klaus Moissner
2 Major AchievementsInvestigated energy conservation algorithms for WSN and identify clustering is promising technique for energy savingSelected typical clustering algorithms for detailed investigation and comparison based on simulationWeaknesses of these algorithms were identified and a NEW algorithm was proposed, the improvement of which was proved through simulation and comparison to the selected algorithms
3 CONTENTS Introduction Energy efficiency Existing protocols Clustering LEACHDEECHEEDProposed AlgorithmImprovementConclusion
4 INTRODUCTION What is a wireless sensor network ? - Data Acquisition network-Data Distribution networkApplications of wireless sensor network- Environmental monitoring- Battle field surveillance- Transportation traffic monitoring
7 ENERGY EFFICIENCYWhat are the common problems in a wireless networking ?What is network lifetime ?Common problems- medium access control, routing, bandwidth allocation, power efficiency, security, life timenetwork lifetime – Time taken until the first node or last node in the network diesProlong the network lifetime – Minimize the power consumption from nodesHow to prolong the network lifetime ?
8 ENERGY EFFICIENCY........ How energy is consumed in a sensor node ? Energy consumption – Transmitting or receiving data, processing query requests, forwarding data or queries to neighbour nodes, idle listening to the media, retransmission when packet collision and generating control packetsEnergy conservation – Major challengeHow to conserve energy in a wireless sensor network ?
11 CLUSTERING What is Clustering ? Promising technique for lifetime extension
12 CLUSTERING...... Choosing LEACH, DEEC and HEED for investigation LEACH – Basic clustering mechanismDEEC - Energy consideration for thresholdHEED - Competitive method
13 LEACH Low Energy Adaptive Clustering Hierarchy Can apply for Single hop networks.Cluster head thresholdT(n) = p/(1-p*(r mod(1/p))) if n ε GT(n) = OtherwiseG is the set consisting of nodes that have not been cluster heads during last (1/p) roundsn takes a value between 0 and 1If n is less than threshold T(n), then that particular node would get the chance to become a cluster head at that particular roundNode which becomes cluster head during round 0, would again get the chance to be a cluster head during next (1/p) rounds
15 LEACH...... Merits Global knowledge of the network is not necessary. Only two hops are needed to reach sink.DemeritsFailure of the cluster head is a problem.Difficult to optimize the cluster head selection.
16 DEEC Distributed Energy – Efficient Clustering Algorithm Can apply for Single hop networksCluster head thresholdT(Si) = Pi /(1-Pi (r mod (1/Pi))) if Si ε GT( Si ) = OtherwisePi = Popt (1+a) Ei (r) / (1+a*m) Ē (r) if normal nodePi = Popt Ei (r) / (1+a*m) Ē (r) if advanced nodeProbability threshold based on the ration between residual energy of each node and the average energy of the network
17 DEEC....... Residual Energy Calculation ETx (l, d) = l*Eelec +l*єfs *d^ if d < d ETx (l, d) = l*Eelec +l*єmp*d^ if d >= d0Average Energy CalculationĒ (r) = (1/N) * Etotal (1- r/R)
18 DEEC........ Merits Life time is prolonged than LEACH Demerits Global knowledge of the network is necessary
19 HEED Hybrid Energy Efficient Distributed Algorithm Multi hop routing protocolClustering – Competitive mechanism
20 HEED....... Clustering parameters - Node residual energy - Node degree Probability to be a cluster headCHprob = Cprob *(Eresidual /Emax )
21 HEED...... Status of nodes - Tentative cluster head - Final cluster head- UncoveredMeritsLarge scalabilityLifetime is prolonged than DEECDemeritsClustering consumes much energy
22 PROPOSED ALGORITHM Clustering Energy: HEED >> DEEC DEEC Clustering for multi hop networks
23 PROPOSED ALGORITHMPseudo code (DEEC Clustering for multi hop networks)For i = 1:1: nFor j = 1:1: nIf ( d( i, j) =< Tr )join ( node j joins with cluster head i );EndK = rand ();If (DEEC clustering threshold probability < k)S ( i ). Cluster = TRUE;
24 PROPOSED ALGORITHM....... Long distance cause Energy loss Shortest path routingObtaining maximum single hop distance (100 m)
28 CONCLUSION Improvement - DEEC Clustering for multi hop networks - Shortest path routing(Based on Single hop maximum distance)Better combined of DEEC Clustering and Multi hopTwelve percent improvement of lifetime