Presentation on theme: "POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS"— Presentation transcript:
1POWER EFFICIENCY ROUTING ALGORITHMS OF WIRELESS SENSOR NETWORKS Presented by - S.ATCHUTHANSupervised by – Prof Klaus Moissner
2Major 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
3CONTENTS Introduction Energy efficiency Existing protocols Clustering LEACHDEECHEEDProposed AlgorithmImprovementConclusion
4INTRODUCTION What is a wireless sensor network ? - Data Acquisition network-Data Distribution networkApplications of wireless sensor network- Environmental monitoring- Battle field surveillance- Transportation traffic monitoring
7ENERGY 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 ?
8ENERGY 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 ?
11CLUSTERING What is Clustering ? Promising technique for lifetime extension
12CLUSTERING...... Choosing LEACH, DEEC and HEED for investigation LEACH – Basic clustering mechanismDEEC - Energy consideration for thresholdHEED - Competitive method
13LEACH 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
15LEACH...... 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.
16DEEC 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
17DEEC....... 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)
18DEEC........ Merits Life time is prolonged than LEACH Demerits Global knowledge of the network is necessary
19HEED Hybrid Energy Efficient Distributed Algorithm Multi hop routing protocolClustering – Competitive mechanism
20HEED....... Clustering parameters - Node residual energy - Node degree Probability to be a cluster headCHprob = Cprob *(Eresidual /Emax )
21HEED...... Status of nodes - Tentative cluster head - Final cluster head- UncoveredMeritsLarge scalabilityLifetime is prolonged than DEECDemeritsClustering consumes much energy
22PROPOSED ALGORITHM Clustering Energy: HEED >> DEEC DEEC Clustering for multi hop networks
23PROPOSED 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;
24PROPOSED ALGORITHM....... Long distance cause Energy loss Shortest path routingObtaining maximum single hop distance (100 m)
28CONCLUSION 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