Load Balancing Routing Scheme in Mars Sensor NetworkObjectivePowerPoint PresentationProposed Algorithm :Design Issue 1 : Construct Routing TableExample for Node iSlide 7Data Transmission from Node D To Base StationSlide 9Multi Path Nodes for Senor NetworkMulti Path for Sensor network100 nodes with 2 Hour Simulation Result Level 3 Nodes Power consumption100 Nodes with 2 Hour Simulation Result Level 4 Nodes Power consumption200 nodes with 5 Hour Simulation Result Level 1 Nodes Power consumption ( test when the nodes are more dense)Conclusion and Future workReferenceLoad Balancing Routing Scheme in Load Balancing Routing Scheme in Mars Sensor NetworkMars Sensor NetworkCS 215 Winter 2001 Term ProjectCS 215 Winter 2001 Term ProjectProf : Mario GerlaProf : Mario GerlaTutor: Xiaoyan HongTutor: Xiaoyan HongStudent : Hanbiao Wang & Qingying LiStudent : Hanbiao Wang & Qingying LiObjective Balancing sensors’ energy consumption by diffusing data traffic into their closest neighbourhoods. Prolong network lifetime by alleviating the load unbalance problem.Problem of Original Design for JPL Sensor networkProblem of Original Design for JPL Sensor network•In the original implementation, it forms a spinning tree for routing path•Node 35  Handle data traffic for cluster 1•Node 74  Handle data traffic for cluster 2•Conclude :Node 35 and 74 died out fast3574Cluster 2Cluster1Proposed Algorithm :Proposed Algorithm :We propose an multi path routing scheme to diffuse data traffic of the sensor to its neighbourhood that is still in the shortest path back to the base station. Routing table construction stage, the sensor network self-organized into a configuration of N levels.a) The base station is the sink with level = 0 ( black in the figure) b) All the nodes that can directly hear from the base station are labelled as level = 1 ( blue in the figure ). All the nodes that could directly talk with level 1 nodes are labelled as level = 2 (green in the figure), but they couldn't directly talk with level 0 node, and so forth. data transmission step, node i at level (N+1) will randomly chooses next hop j from its neighbours at level N with equal probability.Design Issue 1 : Construct Routing TableDesign Issue 1 : Construct Routing Table When a node receives request packages from other nodes,it will check it against its own routing table: 1. HopNumber ( Incoming packet) > HopNumber( record ) discarded ;2 HopNumber(Incoming packet) < HopNumber ( record ) delete old path and record new path;3. HopNumber(Incoming packet) = HopNumber(record) insert this new path into its routing tableExample for Node Example for Node iiAssuming Node i received a package from Node J at first. The node J indicates that its distance to the base is 3, hence, Node i will record its distance to the base is 4 ;Then another package from K arrives and indicates its distance to the base is 2. Hence, Node i compare this with its record, it will delete the path via Node J and update its distance to the base as 3, also record the path via node K.When the package from Node L arrives and indicates its distance to the base is 2. Node i will add this entry to its routing table that gave same shortest distance of 3 to the base, via Node L.Node M has same situation as Node L.Level 111111222Level 22223122Level 4Flooding request package2Level 3BaseiJKLM3Data Transmission from Node D To Base StationData Transmission from Node D To Base StationNode D starts to send data package to the base station via Node i since it is the only path in its routing table.Node i will randomly pick one of the entry ( choose the next hop from routing table entry, via K, or via L, or via M) with equal probability to determine which path to forward the data.Assuming K is chosen by Node i and now node K will check its routing table, determine its next hop, either via Node X or Node Y.Suppose X is chosen and its next hop is the base station and the package is now transmitted from Node D to the base station.During this Data Forwarding, we used routing path 11111112222222331224Transmitting Datafrom Node D to Base with 4different path:Path 1 -- GreyPath 2 -- RedPath 3 -- GreenPath 4 -- Yellow23BaseD4123iKLMXYMulti Path Nodes for Senor NetworkMulti Path Nodes for Senor Network•Level 0  Black•Level 1  Blue•Level 2  Green•Level 3  pink•Level 4  white•Level 5  yellow•Level 6  GreyMulti Path for Sensor networkMulti Path for Sensor network•Node has alternative path to send data to base station.100 nodes with 2 Hour Simulation Result Level 3 Nodes Power consumption•Red Curve = nodes’ power consumption in original implementation in JPL sensor network•Blue Curve = nodes’ power consumption in multi path design.•Original power consumption Range :{110.29w,260.27w} •Our power consumption Range:{116.73w, 208.44w}•No packages lost in new implementation100 Nodes with 2 Hour Simulation Result Level 4 Nodes Power consumption•Red Curve = nodes’ power consumption in original implementation in JPL sensor network•Blue Curve = nodes’ power consumption in multi path design.•Original power consumption Range :{92.31w,186.16w} •Our power consumption Range:{95.84w, 151.63w}•No packages lost in new implementation200 nodes with 5 Hour Simulation Result Level 1 Nodes Power consumption( test when the nodes are more dense)•Red Curve= nodes’ power consumption in original implementation in JPL sensor network•Blue Curve = nodes’ power consumption in multi path design.•Original power consumption Range :{373w,1272.35w} •Our power consumption Range:{408.61w,1149.19 w}•No packages lost in new implementationConclusion and Future workConclusion and Future workAdvantage : 1) Balancing Node Work Load 2) Prolong network life time 3)No performance disgradeFuture Proposal : Data transmission : when Node I of level N+1 tries to pick next Hop J of level N, it should chooses according to :Probability (I picks J)  E j / Pij E j = Energy Left in Node J Pij = Power needed for transmitting data from I to JReferenceXiaoyan Hong et al., The Mars Sensor Network: efficient, power aware communications, (Milcom 2001)Chalermek Intanagonwiwat, Ramesh Govindan, and Deborah Estrin, Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks, Proceedings of the Sixth Annual International Conference on Mobile Computing and