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Localized Techniques for Power Minimization and Information Gathering in Sensor Networks. EE249 Final Presentation David Tong Nguyen Abhijit Davare Mentor: Farinaz Koushanfar. Outline. Introduction Assumptions Project Goals Problem Formulations Related Work
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Localized Techniques for Power Minimization and Information Gathering in Sensor Networks EE249 Final Presentation David Tong Nguyen Abhijit Davare Mentor: Farinaz Koushanfar
Outline • Introduction • Assumptions • Project Goals • Problem Formulations • Related Work • 1. Node coordination for power minimization • 2. Network traversal algorithm • 3. Generation of optimal solution • Experimental Results • Conclusions • Future Work
Introduction • Ad-Hoc wireless sensor networks • Unattended autonomous operation • Limited energy sources • Idle power consumption • Not just point to point routing, but gathering information using only local information • Uncertainty about node status (active, standby)
Assumptions for the sensor network • Unit Disk Communication Model • Nodes can communicate iff (Euclidean distance Rc), where Rc is fixed communication range • ECommunication >> EComputation • Eidle ~ ECommunication (While radio is on) • The algorithms run above the MAC layer protocol • Node Information includes its ID, geographic position and status (active/standby) • Each node has information about its neighbors
Project Goals • Efficient localized node coordination for extending the network lifetime • Power efficient information gathering method • Gathers the queries from all of the nodes within a predefined area in the deployment field • Attempts to visit as few nodes as possible, minimizing communication energy consumption
Problem Formulations 1 – Localized power efficient coordination: • Objective: Maximize the number of nodes in standby mode using only local information. • Constraints: Global network connectivity should be preserved, i.e. A node cannot go into standby if it disconnects the network. 2 – Localized efficient information gathering: • Objective:Minimize the number of communications required for gathering complete information from a network, where some nodes are in standby. 3 – Generation of optimal solution for network traversal • Objective: Find a network and an optimal traversal path through that network that minimizes the number of nodes visited while gathering data from each node
Power aware MAC layer PAMAS [Kravets et al. 2000], [Woo et al. 2001], S-MAC [Ye et. al. 2002] Coordination power saving strategies Span [Chen et al. 2001], GAF [Xu et al. 2001] Ascent [Cerpa et. al., 2002] They do not state necessary and sufficient conditions for putting a node in standby & have less power savings. Network discovery Birthday protocols [McGlynn et al. 2001], TopDisk [Deb et. al. 2002], ad-hoc routing survey [Stojmenovic et al. 2002] We also consider the network shape & regions of low density. Perimeter routing Guaranteed delivery [Bose et al. 2001], GSPR [Karp et al. 2001] They did not consider perimeter routing for studying the shape of the network and has just used it for coming out of local minima in routing. Related Work
1 - Efficient Node Coordination for Power Minimization • We guarantee that enough nodes stay active to maintain network connectivity • Necessary and sufficient condition for putting a node into standby is to ensure an alternate path exists between any two of its neighbors • Fair power saving method • Only local information used
1 - Initial Phase: Token Assignments • Token defines the current active node that has the control of the flow of procedure • Distributed local computation multiple tokens required • Handshaking between tokens is done through a semaphore-like mechanism • During the initial phase, tokens are assigned to the nodes • Such that every node has a token • Tokens act in a localized area
1 - Node Selection for Standby Mode • Each token uses updated information from its local area to make a decision. • Token considers itself and its neighbors. • Each token “locks” the nodes it is considering. • Token chooses node whose neighbors will be able to communicate for the longest time if the node stays in standby mode. • Each node sleeps for Ts interval, dependent on the energy in its local area • Token is then passed to node which gone the largest amount of time without obtaining the token (“miss me?”)
1 - Parameter Tuning Flexibility in choosing: • Ts vs. density • Number of tokens • Ts vs. number of tokens
2 - Information Gathering: What is new? • While there exist many point-to-point routing algorithms, no major contribution for complete area traversal. • Guarantee complete information gathering • Graph theoretic and geometric abstraction of the network area: • Perimeter (shape) of the network • Ranking w.r.t connectivity • Completely localized traversal procedure
Starting Node 2 - Perimeter Routing • Find the perimeter of the network using method similar to Right-Hand Rule. • Problem: • If edges cross in the network, right-hand rule fails
w u v 2 - Perimeter Routing - Planarizing • Solution: Planarize the Graph • To include the edge (u, v) in the graph, the shaded circle must not contain any node w. (Gabriel graph planarization)
2 - Partitioning the graph • While traversing the perimeter, find partitioning points of the planarized graph. Partitioning Point Starting Node
2 - Traversal Method • Network traversal begins at a perimeter node • Next node is determined locally according to: • Rank – Distance from perimeter • Parity – Even or odd rank • Section – Prefer unvisited nodes in same section • Novelty – # of unvisited neighbors
3 - Generating Instances with Known Solutions • To accurately evaluate the quality of network traversal heuristic, must know the optimal solution. • However, given a network, generation of optimal network traversal is NP-complete. • Alternative: Generate an optimal solution first, then generate network around it. • A path through the network is the optimal if each node on the path has at least one unique neighbor, and no other nodes have unique neighbors
3 - Generating Instances with Known Solutions (cont’d) • Place the initial node randomly. • Choose a unique neighbor node within rc. • Choose a second node that is in range of the first node, but not of the unique node • Iterate until path is required length • Filler nodes can be added that are in range of the path nodes
Experimental Results: Coordination • As number of nodes in the network increases, standby strategy becomes more effective
Conclusions • Tremendous energy savings using a localized standby strategy • Necessary and sufficient conditions to maintain the network connectivity • Energy efficient information gathering, which uses both geometric and graph theoretic information
Future Work • Find efficient information dissemination methods • Integrate other power saving strategies into the simulations