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CS230 Project Mobility in Energy Harvesting Wireless Sensor Network

CS230 Project Mobility in Energy Harvesting Wireless Sensor Network . Nga Dang, Henry Nguyen, Xiujuan Yi. What is our project?. Motivation: Wireless Sensor Network - Sensor nodes are powered by batteries - High maintenance cost - Unreliability: network is disconnected

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CS230 Project Mobility in Energy Harvesting Wireless Sensor Network

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  1. CS230 ProjectMobility in Energy HarvestingWireless Sensor Network Nga Dang, Henry Nguyen, Xiujuan Yi

  2. What is our project? Motivation: Wireless Sensor Network - Sensor nodes are powered by batteries - High maintenance cost - Unreliability: network is disconnected when nodes are out of battery Energy Harvesting WSN - Powered by a centralized energy harvesting source whose energy is delivered to sensor nodes by robot - Advantage: + Green computing + Autonomous system + Low maintenance cost Battery System Model Energy Harvesting System Model

  3. What have other groups done? Application • Energy-Efficient Approaches in WSN • Hardware layer: energy-efficient circuit, redundant deployment _ Network layer: energy-efficient routing protocol and network topology _ Operating system: dynamic voltage scheduling, duty cycling _ Application layer: energy-efficient quality-aware data collection, multi-version applications • Use robot mobility as data collector • Robot is scheduled to visit sensor nodes, collecting data in close range • Goal: prolong system’s lifetime • reduce transmission energy for sensor nodes (shorter range) • Find a shortest path to minimize travelling energy • Avoid buffer flow at sensor node’s data buffer, deliver data in time • Usually modeled as Travelling Salesman Problem with additional constraints Operating system Network layer Hardware layer

  4. What have other groups done? (cont.) • Use robot mobility as energy deliverer • Robot is equipped with a large capacity battery • Sensors’ nodes batteries are monitoring periodically • Every hour k nodes with least remaining energy are chosen and robot will visit and charge these nodes through wireless transfer • Prolong system lifetime by charging extra battery • Disadvantage: • System lifetime extension is limited by robot’s battery capacity • Maintenance cost: changing robot battery

  5. How does our system work? Send Energy Requests Sensor Nodes Sensor Nodes Sensor Nodes Execute plan: Visit nodes and recharge batteries Base Station Report charging status Robot Collect Energy Requests &Run algorithm to schedule charging activity Send schedule to robot

  6. The charging algorithm If the robot can’t visit all the node. - It should find the maximum subset of nodes it can visit and give the shortest path of that subset. Input to TSP: D[i]: Deadline of each sensor node C[i,j]: Time to travel from node i to node j W[i]: Waiting time at each node i to charge Input: Energy request queue: sensor deadline Find a starting time satisfy both energy and timing constraints Travelling Salesman Problem Output: A sequence of sensor nodes which robot had to visit Input: Robot charging status Robot speed & power consumption & energy harvesting profile

  7. 1.5 hours 4 hours 2 hours 2 hours 2 hours 1 hour 1 hour 1 hour Charging algorithm example 12:00 7:30 13:15 21:00 0.5 hour charging 23:00 6:10 0.5 hour charging 8:00 9:30 leave base station at 5:00 get back at 23:40

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