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Dynamic Sleeping Scheduling for Real-time Wireless Sensor Networks

Department of EECSUniversity of Tennessee, Knoxville

Xiaodong Wang, Yanjun Yao

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Introduction Low energy consumption

Lower energy consumption -> longer life time Equipment usually powered by batteries

Approaches to save power: Transmission power adjustment, supported by hardware, e.g., power level 1 – 31

on Tmote Invent Periodic sleeping Etc.

Real-time requirement: to constrain the end-to-end delay of information relay A lot of WSN applications require real time service quality:

Wood fire monitoring Battle field application

Border Intruder Monitoring Alarm System

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Periodic Sleeping Periodic sleeping

Sender knows receiver’s sleeping scheduling Sender wakes up when receiver wakes up

Tradeoff between power consumption and real-time Wake up more often -> less delay, more power

sit iC iiR ,1:Sleeping Delay :Cycle Time :Retransmission Count

Periodic sleeping incurs delay!!

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Goals and Challenges Goal: develop a dynamic sleeping scheduling scheme

Provide end-to-end real-time guarantee for each data flow Take advantage of periodic sleeping to save power.

Challenges: Model the end-to-end delay vs. sleeping scheduling on each node.

Each flow constructed by several nodes. Approach to coordinate the nodes

The scheme for the dynamic change of sleeping scheduling. Centralized or distributed

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Preliminary Plan Break end-to-end deadline to sub-deadline on each node

Decouple the coordination of sleeping scheduling on all nodes in the same flow.

Simplify the delay vs. sleeping schedule model establishment.

Distributed approach to adjust sleeping scheduling by each node. Adjust sleeping scheduling for each node to meet sub-deadline. Using feed back control theory to adjust the sleeping scheduling

Plan schedule: By mid-term:

Finish the model of delay vs. sleeping schedule. Implement feed back control on single hop

By final: Finish the coordination of the whole network by controlling all the nodes Using NS2 to do experiment

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Q&A