Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina State University George Rouskas Department of Computer Science North Carolina State University Presented by: This work was supported by the NSF Grant and by the Center for Advanced Computing and Communication.

Outline  Wireless Sensor Networks  Assumptions  Overview of the scheme  Steady State Phase  Setup and Reconfiguration Phase  Simulation results  Conclusion

Wireless Sensor Networks (WSN)

Assumptions  Periodic monitoring (i.e., one sample taken every T seconds).  Common period T known in the entire WSN.  Neighboring nodes are synchronized to each other.  Rate of changes in network topology or WSN objective is low compared to the monitoring period.  Each node generates one flow toward the base station.

Sources of power wastage in WSNs  Idle listening  Retransmissions resulting from collisions  Control packet overhead  Unnecessarily high transmission power  Sub-optimal utilization of the available resources Proposed Scheme

State Diagram for each Flow

Steady State Phase Three actions can be scheduled by each sensor node: Sample (read sensor) Transmit (either own sensor reading or forward) Receive (to be further forwarded)

Example of 10 node sensor and a possible distributed schedule

The Setup and Reconfiguration Phase Proceeds in two steps  Route Select A route to the base station is selected (by the routing algorithm outside the scope of this paper, any existing algorithm is good).  Route Setup Schedules are being setup along the chosen route. If it fails, a new route is selected.

Route Setup  A lower priority (lower than data on established paths) RTS/CTS handshake ensures that only non-interfering transmissions are scheduled at overlapping times.  The length of the route setup packet is larger than the length of a data packet  Proposed priority scheme similar to (SIFS/DIFS)

Comments  The route-setup phase, while being a typical layer 3 function, reliues heavily on layer 2 information and properties.  The schedule can take full advantage of the spatial reuse inherent in ad-hoc networks.  Schedule tables should be able to maintain “per flow” information (two entries for every flow). Aggregation is possible if this becomes a problem.  The route formation scheme is independent on the routing protocol. Power aware routing protocols can be used in conjunction with the proposed scheme.

Simulation Results  Custom simulator (existing simulators cannot simulate hundreds of nodes for periods of months and years).  Network lifetime = when 50% of the nodes cannot report to the base station (either the batteries are depleted or no available routes)  Will compare three technologies: Always On (sensors in receive mode when not transmitting) power savings mode Proposed scheduling approach.

Simulation Setup  Will use a base case and vary one parameter at a time. Base case parameters: Nodes: 100 Transition from “off” to “on”:3ms Area: 100x100m Transmission Radius: 25m Current in TX mode:17mA One sample sent every: 60s Synchronization precision: 1ms PSM beacon interval: 500ms Current in RX mode:10mA Current in idle mode:10µA

Simulation Results for Base Case Network Lifetime MeanStd. deviation No Power Savings 8.3 days4 minutes PSM3.2 months7.5 days Power scheduling 24.2 months5 months

Dependency of the network lifetimes on the number of nodes for a constant deployment area.

Dependency of the network lifetimes on the number of nodes for a constant density.

Dependency of the network lifetimes on the measurement period of the network.

Dependency of the network lifetimes on the power consumption in idle mode.

Dependency of the network lifetimes on the precision of the synchronization algorithm.

Conclusion  New power savings algorithm for stationary, continuous monitoring wireless sensor networks.  Exploits the time scale difference between sensor network reconfiguration periods and data forwarding periods.  Shows via simulations lifetime increases of several orders of magnitude.

Thank you for your attention Questions?