Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks
Mihail L. SichitiuDepartment of Electrical and Computer Engineering
North Carolina State University
IEEE Infocom 2004
Speaker: jenchi
Outline
Introduction Proposed approach
The steady state phase The setup and reconfiguration phase
Simulation results Conclusion
Introduction
The characteristic of sensor nodes Very small form Be inexpensive and deployed in very large
numbers Once deployed, the sensor networks are
usually unattended The life of the sensor network is determined by
the life of its batteries Such a network is typically expected to work
for extended periods of time
Introduction
The power consumption in sensor networks Idle listening Retransmissions resulting from collisions Control packet overhead Unnecessarily high transmitting power Sub-optimal utilization of the available
resources
Introduction Two modes of sensor networks
Event driven sensor network Sensor nodes do not send data until a certain event oc
curs A forest fire monitoring application
difficulty: the sensor network is able to wake up the entire network when the event occurs
Continuous monitoring sensor network Data is sampled and transmitted at regular intervals
A temperature monitoring station Indeed, in order to detect an event, a continuous monit
oring scheme is necessary
Introduction
This paper presents an approach tailored specifically to the needs of sensor networks with continuous monitoring capabilities
The proposed scheme derives its power efficiency from eliminating idle listening and collisions in the sensor network
The need for such a scheme is highlighted and prompted by recent habitat monitoring applications
Proposed approach
To develop a framework for deterministic optimal energy conservation while maintaining the network real-time characteristics
Sensor nodes dynamically create on-off schedules in such a way that the nodes will be awake only when needed and asleep the rest of the time
Proposed approach
The proposed scheme can be decoupled into two distinct phases for each flow in the network The setup and reconfiguration phase
To set up the schedules that will be used during the steady state phase
The steady state phase It utilizes the schedule established in the setup
and reconfiguration phase to forward the data to the base station
Proposed approach
Assumptions The traffic is periodic, with the same period in
the entire network Each node originates only one packet in each
period To ensure that the control packets necessary
to set up schedules do not collide with the data packets forwarded, a two-level priority scheme MAC layer has to be used
Proposed approach
State diagram for each data flow in the network
The steady state phase
Assume that the network is perfectly synchronized
The nodes on the path forward DATA packets at the appropriate times
Each node on the path stores a schedule table that specifies when various actions have to take place
The steady state phase The three different actions
Sample The source node taking a data sample Be forwarded along the path to the base station
Transmit The action of transmitting a packet of the flow to
the next node on the path to the base station Receive
The reception of a packet The packet will be further transmitted to the next
node
The steady state phase
The actions are stored in a schedule table that has two columns• the first column: what type of action that has to be performed• the section column: when a certain action has to take place
The steady state phase
□
The setup and reconfiguration phase
The schedule setup algorithm for any flow proceeds in two steps Route select
A route to the base station is selected Route setup
Schedules are being setup along the chosen route
If it fails, a new route is selected
The setup and reconfiguration phase
The route select step The setup and reconfiguration algorithm is
independent of the underlying routing algorithm Power aware routing algorithms may be
preferable
The setup and reconfiguration phase
The route setup step A route setup (RSETUP) packet will be sent
on the selected route from the source of the flow to the base station
To find a time when a DATA packet can be scheduled without colliding with other nearby transmissions
The RSETUP packet contain the node source and the duration of the packets on that flow
The setup and reconfiguration phase
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 802.11 (SIFS/DIFS)
The setup and reconfiguration phase
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).
802.11 power savings mode
Proposed scheduling approach.
Simulation results
Will use a base case and vary one parameter at a time. Base case parameters:
Nodes: 100 Transition from “off” to “on”: 3msArea: 100x100m
Transmission Radius: 25m
Current in TX mode: 17mA
One sample sent every: 60sSynchronization precision: 1ms802.11 PSM beacon interval: 500ms
Current in RX mode: 10mACurrent in idle mode: 10µA
Simulation results Simulation results for base case
Network Lifetime
Mean Std. deviation
No Power Savings
8.3 days 4 minutes
802.11 PSM 3.2 months 7.5 days
Power scheduling
24.2 months 5 months
Simulation results—Dependency of the network lifetimes on the number of nodes for a constant deployment area
Net
wor
k lif
etim
e [s
]
Initial number of nodes
Simulation results—Dependency of the network lifetimes on the number of nodes for a constant density
Net
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k lif
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Initial number of nodes
Simulation results—Dependency of the network lifetimes on the measurement period of the network
Net
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Measurement period of the sensor network(s)
Simulation results—Dependency of the network lifetimes on the power consumption in idle mode
Net
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k lif
etim
e [s
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Current drawn in idle mode (mA)
Simulation results—Dependency of the network lifetimes on the precision of the synchronization algorithm
Net
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k lif
etim
e [s
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Synchronization precision Δ [ms]
Conclusion
Presented a new distributed scheduling algorithm for stationary continuous monitoring sensor networks
Is fully distributed and works in tight cooperation with popular sensor networks routing and MAC families of protocols
For the right type of networks, it is shown via simulations that the network lifetime can be increased by orders of magnitude
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