1 a delay-aware reliable event reporting framework for wireless sensor-actuator networks presented...
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A Delay-Aware Reliable Event Reporting Framework for Wireless Sensor-Actuator Networks
Presented by Edith NgaiSupervised by Prof. Michael R. Lyu
Term Presentation Spring 2006
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Outline Introduction Related Work Network Model and Objective Delay-Aware Reliable Event Reporting
Framework Grid-Based Data Aggregation Priority-Based Event Reporting Actuator Allocation
Simulation Results Conclusion
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WSAN Collection of sensors and actuators Sensors
small and low-cost devices with limited energy, sensing, computation, and transmission capability
passive devices for collecting data only and not interactive to the environments
Actuators resource-rich devices equipped with more energy, stronger
computation power, longer transmission range, and usually mobile
make decisions and perform appropriate actions in response to the sensor measurements
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WSAN Sensors and actuators
collaborate sensors perform sensing and
report the sensed data to the actuators
actuators then carry out appropriate actions in response
Applications environmental monitoring sensing and maintenance in
large industrial plants military surveillance, medical
sensing, attack detection, and target tracking, etc.
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Our Focus Design of a generic framework for
reliable event reporting in WSANs Reliability in this context is closely
related to the delay, or the freshness of the events, and they should be jointly optimized
Non-uniform importance of the events can be explored in the optimization
A delay- and importance-aware reliability index for the WSANs
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Our Framework Seamlessly integrates three key modules
to maximize the reliability index: 1. A multi-level data aggregation scheme,
which is fault-tolerant with errorprone sensors
2. A priority-based transmission protocol, which accounts for both the importance and delay requirements of the events
3. An actuator allocation algorithm, which smartly distributes the actuators to match the demands from the sensors.
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Related Work Real-time communication protocol in WSN
SPEED [Hu et. al. 2003] real-time unicast, real-time area-multicast and
real-time area-anycast for WSN achieved by using a combination of feedback
control and non-deterministic QoS-aware geographic forwarding with a bounded hop count
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Related Work Real-time communications in WSN
MMSPEED [Felemban et al. 2005] Multi-Path and Multi-Speed Routing Protocol for
probabilistic QoS guarantee in WSN multiple QoS levels are provided in the timeliness
domain by guaranteeing multiple packet delivery speed options
supported by probabilistic multipath forwarding in the reliability domain
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Related Work Distributed coordination framework for WSAN
[Melodia et al. 2005] based on an event-driven clustering paradigm all sensors in the event area forward their readings to
the appropriate actuators by the data aggregation trees
provides actuator-actuator coordination to split the event area among different actuators
assumes immobile actuators that can act on a limited area defined by their action range
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Network Model Compose of sensors
and actuators Nodes aware of their
locations Divide the network
into a number of grids cell for data aggregation
A subset of nodes, referred as reporting nodes, v, send data to the actuators
Anycast routing
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Objective Reliability index
Measures the probability that that event data are aggregated and received accurately within pre-defined latency bounds
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Grid-Based Data Aggregation
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Priority-Based Event Reporting
We adopt a priority queue in each sensor, which plays two important roles:
1. prioritized scheduling to speed up important event data transmission
2. queue utilization as an index for route selection to meet the latency bounds
In our preemptive priority queue, the packets for the event data are placed according to its data importance and served in a first-in-first-out (FIFO) discipline
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Delay The delay of sensor node is composed of the processing
delay, the queueing delay, the transmission delay, and the propagation delay
dtotal = dproc + dq + dtran + dprop The processing delay and the propagation delay are
typically only a few microseconds Our routing protocol allocates routes according to the data
importance Transmission delay dtran
We borrowed the idea from the SPEED protocol to estimate dtran by acknowledgement
Queueing delay dq
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Queueing Delay The queueing delay of the highest priority
queue
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Queueing Delay
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Next Hop Selection
Consider node i receives new type of event data datae with
data rate It broadcasts a control message to its immediate
neighbors Every neighbors j replies with the message:
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Next Hop Selection Node i requires that the end-to-end delay to actuator is less than the
latency bound Be
It first estimates the number of hops h from i to the closest actuator a and the maximum delay from i to j, delayi,j.
dq_max is the maximum queueing delay allowed, such that the latency bound Be can be met
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Next Hop Selection Among the neighbors with dq_max>0, node i starts
inspecting the neighbors with λhigh=0 and λlow=0 means it is not forwarding any event data as all
next hop with λhigh>0 means it is transmitting some data with higher importance
If node i selects the next hop j with λlow>0 , then it may need to preempt some less important data
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Next Hop Selection For each neighbor above, i calculates the maximum data
rate λi that it can forward the data to while satisfying the latency bound
The inspecting process stops when i finds enough neighbors j to forward the data, such that
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Data transmission with Latency Constraint The latency bound Be will be updated before forwarding to
next hop
Be’ = Be – ( tdepart – tarrive) – dtran – dprop
A sensor always select a next hop that can satisfy the latency bound
If no route can meet the bound, it informs the previous hop forward the packets via another node.
In case of congestion (e.g. high priority packets flows in and preempts low priority packets), previous hop should also be informed
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Actuator Allocation The actuators may record the
event frequency and re-arrange their standby positions periodically
Let freqg be the event frequency of the grid cell g
Estimate freqg periodically as follow:
, where freqg-1 is previous record of the event frequency in grid g
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Actuator Allocation
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Simulations Simulator: NS-2 Metrics
On-time Reachability Average Delay Overall Reliability
4 events 2 with high importance 2 with low importance Located in left bottom corner
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On-Time Reachability
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Average Delay
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Overall Reliability
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With Actuator Allocation
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With Actuator Allocation
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Conclusion We provide a distributed, self-organized, and comprehensive solution for
reliable event reporting and actuator coordination in WSAN We formulate the event reporting problem and define reliability as the
percentage of event data that can reach the destination and satisfy certain accuracy and latency constraints
We provide a distributed data aggregation mechanism, which can tolerate sensing failures and reduce network traffic
We propose a reliable priority-based event reporting algorithm with event importance. Sensors can route their data based on the affordable service rate provided by its neighbors
We further improve the efficiency of event reporting and reaction by proposing an actuator allocation algorithm. It estimates the event happening frequency in the network and balances the workload among the actuators by allocating them proper locations
Simulation results are provided to demonstrate the effectiveness of our solutions.
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Q & A
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