1 A Low Latency Data Transmission Scheme for Smart Grid Condition Monitoring Applications I R F A N S. A L - A N B A G I, M E L I K E E R O L - K A N T A R C I, H U S S E I N T. M O U F T A H U N I V E R S I T Y O F O T T A W A O T T A W A, O N, C A N A D A E M A I L S : { I A L A N 0 5 5, M E L I K E. E R O L K A N T A R C I, M O U F T A H } @ U O T T A W A. C A
Outline 2 Introduction Delay-responsive, Cross Layer (DRX) Data Transmission Delay Estimation Performance Evaluation Conclusions
Introduction(1) 3 WSNs offer many advantages; Ability to work in extreme environmental conditions Enhanced fault tolerance Low power consumption Self configuration Low cost WSNs have low data rate and limited energy resources Performance bottleneck Delivery of time-critical data becomes a significant challenge Thus data prioritizing techniques becomes essential in WSNs
Introduction(2) 4 In the smart grid, a fault occurring in any of its assets may trigger load control actions in various locations. The status of the smart grid assets needs to be monitored in near real-time. Transmitting delay-critical data in the smart grid via WSNs needs data prioritization and delay-responsiveness. We present a Delay-responsive, cross layer (DRX) data transmission scheme.
DELAY-RESPONSIVE, CROSS LAYER (DRX) DATA TRANSMISSION MAC Layer Configuration DRX scheme includes a data prioritization cross layer adaptive scheme 5 The scheme enables the interaction of the application layer with the MAC and physical layers of the IEEE80.15.4 protocol stack DRX achieves delay reduction in highly critical smart grid monitoring applications. The application layer independently activates E[D] if the measured data trigger an alarm indicating high priority.
DELAY-RESPONSIVE, CROSS LAYER (DRX) DATA TRANSMISSION If E[D] > τ TH then place a flag in the application layer header indicating that lower layers should treat these packets differently. The MAC sub-layer requests the physical layer to make changes in its parameters. 6 The physical layer decreases the CCA length from 8 symbol periods to 4 symbol periods. The physical layer will sense the channel in half of the normal CCA duration and report the results to the MAC sub-layer. The node will have a higher probability to acquire the channel and transmit its data before other contending nodes.
Delay Estimation (E[T]) Estimate the delay using a Markov chain-based analytical model of the slotted CSMA/CA mechanism of IEEE 802.15.4 The model is based on a WSN having a PAN coordinator with N nodes Each node uses beacon-enabled mode The model uses Markov chain to model the behavior of a single node The main idea behind the model is that Sensor nodes can estimate the busy channel probabilities Depending on first and second CCA s (ρ 2 and ρ 1 ). 7
DELAY-RESPONSIVE, CROSS LAYER (DRX) DATA TRANSMISSION 8
Performance Evaluation We use QualNet network simulator 9 We use a star topology having N nodes and a coordinator All nodes are operating in the 2.4 GHz band with a maximum bit rate of 250 Kbps The transmission range was set to 40m and all the nodes are in the same PAN Each result represents an average of 10 runs
Performance Evaluation 10 Average end-to-end delay
Performance Evaluation 11 Packet delivery ratio
Performance Evaluation 12
Performance Evaluation 13 Packets lost due to collisions in the DRX scheme
Performance Evaluation Case Study: Transformer monitoring 14
Conclusions The presented scheme achieve delay-responsiveness by modifying the parameters of the physical layer of the IEEE 802.15.4 protocol. 15 DRX scheme succeed in reducing the delay for high priority data and maintaining satisfactory packet delivery ratios. Smart grid specific results show that the DRX scheme has an effect on the end-to-end delay reduction compared to the default IEEE 802.15.4 setting. This delay reduction will enhance the smart grid operation in situations where sudden changes in loads or the generation cycle
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