Event Processing Middleware for Wireless Sensor Networks

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1 Event Processing Middleware for Wireless Sensor Networks Selvakennedy Selvadurai University of Sydney

2 Outline Introduction System Assumptions EPM Architecture Group Management and Centre Localisation Components Results Conclusions 2

3 WSN Background This technology is evolving rather rapidly E.g., the Mica2 sensor has roughly 8x the memory and bandwidth as its predecessor, the Rene sensor for the same power budget Some apps: earthquake monitoring, target tracking and surveillance, structural monitoring and precision agriculture Typically, these apps entail simple sensing and relaying to the sink(s) for processing and storage 3

4 In-Network Processing Now, need more intelligence into the network itself inline with the hardware advance Moreover, in many control apps, latency constraints call for more in-network processing A number of efforts being undertaken These efforts may be classified either as statistical processing or semantics processing Most fall under the former class data processing purely involves statistical treatments informed by any temporal/spatial correlation structure in the data 4

5 Semantic Processing In semantics processing, data processing is informed by the application semantics Sensor readings of high significance are tracked reflecting the readings of phenomena of interest Sensor nodes will need to collaboratively process their data Enables rapid reactive mechanism towards events through appropriate actuators. For instance, some nodes may detect a fire event, and then collaboratively process and activate the relevant water sprinklers Would complete the sense-control-actuate loop. 5

6 Collaborative Processing Phenomena may span an area Collaborative processing is needed We might be interested to capture its area coverage, its boundary and its centre Various algorithms have been proposed independently to process specific event properties It may be more beneficial to provide event processing services in an integrated manner 6

7 Event Processing M ware (EPM) Advantageous to provide them as middleware services Middleware has often been useful for bridging the gap between the lower-level components and the application Eases development of distributed applications A WSN middleware, termed MiLAN [3], allows apps to specify their quality needs and proactively adjusts the network characteristics DSWare middleware [4] provides real-time event detection services that sits between the application layer and the network layer. Our proposed middleware could logically complement DSWare by providing event processing services. 7

8 EPM It masks the collaborative processing required for some services As concrete examples, we implement the event boundary, event area and event centre processing services The edge detection component will form the core component Other services uses the above to estimate both event centre and area. This is the first such attempt. The middleware also exploits the existence of clusterheads in certain data gathering protocols, like LEACH, HEED and T-ANT Using this approach, significant overhead reduction is achieved while maintaining up to 95% accuracy of event information 8

9 System Assumptions Each node knows its location Nodes know interesting sensor readings (appdefined) Nodes within event are termed affected nodes Otherwise, unaffected nodes. The edge of a phenomenon is the imaginary boundary between these sets event area is circular 9

10 EPM Architecture Event Subscription Higher-Level Processing Event Notification Event Data Storage Edge Detection Group Management 10

11 EPM Components Event Notification allows a node to discover its neighbourhood related to certain events Event Data Storage: Some information are kept at the nodes and cluster info at CHs Group Management: This component controls the collaboration among sensor nodes Edge Detection: It tests whether the current node is on the event edge (based on T-Fit [9]) Higher-Level Processing: event centre localization and area computation Event Subscription: A type of data dissemination service 11

12 Group Management An overlay tree is formed among CHs When an event transpires, sensors in disjoint clusters might detect it CHs collect from their clusters To choose the root, a natural choice would be a CH close to the event region Data are aggregated and finally processed at the root Any subscribed higher-level services is pushed to the sink from root 12

13 Event Centre Localisation A x-coord sorted list of edge points becomes available at the tree root For center localization, we need to find the furthest distance between any pair of edge nodes Since the diameter of a circle can II I be approximated by the longest B possible pair-wise distance, the centre is the midpoint C III D IV A An exhaustive search over the edge nodes can be performed but results in O(n 2 ) 13

14 Event Centre Localisation The nodes are organised into k subgroups Two node pointers are used for traversing, and they are initialized at opposite ends of the edge node list Then, line segments involving nodes in subgroup 1 and k are checked, followed by nodes in 1 2 k-1 k subgroups 2 and k-1 and so on. x_start B A x_end C x_inv 14

15 Simulation Scenario Sensor nodes are randomly distributed in a square MxM region with M = 100 m The data message size is fixed at 30B. Node radio range is fixed at 20m Event is circular and radius is 30m 15

16 CL Estimation Error Estimation Accuracy (%) Number of Nodes 16

17 CL Estimation Error Estimation Accuracy (%) Event Radius (m) 17

18 Communications Overhead Total Communication Overhead(Byte) Mean Value with EPM Mean Value without EPM Event Area Radius (m) Total Energy Consumption Mean Value with EPM Mean Value without EPM Radio Range (m) 18

19 Conclusions EPM is proposed The edge detection module forms the core component. it supports higher-level event processing services. The in-network service is found to achieve up to 95% accuracy in its estimation of event center as well as area It also has significant lower communication overhead and energy usage These middleware services may be subscribed by the sinks and the actuators 19

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