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MiLAN

MiLAN. Muhammad Mirza Zeeshan Mehmood Supervisor: Dr. Waltenegus Dargie Seminar Presentation : Wireless Sensor Networks ( Winter 2006-07 ) 16.01.2007. Contents. Introduction Motivation Architecture Conclusion Critique References. Introduction.

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MiLAN

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  1. MiLAN Muhammad Mirza Zeeshan Mehmood Supervisor: Dr. Waltenegus Dargie Seminar Presentation : Wireless Sensor Networks ( Winter 2006-07 ) 16.01.2007

  2. Contents • Introduction • Motivation • Architecture • Conclusion • Critique • References Wireless Sensor Networks: Winter 2006-07

  3. Introduction MiLAN ( Middleware Linking Applications and Networks ) is a middlewarearchitecture: • Maximizing applicationlifetime While • Providing application QoS by controlling and optimizing network as well as sensors. Wireless Sensor Networks: Winter 2006-07

  4. Motivation Personal Health Monitor Application • The QoS of the different variables of interest at each different states of patient • The state-based Variable Requirement graph High respiratory rate Low blood pressure Respiratory Rate Blood Pressure 0.8 0.8 Blood O2 0.3 Blood O2 0.7 Heart Rate 0.8 0.3 Heart Rate 0.3 Blood O2 1.0 ECG Diagram 0.3 Normal Heart Rate High Heart Rate Blood Pressure Wireless Sensor Networks: Winter 2006-07

  5. Motivation Personal Health Monitor Application • The QoS of the different variables depends on which sensors provide data to the application • The Sensor QoS Graph Heart rate Blood pressure 1.0 0.7 0.8 0.7 1.0 0.8 0.7 1.0 0.7 Blood pulse Blood press Blood flow Pulse oxy ECG Blood press Blood flow Pulse oxy Virtual sensor Wireless Sensor Networks: Winter 2006-07

  6. Motivation The challenging characteristics of sensor network • 1. Inherent Distribution • The sensors are distributed throughout a physical space and primarily connected wirelessly • ? increase unreliability of whole system • 2. Dynamic Availability • Either mobility through space, addition of new sensors, or loss of existing sensors causes the set of available sensors to change over time • ? Availability is the main factor • 3. Resource Limitation • Both network bandwidth and sensor energy are constrained. This is especially true when considering battery-powered sensors and wireless networks • ? Provide less bandwidth and less reliable connectivity than wired network Wireless Sensor Networks: Winter 2006-07

  7. Goal of MiLAN MiLAN control sensor network as well as the sensors and maximizes Application life time and Qos Application QoS Requirement Network Monitoring State Of Monitored Objects Control the network as well as the sensors Provide Application QoS Maximize Application Lifetime Wireless Sensor Networks: Winter 2006-07

  8. Relationships among different Middleware Wireless Sensor Networks: Winter 2006-07

  9. MiLAN Application Application QoS MiLAN Sensor power on&off Data routing path Sensor data transmission rate Network Information Data Reading Sensor Network Wireless Sensor Networks: Winter 2006-07

  10. MiLAN Architecture Wireless Sensor Networks: Winter 2006-07

  11. MiLAN Architecture Application Middleware - MiLAN Application QoS Requirement App. Feasible Set Network Feasible Set Network Information Sensed Object States Overall Set Trade-off computation Application Logic Doctor Sensor Network Configuration Sensor Reading Sensor Network Wireless Sensor Networks: Winter 2006-07

  12. MiLAN Components Wireless Sensor Networks: Winter 2006-07

  13. A High-level overview of MiLAN operation and Partial MiLAN API Wireless Sensor Networks: Winter 2006-07

  14. MiLAN Network Plugin Functionality • Providing available sensor sets • Getting bandwidth information • Discovery sensors • Using service discovery protocol • Ex. SDP, SLP • Configure sensors • Data transmission rate • Sensor power on&off • Setting of different sleep states • Specifying the role of each sensors in multihop networks Wireless Sensor Networks: Winter 2006-07

  15. Computing Sets State Based Variable Requirements graph Network Feasible Set App. Feasible Set Overall Set Trade off computation Wireless Sensor Networks: Winter 2006-07

  16. State-based Variable Requirement graph Wireless Sensor Networks: Winter 2006-07

  17. Application Feasible Set FA • Multiple set of sensors, which can provide application QoS at a given state, can be derived from the state-based variable requirement graph and the sensor QoS graph • A patient state • medium stress • high heart rate, normal respiratory rate, and low blood pressure Wireless Sensor Networks: Winter 2006-07

  18. Network Feasible Set FN Network Feasible Set • Network plugin’s job • The subsets of nodes that can be supported by the network • Suppose that the sensors and processors communicate using an IEEE 802.11a network • It can support overall throughput of nearly 11Mb/s • However, if multiple applications are running simultaneously on the network and the personal health monitor application can only utilize 100kb/s of the throughput, the network would not be able to support the transmission of data from the ECG sensor with either 3, 5, or 12 leads Wireless Sensor Networks: Winter 2006-07

  19. Overall Set F • F = FA∩ FN • Example of Overall set F • Suppose network can’t support ECG 3, 5 12 leads, since other applications are running simultaneously FA ∩ FN Overall Set F Application Feasible Set FA Wireless Sensor Networks: Winter 2006-07

  20. Conclusion A middleware for sensor network applications • Ease the application development task • Enable applications to affect the network and sensors themselves • Tight coupling between the needs of the application and the management of the network • Separate the policy (obtained from the application) and the mechanism (performed in the middleware) Wireless Sensor Networks: Winter 2006-07

  21. Critique Strong Points • Application QoS requirement is actively reflected in the network and sensors • Middleware control sensor network directly • Application QoS is specified at each different states of monitored objects Weak Points • MiLAN approach is not appropriate when there are a lot of sensors • MiLAN should know a lot of information about each sensors • Available energy, role of each sensor, network connectivity, etc. • They didn’t present enough explanation about mechanism in detail • How to choose an element among overall set F Wireless Sensor Networks: Winter 2006-07

  22. MiLAN Development MILAN v0.9 Beta • Early Spring 2003 • Documentation MILAN v1.0 • Early Fall 2003 • Extensibility toolkit (beta version) • Additional simulators, hardware platforms etc. • Tutorials MILAN v1.1 • Early Summer 2004 • Service release • Additional simulator integration as needed • Full scale demonstration Wireless Sensor Networks: Winter 2006-07

  23. References • A. Murphy and W. Heinzelman, "Milan: Middleware linking applications and networks," TR-795, University of Rochester, Computer Science, November 2002. • WB Heinzelman, AL Murphy, HS Carvalho, and MA Perillo. Middleware to support sensor network applications. IEEE Network Mag., 18(1):6--14, 2004. • MiLAN: Middleware to Support Sensor Network Applications • Kyungmin Cho,Network Computing Lab., KAIST Wireless Sensor Networks: Winter 2006-07

  24. Thank youQuestions ? Wireless Sensor Networks: Winter 2006-07

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