Collaboration of Mobile and Pervasive Devices for Embedded Networked Systems

1. Presented by: Su Jin Kim Collaboration of Mobile and Pervasive Devices for Embedded Networked Systems • Committee: Sandeep K. S. Gupta (Chair) Partha Dasgupta Hasan Davulcu Yann-Hang Lee

2. Outline • Introduction • Mobile Edge Computing Devices (MECD) • Mesh-Networked MECDs • Self-organizing Authentication for Embedded Networked Systems • Conclusion and Future Work

3. Embedded Networked System (ENS) Feature Technology Embedded Networked System (ENS) • ENS Architecture [1][2][3] • End nodes are embedded systems with wireless communication capability. • Gateways are capable of connecting end nodes to the external network. • Servers could access data remotely. • Collaboration of local gateways • Interaction is mostly local. • Local systems could detect same events (e.g. fire, earthquake). Save bandwidth and reduce delay. Collaboration Embedded System Context awareness Wireless Network Pervasive Computing Smart Service in everyday life Bandwidth and connectivity problem between gateways and servers End nodes

4. Research Challenges Research Issues ENS Characteristics • Large sized • Distributed and Autonomous • Mobile (high and unpredictable) • Resource limited • Heterogeneous • Scalability • End-to-end reliability • Local data processing • Efficiency • Energy, computation, and communication • Neighbor & Service discovery • Security • Authentication • Authorization (Access control) • Key management • Additional networks and works Gateway- level collaboration • Dynamic characteristic of gateway level networks Research Questions • Scalability • How to support additional networks of local gateways for a large sized network. • End-to-end reliability • How to ensure packet delivery between local and external networks within a certain delay. • Authentication • How to authenticate strangers without any knowledge.

5. Research Contributions

6. Outline • Introduction • Mobile Edge Computing Devices (MECD) • Mesh-Networked MECDs • Self-organizing Authentication for Embedded Networked Systems • Conclusion and Future Work

7. Scalability of Gateway and Related Work • Scalability Problem of Gateways in ENS • Interface for a large network • Collaboration between gateways • High and unpredictable mobility pattern • Hard to provide scalability to a huge number of mobile devices that have unpredictable mobility patterns.  Use a mobile gateway per object not per area Gateway Mobile Static Improve Connectivity Improve Lifetime

8. Hierarchical Network Structure with MECDs • Mobile Edge Computing Device (MECD) • Mobile gateway • Manage the internal network of a moving object in a distributed manner • Perform local data processing • Support collaboration with neighboring gateways • 3-level network of ENS • Reduce the amount of data • Reduce the remote communication • Separate the internal network from outside

9. Functional Architecture of MECD • Communication with • remote servers • Communication with • end nodes • neighboring MECDs Local Data Processing

10. Case Study: Intelligent Container Systems • Autonomous End-to-End monitoring system for cargo containers • Homeland Security • Global Supply Chain

11. Test-bed Configuration PDA: Monitors data from MECD, Setup variables 802.11 MECD: Data collection, Data reporting, Door Opening Detection, RFID reader Control, Datase Management 2.4 GHz Container Reader-mote module: Reads tag IDs and reports fresh readings MicaZ/TelosB mote(s): Report sensed data periodically

12. Deployment Supported by Mary Murphy-Hoye

13. Lessons Learned • Unreachability Problem • High temperature variance • High interference between metalic containers  Effect on connectivity between gateways

14. Outline • Introduction • Mobile Edge Computing Devices (MECD) • Mesh-Networked MECDs • Self-organizing Authentication for Embedded Networked Systems • Conclusion and Future Work

15. Lifecycle of Containers

16. Mesh Network • Multi-hop • Reliability • Self-healing • Self-organizing • More extensive range A B • Requirements of Mesh-networked MECDs • Server reachability • Low delay • Energy efficiency

17. Simulation Setup • International Standards Organization (ISO) Container Size • Common width for international commerce = 8 ft. (2.44 m) • Common height = 8.5 (2.6 m) • Length: 20 ft. – 53 ft. • Common lengths = 20 ft. (6.1 m), 40 ft. (12.2 m), 48 ft. (14.6 m), 53 ft. (16.2 m) Forwarder • Temperature, T • 25C ≤ T ≤ 65C • Containers stack • – Up to 6 in height • – 1 ft distance

18. Metrics • Connectivity (Ci) • Ci= 1, If there is a path between MECD i and the forwarder. • Ci = 0, If not. • Sever Reachability (SR) (S is the set of MECDs in the network) • Network Latency • Average path length that is defined as the average number of hops along the shortest paths between the forwarder and all other MECDs in the network • Energy Efficiency • Total energy consumption when every node sends a packet to the forwarder via its shortest path.

19. Simulation Model: Communication Model • Received power (Log-distance Path Loss) [4] • Temperature Loss [5] • Maximum Transmission Range [5] Distance Zero-mean normally distributed random variable with standard deviation σ Received Power at the refence distance d0 Path loss exponent d0 = 1m np = 3.3 Pr(0)= -45dBm σ= 3dBm Ps = -94 dBm Temperature, 25C ≤ T ≤ 65C Radio Sensitivity

20. Simulation Model: Energy Consumption Model • First-order Radio Model [6] • Energy Consumption to transmit a k-bit packet to a distance d • Energy Consumption to receive a k-bit packet • Total Energy Consumption to transmit a k-bit packet over n hops Energy loss at distance d Energy consumption to run the transmitter circuitry for a k-bit packet Energy consumption by transmitting amplifier Energy consumption by transmitting amplifier to transmite k bits to distance d Energy consumption to run the transmitter circuitry Eelec = 50nJ/bit amp = 100pJ/bit/m2 k = 20 bits, d = 50m Energy consumption to run receiver circuitry for a k-bit packet

21. Server Reachability vs Network Density vs Temperature • MECD-level network can provide 100% server reachability for ISO standard containers within the range 25 C ≤ T ≤ 65 C. ISO standard container lengths with 1 ft. space are less than 16.5 m.

22. Path length vs Network Size vs Temperature • The MECD-level network will produce a small amount of additional delays and is scalable to a large size of MECD networks (a) T = 25 C (b) T = 45 C (c) T = 65 C

23. Energy Consumption vs Network Size vs Temperature • The MECD-level network will consume a small amount of additional power and is scalable to a large size of MECD networks (a) T = 25 C (b) T = 45 C (c) T = 65 C

24. Outline • Introduction • Mobile Edge Computing Devices (MECD) • Mesh-Networked MECDs • Self-organizing Authentication for Embedded Networked Systems • Conclusion and Future Work

25. Authentication • Collaboration among neighboring MECDs • Wireless communication • Sharing information and resources • Authentication • The process to prove a user’s claimed identity. • Required before granting access

26. Related Work Interact with the environment and use contextual information • Requirement of authentication process for MECD-level networks • Mutually unknown MECDs must verify each other’s claim without any knowledge. Authentication Context-aware Traditional Biometric Pre-shared Secret Trusted-Third Party Location-based Require securely pre-established information

27. Location-based authentication • The process to authenticate a user by detecting his presence at a distinct location • Trust relationship is based on a user’s current location • Localization Approach • Absolute location • Distance bounding • In-region

28. Problem Definition & Assumptions • Self-organizing Region-based Authentication • A verifierv authenticates a requesterr when they are in a region R of interest. • Without human’s help, pre-shared information, and pre-established trust relationship. • R: the region (e.g., a room, a house, a ship, or a yard) • Trust-relationship • An entity’s presence of the region, R. • Assumptions • R must have some sort of physical control to restrict people into this area. • v and r are well-synchronized. • Threat model • Active adversaries – capture, replay, and insert • Passive adversaries - eavesdrop • Denial of Service attacks (DoS) not considered • an attempt to make a computer resource unavailable to its intended users

29. Acoustic Feature Based Approach • Challenges • Distinguish the region • Detecting the leave and closing the granted access • Approach • Acoustic feature based technique using environmental sound • Environmental sound is produced by random events in any physical location. • Devices within a particular region hear similar environmental sound. • A microphone is cheap. Recording Feature Extraction Feature Exchange Verification

30. Acoustic Feature Extraction Techniques • Time-domain (temporal) feature extraction • Simple to implement. Requires highly well synchronized devices. • Frequency-domain (spectral) feature extraction • Relatively expensive. Relax synchronization requirement. • Hybrid feature extraction • Split into several windows and perform frequency-domain feature extraction. • Requirements • Distinctiveness of locating • Randomness and Timevariance

31. Correlation • Recorded sounds in 4 different environments • Café • Classroom • House • Office • Correlation coefficient • Measure the similarity of two frequency domain signals with different length of FFT functions. • Definition: Co-located devices • Devices within the same region

32. Correlation with 256-point FFT (a) Cafe (b) Classroom (d) Office (c) House

33. Distinctiveness vs Cost of FFT functions • Percentage of overlapping between two case: correlation of co-located and not co-located devices • Specifications • Computation and Energy Cost [7] [8] [9] [10] [11] [9]

34. Acoustic Feature Extraction Recording • A requester sends the request. • A verifier sends a random number, n. • Both devices start recording and feature extraction steps. • The requester sends the feature set to the verifier. • The verifier performs the verification step. 1 2 3 . . . w Windowing FFT Feature Extraction Caculating the peak of each window P1 P2 P3 ….. Pw Hash H(P1| n) mod l H(P2| n) mod l …. H(Pw | n) mod l Bloom Filter 0 1 0 0 1 0 0 0 0 ….. 0 0 1 0

35. Verification Features received from the requester 0 1 0 0 1 0 0 0 0 ….. 0 0 1 0 Not matched Matched Matched Features extracted locally 0 1 0 0 0 0 0 1 0 ….. 0 0 1 0 At least t % of features match? Yes Authenticated No Reject

36. Data Collection • Implemented on Google Android Dev 1 phones. • Deployed at a room. • Distinctiveness Evaluation • False Positive Rate (FPR): the error rate of failing to reject authentication when it is in fact false • False Negative Rate (FNP): the error rate of rejecting authentication when it is actually true • To be completely distinguishable against attacks out of the region, • False positive rate must be 0. • False positive rate ≠ 0, a system is vulnerable. • False negative rate ≠ 0, re-trial can be used. 10 m 20 m 30 m

37. Experimental Results • With t ≥40%, the complete dinstincitiveness can achieved within a small region. • Security Analysis • Replay attack: The random number, n, is generated by the verifier and used for a feature set. Therefore, an attacker can not reuse any valid feature set from the previous communications. • Guessing: To represent the 128-bit output of the MD-5 hash function in a filter, the length can be 128-bit. With the longer bits of the feature set, it is hard to guess a valid set. (a) w=10 (b) w=6

38. Outline • Introduction • Mobile Edge Computing Devices (MECD) • Mesh-Networked MECDs • Self-organizing Authentication for Embedded Networked Systems • Conclusion and Future Work

39. Conclusion and Future Work • Conclusion • Collaboration among gateways is a key component to save bandwidth and reduce delay for the remote communication by sharing information locally. • A mesh networking approach of MECDs improves the connectivity with the remote server. • For an intelligent container scenairo, using mesh networked MECDs can solve reachability problem completely with small additional delay and energy consumption with the range of temperature, 25 – 65 °C. • The acoustic feature based technique is feasible for self-organizing region-based authentication within a small region. • With threshold of 40%, it provides 0.1 FNR for 10m and 0.4 FNR for 20m approximately for a smart home scenario. • Future Work • Power management for mobile gateways of ENS • Mesh-networked MECDs • Mesh network management for general USN • Self-organizing region-based authentication • Improve distinctiveness: multiple contextual information (e.g. temp, light, wifi) • Extend for heterogeneous devices in ENS

40. References [1] S. Fukunaga, T. Tagawa, K. Fukui, K. Tanimoto, and H. Kanno., “Development of Ubiquitous Sensor Network, Oki Technical Review,” Vol. 71, No. 4, Oct. 2004. [2] ITU-T Technology Watch Briefing Report Series, No. 4., “Ubiquitous Sensor Networks,” http://www.itu.int/dms\_pub/itu-t/oth/23/01/T23010000040001PDFE.pdf [3] M. Kim, Y. Lee1, and J. Ryou, “What are Possible Security Threats in Ubiquitous Sensor Network Environment?,” In Proc. of Asia-Pacific Network Operations and Management Symposium (APNOMS 2007), LNCS4773, pp. 437-446, 2007. [4] Randy H. Katz, “Radio propagation,” http://www.sss-mag.com/pdf/1propagation.pdf [5] K. Bannister, G. Giorgetti, and S. K. S. Gupta, “Wireless Sensor Networking for Hot Applications: Effects of Temperature on Signal Strength, Data Collection and Localization,” In Proc. of the 5th Workshop on Embedded Networked Sensors (HotEmNets)}, Jun. 2008. [6] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Eenergy-effieicnt communication protocol for wireless microsensor networks,” In Proc. of the 33rd Hawaii Int'l Conf, on System Science, Vol. 8, pp. 8020-8029, 2000. [7] CrossBow, “Mica2 Datasheet,” https://www.eol.ucar.edu/rtf/facilities/isa/internal/CrossBow/DataSheets/mica2.pdf [8] CrossBow, “CrossBow TelosB 2.4GHz datasheet,” http://www.willow.co.uk/TelosB\_Datasheet.pdf [9] Shah Bhatti, James Carlson, Hui Dai, Jing Deng, Jeff Rose, Anmol Sheth, Brian Shucker, Charles Gruenwald, Adam Torgerson, and Richard Han, “MANTIS OS: An Embedded Multithreaded Operating System for Wireless Micro Sensor Platforms,” In ACM/Kluwer Mobile Networks \& Applications (MONET) Journal, Special Issue on Wireless Sensor Networks, August 2005. [10] Robert M. Newman and Elena Gaura, “Size does matter - the case for big motes,” In Proc. of the 2006 NSTI Nanotechnology Conference and Trade Show (Nanotech 2006), May 2006. [11] K. Venkatasubramanian, A. Banerjee, S. K. S. Gupta, “Green and Sustainable Cyber Physical Security Solutions for Body Area Networks,” In Proceedings of 6th Workshop on Body Sensor Networks (BSN'09), Berkeley, CA, June 2009.

41. Thank you!Questions? Impact Lab (http://impact.asu.edu)

42. Backup Slides

43. Related publications • Su Jin Kim, and Sandeep K. S. Gupta, “Design and Implementation of Monitoring Systems using Networked Mobile Edge Computing Devices for Ubiquitous Sensor Networks,” IEEE Trans. on Consumer Electronics, Under review. • Su Jin Kim, and Sandeep K. S. Gupta, “Audio-based Self-organizing Authentication for Pervasive Computing: a Cyber-Physical Approach,” The 2nd Int’l Workshop on Next Generation of Wireless and Mobile Networks (NGWMN’09), Vienna, Austria, 2009. • Su Jin Kim, Guofeng Deng, Sandeep K. S. Gupta and Mary Murphy-Hoye, “Enhancing Cargo Container Security during Transportation: A Mesh Networking Based Approach,” 2008 IEEE Int’l Conf. on Technologies for Homeland Security (HST'08), Waltham, MA, USA, April 2008. • Su Jin Kim, Guofeng Deng, Sandeep K. S. Gupta and Mary Murphy-Hoye, “Intelligent Networked Containers for Enhancing Global Supply Chain Security and Enabling New Commercial Value,” The 3rd Int'l Conf. on Communication System Software and Middleware (COMSWARE'08), Bangalore, India, 2008.

44. Functional Requirements of Smart Containers

45. Prototype Implementation of MECD Stargate USB Memory Card MICAz mote 2.4 GHz USB 51-pin Stargate (Gateway) Ethernet • Crossbow Stargate Gateway • Single-board embedded Linux computing designed for sensor networking applications • Low-power device • Various interfaces RS232 PCMCIA Compact Flash 802.11 Compact Flash card

46. RFID Reader-Mote Implementation Reader-Mote MICAz mote 2.4 GHz • SkyeTek M9 UHF RFID eader • Small form factor, cost-efficient, energy-efficient and high-performance RFID reader • Converter • Two-way communications • Voltage conversion between the M9 reader (5V) and MicaZ mote (3V) Converter UART RS232 M9 UHF RFID Reader

47. GUI implementation

48. Software Components and Data Flow

49. Experimental Study: RFID Read Ranges • According to the SkyeTek document, a M9 UHF RFID reader can approximately read 138 inches with the maximum output power (27 dBm). However, the average read ranges by our experiments are much smaller. • In Singapore and Taiwan, the government regulation of output power level is 0.5 watts ERP. In this case, the RFID read range is 10-18 inches.

50. Experimental Study: Lifetime of MicaZ motes • MicaZ mote with MTS310 Sensor board • Broadcasts a packet every 10 sec with its voltage level • Uses the power saving mode (switching off radio and sensor board after readings) • 2 new AA batteries • The base station (4 meters away) collects packets • The mote lasts about 46 days 46 days