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Hao Ji, Lei Xie, Yafeng Yin, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China Presenter: Dr. Lei Xie, Associate.

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Presentation on theme: "Hao Ji, Lei Xie, Yafeng Yin, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China Presenter: Dr. Lei Xie, Associate."— Presentation transcript:

1 Hao Ji, Lei Xie, Yafeng Yin, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China Presenter: Dr. Lei Xie, Associate Professor An Efficient Indoor Navigation Scheme Using RFID-based Delay Tolerant Network GLOBECOM 2013

2 Outline

3 MotivationEvaluationRelated WorksProblem DescriptionOur Solutions 1 Mobile Indoor Navigation Is Necessary Although now people have several ways to communicate with each other, finding a mobile target (e.g., children, puppies) in a public place, such as in a supermarket, theme park, or shopping mall, can be difficult. How to locate and navigate to a mobile target

4 Indoor localization Technology EvaluationRelated WorksProblem DescriptionOur Solutions 2 Motivation Wireless/Radio Signal The active badge location system ACM Transactions on Information System, pp. 91–102, Design and Evaluation of a Wireless Magnetic-based Proximity Detection Platform for Indoor Applications ACM/IEEE IPSN 2012, MSRA Magnetic RFID Mining Frequent Trajectory Patterns for Activity Monitoring Using Radio Frequency Tag Arrays IEEE Transactions on Parallel and Distributed Systems (TPDS), (RFID) Wi-Fi Wifi localization and navigation for autonomous indoor mobile robots International Conference on Robotics and Automation (ICRA), pp , Bluetooth Ultrasonic Infrared Providing location based information/advertising for existing mobile phone users Personal and Ubiquitous Computing, pp. 3–10, The cricket location-support system MobiCom, pp. 32–43, Smartphone Did you see Bob?: human localization using mobile phones. ACM MobiCom 2010 , Duke University. Computer Vision (CV) Precise Positioning Proximity Detection

5 Challenges for Indoor Localization EvaluationProblem DescriptionOur Solutions 3 Motivation Magnetic RFIDWi-FiBluetooth UltrasonicInfrared Accuracy & Transmission & Identification Accuracy of positioning Transmission Capability Identification Capability Related Works

6 Design and Evaluation of a Wireless Magnetic-based Proximity Detection Platform for Indoor Applications ACM/IEEE IPSN 2012, MSRA 4 EvaluationRelated WorksProblem DescriptionOur SolutionsMotivation Wireless Proximity Detection based on Magnetic Induction Deploying inside a large food court to offer context-aware and personalized advertisements and diet suggestions at a per-counter granularity.

7 Did you see Bob?: human localization using mobile phones. ACM MobiCom 2010 , Duke University. C(t) B(t) T_AC T_BC ) B(t) ) C(t) 5 EvaluationRelated WorksProblem DescriptionOur SolutionsMotivation Using mobile phone sensors and opportunistic user-intersections to develop an indoor navigation system.

8 Compare With Actual Situation Centralized System Architecture There is centralized server in the system. The Position of the Target Is Stationery Position of the target is stationery on the map. Direct Communication Ability with the Centralized Server Each client directly reports its location info to server whenever possible. 6 EvaluationRelated WorksProblem DescriptionOur SolutionsMotivation Traditional Indoor Navigation System Actual Situation  Distributed System Architecture  The Position of the Mobile Target Is Continuously Changing.  No Direct Communication among Clients.  Sufficiently Reduce the Cost of Deployment and Hardware.

9 Deploying RFID TAGs as a Delay Tolerant Network EvaluationRelated WorksProblem DescriptionOur Solutions 7 Motivation Low Cost Noncontact Identification Storage Capacity Massively Deployed RFID tags are deployed on key locations Entrances of building Door of office room, meeting room and washing room Corners of corridor, elevators etc

10 Problem Description EvaluationRelated WorksProblem DescriptionOur Solutions 8 Motivation Whenever client pass by a location sensing device, the location info can be recorded locally. There is no centralized server in the system. Navigation To A Moving Target User In Indoor Environment. Client need not to have long distance communication ability.

11 Location Info——Event Message EvaluationRelated WorksProblem DescriptionOur Solutions 9 Motivation When a user passes by a RFID tag, an event message will be left on the tag. A location1 Event was written to this tag. Which means “user A pass by location1 at time1” Two components in the system: Location sensing devices(like RFID tags)----stationary Users----mobile

12 A B Location Info(Event) can be spread by other users. Spread of Event Message EvaluationRelated WorksProblem DescriptionOur Solutions 10 Motivation User B carried user A’s location info to loc4’ and loc5’

13 Request Info——Request Message EvaluationRelated WorksProblem DescriptionOur Solutions 11 Motivation When a user A wants to find user B. A Request R was written to this tag. Which means “please help user A to find user B”

14 Spread of Request Message EvaluationRelated WorksProblem DescriptionOur Solutions 12 Motivation User A wants to find user B, if another user C is also in the system. A R C B User C brought user A’s request R more places

15 Two Kinds of Messages EvaluationRelated WorksProblem DescriptionOur Solutions 13 Motivation Event Message: Request Message: “I was once here” “Please help me to find T”

16 S Req H T Req User S want to find user T User H carried user T’s location info to user S

17 EvaluationRelated WorksProblem DescriptionOur Solutions 14 Motivation Navigation Scheme Normal Mode: Transmit his own “check-in” to surrounding location sensing devices. Collect other users’ “check-in” from surrounding location sensing devices. Collect surrounding “request”. Process collected requests. Searcher Mode: Transmit “request” to surrounding location sensing devices. Transmit his own “check-in” to surrounding location sensing devices. Collect other users’ “check-in” from surrounding location sensing devices. Collect surrounding “request”. Process collected requests. Use collected targets’ “check-in” info to make path decision. Crowdsourcing

18 Management of Storage Resource EvaluationRelated WorksProblem DescriptionOur Solutions 15 Motivation The memory size of RFID tag is limited, So we should make full use of these storage resources. Under the navigation framework, post operation will write messages to tags. Therefore, a reasonable writing and replacing strategy should be used.

19 Each Tag maintains at most λ event messages of each user H i. Each Tag maintains at most one request message of searcher S and target T. When a helper passes by a vertex, he will post messages to the vertex with a posting probability p. when new event message arrive, will be removed. FIFO empty 123 Memory space of Tag Example posting probability p = 1/3

20 Navigation Algorithm EvaluationRelated WorksProblem DescriptionOur Solutions 16 Motivation When searcher S has collected more than one event messages of the target T, how to use these event message to calculate the current position of target T?

21 We use a target region rather than a single point. Target region EvaluationRelated WorksProblem DescriptionOur Solutions 17 Motivation A simple way to do this is selecting the neighbor vertex which is nearest to the latest appearance location of the target. Three reasons: The location with latest timestamp may be far away. There should be a tradeoff between the timestamp of the trace and distance. The target is a moving object whose motion is a continuous process. The movement behavior of the target has locality in the real world.

22 Pre-calculate the distance matrix Calculate the distance weight Calculate distance cost function Navigation Algorithm

23 1. We select the top 3 timestamp event message location as the target region. Example S 2. Calculate the weighted distance according to event message’s timestamp. 3. Select the minimum cost neighbor.

24 Evaluation Experiment Settings 30 X 30 grid-graph Length of each edge is 4m Movement speed of the searcher is 2m/s, other user’s are 1m/s For all figures presented, we run the simulation 1,000 times to get average values. Evaluation Related WorksProblem DescriptionOur Solutions 18 Motivation

25 Evaluation To Simulate The Mobility of Human Beings  Random Walk Mobility Model(RW)  Random Way-Point Mobility Model(RWP) the radius of the circle obeys a normal distribution the stay time of each user obeys a truncated power-law distribution EvaluationRelated WorksProblem DescriptionOur Solutions 19 Motivation

26 Evaluation More users means more helpers for the searcher EvaluationRelated WorksProblem DescriptionOur Solutions 20 Motivation Smaller average searching time

27 Evaluation Related WorksProblem DescriptionOur Solutions 21 Motivation The larger time to live of request message is, the smaller average searching time is. Too small request TTL means fewer helper will “see” it.

28 Evaluation Related WorksProblem DescriptionOur Solutions 22 Motivation Average searching time and expectation of movement region radius does not satisfy the monotonic relation.

29 Evaluation Related WorksProblem DescriptionOur Solutions 23 Motivation The Number of Request message reduce with the increment of time.

30 Conclusion Related WorksProblem DescriptionOur Solutions 24 Motivation We propose a framework leveraging RFID-based delay tolerant network for localization and navigation. Store-and-forward of the DTN Crowdsourcing We propose a time-efficient scheme to locate and navigate to a mobile target who is continuously moving. The most possible region of the target

31 Thank you ! Questions ? GLOBECOM 2013


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