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Acc: Generic On-Demand Accelerations for Neighbor Discovery in Mobile Applications Desheng Zhang, Tian He, Yunhuai Liu, Yu Gu, Fan Ye, Raghu k. Ganti,

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Presentation on theme: "Acc: Generic On-Demand Accelerations for Neighbor Discovery in Mobile Applications Desheng Zhang, Tian He, Yunhuai Liu, Yu Gu, Fan Ye, Raghu k. Ganti,"— Presentation transcript:

1 Acc: Generic On-Demand Accelerations for Neighbor Discovery in Mobile Applications Desheng Zhang, Tian He, Yunhuai Liu, Yu Gu, Fan Ye, Raghu k. Ganti, Hui Lei Computer Science and Engineering, University of Minnesota, USA Third Research Institute of Ministry of Public Security, China Singapore University of Technology and Design, Singapore IBM T.J. Watson Research Center, USA 2012/11/26 Junction 1Study Group / Junction

2 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 2

3 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 3

4 Motivation For interactive mobile applications require a fast discovery of neighbor devices in a nearby region allow applications to effectively collaborate among participating devices 2012/11/264 Study Group / Junction

5 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 5

6 Common interaction patterns in mobile systems Talking. Two nodes meet, exchange data, and diverge. Docking. A mobile node discovers a static node situated at a rendezvous point Flocking. A group of nodes move together as a unit 2012/11/266 Study Group / Junction

7 Emerging class of low-power mobile sensing applications 7 Talking DockingFlocking [Liu04] [Choudury04,07] [Wark07] [Malinowski07] [Borriello04] [Huang05] [UP08] [Eisenman08] 2012/11/26 Study Group / Junction

8 Challenges To achieve a bounded discovery latency and energy efficiency 1. shorter discovery latency delay tolerant => mobile applications humans are involved Coordinate duty cycles of all devices in the network => personal devices 2. mobile applications on personal devices desire a fast discovery only when need => continuous discovery is need to maintain network connectivity in mobile environments 2012/11/268 Study Group / Junction

9 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 9

10 What is done in this paper? Propose Acc: serves as an on-demand generic discovery accelerating middleware support a wide range of discovery protocols with an arbitrary duty cycle pattern based on knowledge collected by an existing discovery scheme Leverages the discovery capabilities of neighbor devices Supporting both direct and indirect neighbor discoveries 2012/11/26 Study Group / Junction 10

11 achievements Acc-assisted schemes reduce the discovery latency by a maximum of 51.8% when consuming the same energy. Based on a 10 GB dataset of more than 15;000 taxis in a metropolitan area, Acc employed by taxi drivers is able to accelerate selection of a direction with fewer competing taxis and more potential passengers. 2012/11/26 Study Group / Junction 11

12 Outline Motivation Introduction Contributions Relative Works Disco Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 12

13 Relative Works probabilistic protocols Birthday Protocol [1], 2012/11/26 Study Group / Junction 13 [1] Birthday protocols for low energy deployment and flexible neighbor discovery in ad hoc wireless networks. M. J. McGlynn and S. A. Borbash. In MobiHoc01, assign different probabilities for sending, receiving, and sleeping in individual slots offer very good performance in the average discovery latency a unbounded worst-case discovery latency, which leads to a long tail on discovery probabilities for stationary networks, instead of mobile networks

14 Relative Works quorum-based discovery protocols [2] 2012/11/26 Study Group / Junction 14 [2] Power-saving protocols for ieee based multi-hop ad hoc networks. Y.-C. Tseng, C.-S. Hsu, and T.-Y. HsiehIn INFOCOM02 Listen during a row Transmit during a column Global agreement on duty cycle primarily proposed for stationary networks where energy is the most pressing concern, not mobility T L R t m m

15 Relative Works deterministic protocols DISCO [3], Based on the Chinese Remainder Theorem each device selects two prime numbers and generates its period independently based on these numbers 2012/11/26 Study Group / Junction 15 [3] Practical asynchronous neighbor discovery and rendezvous for mobile sensing applications. P. Dutta and D. Culler. In SenSys 08, 2008.

16 Real Implementation in DISCO 2012/11/26 Study Group / Junction 16 Node i is awake at times: 5, 10, 15, 20, 25, 30, 25, and 7, 14, 21, 28, 35 Node j is awake at times: 1, 6, 11, 16, 21, 26, 31, and 1, 8, 15, 22, 29, 36 Nodes i and j are both awake at 15, 22 Two primes per node ensures even if both nodes pick same primes, discovery will occur ijR t B/L/B O(11 ms) in Disco m m 21 15

17 Choice of primes and pairs greatly affects discovery latency 2012/11/26 Study Group / Junction 17 Birthday Unbalanced primes in asymmetric pairs show best latency (23,157), (29,67) Unbalanced primes in symmetric pairs show worst latency (23,157), (23,157) Balanced primes in symmetric pairs show average latency (37,43), (37,43) 5%

18 Outline Motivation Introduction Contributions Relative Works Design Scheme Preliminaries Design Goal Evaluation Conclusion 2012/11/26 Study Group / Junction 18

19 Outline Motivation Introduction Contributions Relative Works Design Scheme Preliminaries Design Goal Evaluation Conclusion 2012/11/26 Study Group / Junction 19

20 Preliminaries for Neighbor Discovery Each device choose one prime number corresponding to its duty cycle. Assume perfect alignment In practice, they do not require perfectly aligned and are robust to clock drift. 2012/11/26 Study Group / Junction 20

21 Practical Often Beats Theory 2012/11/26 Study Group / Junction 21 Theory Practice

22 A clock skew of ±50 ppm could result in a failure to rendezvous as expected at duty cycles below 1% 2012/11/26 Study Group / Junction 22 failed rendezvous slots overlap expected rendezvous failed rendezvous early rendezvous early rendezvous No clock skew is clock is fast js clock is fast

23 Outline Motivation Introduction Contributions Relative Works Design Scheme Preliminaries Design Goal Indirect Discovery: Temporal-Spatial Coverage Online Activation Scheduling Evaluation Conclusion 2012/11/26 Study Group / Junction 23

24 ACC Design Goal Energy is not the main concern any more Need fast response 2012/11/26 Study Group / Junction 24 More efficiently utilize the additional energy budget to accelerate the discovery process, compared to current designs with the same amount of energy. Disco:10% duty cycle Acc-Disco: 5% duty cycle allocated to Disco for bounded latency 5% duty cycle allocated to Acc for acceleration purpose

25 ACC DESIGN Turn on radio during this slot (1) at the beginning and the end of the slot: Sends a discovery message including its neighbor table Its duty cycles, IDs, duty cycles of its current known neighbor (2) S may receive similar discovery messages from previously unknown or known neighbors if they also become active in the same slots with S When the known neighbors will become active again in the future slots Help S to decide how to accelerate the discovery 2012/11/26 Study Group / Junction 25 Energy Efficient Discovery Mode On-demand Accelerating Discovery Mode

26 When an on-demand fast discovery is required S enters this mode to accelerate the discovery process with an additionally provided energy budget S will also become active during several additional slots to receive discovery messages Optimal for discovering more potential neighbors: (1) direct neighbor discovery by S itself (2) indirect neighbor discovery by Ss known neighboring devices 2012/11/26 Study Group / Junction 26 ACC DESIGN Energy Efficient Discovery Mode On-demand Accelerating Discovery Mode

27 Indirect Discovery 2012/11/26 Study Group / Junction 27 One of the key features of ACC

28 Which slots? Evaluate the effectiveness of all potential active slots Select a subset of active slots to maximize the discovery probability and reduce discovery latency Spatial –temporal coverage Temporal diversity how many slots a known neighbor is active even though S is not Spatial similarity How likely a neighbor of a known neighbor of S is also Ss neighbor 2012/11/26 Study Group / Junction 28

29 Temporal Diversity Between a pair of devices S and its know neighbor A Determined by the difference in active slot schedules between them. More difference, more likely that via A, S can early indirectly discover new neighbors 2012/11/26 Study Group / Junction 29 Provide limit information Provide more information The common active slot set of i and j from slot t 0 to t The total active slot set of i from slot t 0 to t

30 Spatial Similarity Between a pair of devices S and A Determined by the spatial closeness between them The closer A is to S, the larger the possibility that more common neighbors exist between them Maximize the possibility that the potential unknown neighbors forwarded by the know neighbors to S Attempts to activate S at slots where more known neighbors with larger spatial similarities become active 2012/11/26 Study Group / Junction 30 The #. Of common known neighbors of i and j The #. Of known neighbors to itself at slot t 0 Direct: Indirect:

31 Slot Gain Calculation Slot gain of slot t S can calculate slot 6s slot gain as follow: 2012/11/26 Study Group / Junction 31 The neighbor table of S at slot t 0 Provide temporal-spatial coverage for S to discover all its neighbors becoming active from slot t 0 to t The temporal-spatial coverage that a known neighbor i can provide for S

32 Outline Motivation Introduction Contributions Relative Works Design Scheme Preliminaries Design Goal Indirect Discovery: Temporal-Spatial Coverage Online Activation Scheduling Evaluation Conclusion 2012/11/26 Study Group / Junction 32

33 Online Activation Scheduling 2012/11/26 Study Group / Junction 33 Additional duty cycle for S performing discovery in some additional slots, e.g. 2/11 Neighborhood table in current slot t, updated from latest info collected during this active t Next original active slot t N ( S should not select additional active slots after t N (change) Original duty cycle: 1/11 B = 2/11 (2 additional slots)

34 Competitive Analysis of Scheduling Algorithm 2012/11/26 Study Group / Junction 34

35 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Testbed Evaluation Simulation Evaluation Crowd-Alert Application Conclusion 2012/11/26 Study Group / Junction 35

36 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Testbed Evaluation Simulation Evaluation Crowd-Alert Application Conclusion 2012/11/26 Study Group / Junction 36

37 Testbed Evaluation Integrate Acc with 2 state-of-the-art discovery protocol: DISCO and WiFlock 2012/11/26 Study Group / Junction TelosB sensor devices a 10 KB RAM soze on the TinyOS/Mote platform One-hop grid network A mobile toy car attached with another TelosB as a discovering device circle around the grid

38 Testbed Evaluation Setting Time slot length: 25ms Direct: Smaller slot -> faster discovery Too small ( the jitters introduced by TinyOS timer Indirect: bigger slot -> reduce collisions of messages more exchanges of neighbor tables Additional duty cycle budge B for Acc: 5% Original duty cycle: 5% 2012/11/26 Study Group / Junction 38

39 Comparison & Metrics 2012/11/26 Study Group / Junction 39 Run 40 slots (=1s) Log the # of neighbors it discovered so far Repeat 20 times

40 Percentage of Discoveries 80% (13s, 22s, 27s) Acc-Disco finishes the discovery process faster than Disco by 51.8% Consume the same energy Base-Disco selects active slots with more known neighbors becoming active 2012/11/26 Study Group / Junction 40

41 Number of Discovered Devices # of neighbors discovered in every 8s time window Acc-Disco discover the largest number of neighbor devices during the first 8s. Other versions discover relatively uniform numbers of devices over time 2012/11/26 Study Group / Junction 41

42 Impact of Duty Cycle 2012/11/26 Study Group / Junction 42

43 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Testbed Evaluation Simulation Evaluation Crowd-Alert Application Conclusion 2012/11/26 Study Group / Junction 43

44 Percentage of Discoveries 99% of neighbor (1000, 1600, 1700) slots 41.1% gain > Disco 37.5% gain > Base 2012/11/26 Study Group / Junction 44

45 Impact of Duty Cycle Duty cycle, average latency the performance gain between Acc and Disco 2012/11/26 Study Group / Junction 45 (380, 200, 140)

46 Impact of Device Density 2012/11/26 Study Group / Junction 46

47 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Testbed Evaluation Simulation Evaluation Crowd-Alert Application Conclusion 2012/11/26 Study Group / Junction 47

48 Crowd-Alert Application Taxi drivers can quickly navigate optimal directions to travel to maximize the possibility of picking up passengers (faster neighbor discovery) Smart phone app Navigate lower density of taxis High passenger density 2012/11/26 Study Group / Junction 48

49 Dataset 7 days GPS traces from more than 15,000 taxis Plate Number Date and time GPS Coordinates Availability Upload 30 sec 2012/11/26 Study Group / Junction 49 Location distribution of competing taxis (10s uploading time window at 5PM) Location distribution of served passengers (in 2 hr uploading window 4~6 PM) With passengers Without passengers Location passengers exit entering

50 Reduction of Discovery Latency Trace driven simulation With total duty cycle: 4/ /11/26 Study Group / Junction 50 22% gain Achieve half of discoveries Assist driver to more quickly drive to the optimal directions

51 Acceleration of Navigation Duty cycle: 4/30, communication radius: 30km (1) Navigating with Disco (2) Navigating with Acc-Disco (3) Navigating with Oracle Instantly know taxi distribution and passenger distribution (4) Ground truth without navigation Preference: fewer competing taxis or more served passengers Metrics Competing taxis density Served passengers density of taxis neighborhoods 2012/11/26 Study Group / Junction 51

52 Density of Competing Taxis (1) Only one smart taxi Oracle doesnt outperform Disco or Acc-Disco much Possible reason: in the Downtown area 2012/11/26 Study Group / Junction 52 No tendency toward consistent increase or decrease decrease Decrease 14% Decrease 20% 7.5% gain 12.6% gain

53 Density of Competing Taxis (2) 10% Smart Taxis More taxi used Achieve more uniform taxis distribution 2012/11/26 Study Group / Junction % 10.1%

54 Density of Served Passengers (2) 10% of Smart Taxis 2012/11/26 Study Group / Junction 54 All scheme increase Due to drivers experiences 13.2% gain 25.6% gain

55 Outline Motivation Introduction Contributions Relative Works Design Scheme Evaluation Conclusion 2012/11/26 Study Group / Junction 55

56 Conclusion Acc, an augmenting layer for the acceleration of neighbor discovery in existing discovery schemes Known neighbors can help a device learn unknown neighbors indirectly Online scheduling algorithm considering temporal diversity and spatial similarity Integrate Acc with 3 kinds of protocols 2012/11/26 Study Group / Junction 56


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