Multiple-UUV Approach for Enhancing Connectivity in Underwater - PowerPoint PPT Presentation

Multiple-UUV Approach for Enhancing Connectivity in Underwater Ad-hoc Sensor Networks Winston Seah Institute for Infocomm Research, Singapore winston@i2r.a-star.edu.sg http://www1.i2r.a-star.edu.sg/~winston

Outline • Introduction & Research Aim • Reference Architecture • Research Issues – Identification of communication gaps – Searching of communication gaps – Bridging communication gaps • Simulation Results and Analysis • Conclusion 2

Underwater Ad-hoc Sensor Networks • Large scale deployment for data collection, monitoring and surveillance • Adverse environment – Ambient noise – Multipath and fading effects – Temporal variations in channel • Acoustic communication – Low bit rates – Long and variable propagation delays 3

Research Aim • To improve network connectivity by bridging temporal disconnections – Using cooperative robotics approach – Relies on cooperation between mobile (robot) and static sensor nodes • Hop count information • Clustering information • For post-deployment topology optimization 4

Reference Architecture • Underwater collection points or sinks – Deployed at the corner/boundary of the interested area • Sensor nodes: – Deployed in the area of interest – Communicate via multi-hop acoustic links to send data to collection points or sinks – Clustering and localization – Use simple ALOHA protocol for medium access • UUV: – Transmission equipment – Mission sensors (e.g., actuators) – Motion sensors (e.g., sonar) – A payload of sensor nodes that can be deployed 5

Reference Architecture (2) optical fibre sink S 3 monitoring centre S 2 C 4 C 3 C 5 C 2 UUV C 0 S 1 S 0 cluster C 1 6

Reference Architecture (3) • UUV – Directional antenna (distance/orientation) – Mission sensors – Motion sensors – Payload of static nodes to be dropped 2 3 front rear 4 1 6 5 7

Research Issues • Identification of critical communication gaps in underwater ad-hoc sensor networks • Search algorithm to find the critical communication gaps • Methodology to bridge the communication gaps 8

Identification of Communication Gaps • Related work – Clustering by ID – [Corke et al, 2004] • Pros: simple and complete • Cons: overhead, information only used for gap identification, scalability issues • Our approach – by hop count (HC) – Each static node calculates its HC to sinks – Each static node broadcast this HC – A robot can detect communication gaps by receiving and analyzing the received static HC information 9

Propagation of Hop Counts 5 5 3 5 4 5 3 3 4 2 5 2 1 3 4 S 0 2 1 3 *only hop counts to sink S 0 are shown 10

Detection/Analysis of Neighbors’ HC Information S 3 S 2 E (11,11,7,4) D (16,13,6,16) (12,12,6,5) (10,10,8,3) (10,10,10,3) X F (9,9,9,3) Y C Z S 0 S 1 11

Searching of Communication Gaps • Exploration • Related work – With mapping – [Yamauchi, 1998] • Pros: complete • Con: complex and difficult, not scalable, expensive, not applicable – Without mapping – [Bandyopadhyay et al, 2005] • Pros: simple and scalable • Cons: cannot guarantee 100% coverage • Our approach – without mapping or with minimal mapping – Predefined searching (need simple map and rough location info) – Perimeter searching (no mapping, need clustering info) – Swarm intelligence (no mapping) – Advanced Potential field based searching (no mapping) 12

Predefined Searching • Needs map and location information • Pros: complete • Cons: not optimal Reference Node UUV Static Node 13

Perimeter Searching • Search around the boundary of clusters • Pros: more promising to find inter-cluster gaps suitable for non-uniform networks; • Cons: requires a clustering algorithm 14

Advanced Potential Field Based Search Searching ( Swarm Intelligence) • Potential Field Based Search - Disperse UUVs in the environment with obstacle avoidance capabilities – Virtual repulsive force among UUVs – Virtual repulsive force between UUV and obstacles – Virtual attractive force to let UUVs move • Multi-Robots collaboration – broadcast headings � neighboring robots choose different orientation • Pros: simple and scalable • Cons: low level cooperation 16

Bridging Communication Gaps • If link is disconnected temporarily, the UUV will move away when the connectivity is restored • If the disconnection is permanent, the UUV can: – Deploy sensor from its carried payload to bridge the gap; or – Remain as a bridge (or move away, depending on decision made at the monitoring centre) 18

Performance Evaluation • Connectivity � number of nodes that are connected to at least one sink • Average hop count � average hop count of each nodes to a sink • k -connectivity � average number of sinks that nodes are connected to, where 0 ≤ k ≤ n ( n =4 in our simulation studies) 19

Simulation Environment • Simulator – Qualnet � network simulator (packet loss, delay, …) – Player/Stage � robotics simulator (sensor/actuator error, …) – Semaphore � synchronize Qualnet and Player/Stage • Size of network � 2.5 km × 2.5 km • Number of sinks � 4 (at four corners) • Number of static nodes initially � 80 • Robots � 4 • Static nodes to be dropped � 20 • Transmission range � 250 metres • MAC protocol � ALOHA (with no retransmissions) 20

Simulation Scenarios • Number of UUV � 1 (single-UUV) or 4 (multi-UUVs) • 2 scenarios: – Node failure � due to corrosion, energy depletion, etc.. And may lead to network partitions – Intermittent link failure � common phenomenon in underwater environments 21

Simulation Results – Node Failure k-connectivity (multi-UUVs) connectivity (multi-UUVs) 80 2 static APFS avg k-connectivity connected nodes 60 1.5 predefined perimeter 40 1 static APFS 0.5 20 predefined perimeter 0 0 1 3 5 7 9 11 13 15 1 3 5 7 9 11 13 15 time step time step hopcount (multi-UUVs) 30 static APFS 28 predefined avg hopcount perimeter 26 24 22 20 1 3 5 7 9 11 13 15 time step 22

Simulation Results –Link Failure connectivity (multi-UUVs) k-connectivity (multi-UUVs) 80 2 70 static avg k-connectivity connected nodes 60 APFS 1.5 predefined 50 perimeter 40 1 30 static 0.5 APFS 20 predefined 10 perimeter 0 0 1 3 5 7 9 11 13 15 1 3 5 7 9 11 13 15 time step time step hopcount (multi-UUVs) 30 28 avg hopcount 26 24 static 22 APFS predefined 20 perimeter 18 1 3 5 7 9 11 13 15 time step 23

Conclusion • Harsh environment and adverse underwater communication channels poses many challenges to deployment of sensor networks • Poor channel conditions can further deteriorate due to multipath fading and ambient noise • Use of multiple UUVs with collaborative search strategies can identify and bridge communication impairments in underwater sensor networks 24

References Corke, et. al., “Deployment and Connectivity Repair of a Sensor Net with a Flying Robot”, in Proceedings of the 9th International Symposium on Experimental Robotics 2004 (ISER04), Singapore, Jun 2004 Yamauchi, B., “Frontier-Based Exploration Using Multiple Robots”, in Proceedings of the Second International Conference on Autonomous Agents (Agents '98) , Minneapolis, MN, USA, 1998 Bandyopadhyay, T., Liu, Z., Ang, M. H. Jr., and Seah, W. K. G., “Visibility-based Exploration in Unknown Environment Containing Polygonal Obstacles”, in Proceedings of the 12th International Conference on Advanced Robotics (ICAR05) , 2005 25

Thank you http://www1.i2r.a-star.edu.sg/~winston http://www1.i2r.a-star.edu.sg/~winston 26