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This paper presents a distributed algorithm designed to guide user navigation within adaptive sensor networks. The proposed solution employs multiple protocols to compute potential fields, determine the safest pathways, and direct user movements while considering danger zones detected by the sensors. Implementation issues and experimental results validate the efficacy of the approach, demonstrating clear paths with the largest safe clearance from identified dangers. The work advances the field of adaptive information systems, enhancing the functionality of a vast number of small sensors with limited capabilities.
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Distributed Algorithms for Guiding Navigation across aSensor Network Qun Li, Michael De Rosa, and Daniela Rus Mobicom 2003
Outline • Introduction • A distributed algorithm for guiding the navigation of a user • Implementation Issues • Experiments • Conclusion
Introduction • To create more versatile information systems • Adaptive distributed sensor networks • Hundreds of small sensors • Some limited memory and processing capabilities • Communication capabilities • Multiple sensing capabilities • To guide the movement of a user • Human • Robot
Introduction (cont.) • Danger detected by the sensors • Danger zone • Safest path • With the largest clearance of the danger zones
Danger zone Danger zone Introduction (cont.) Goal Sensor network
A distributed algorithm for guiding the navigation of a user • Algorithm 1 • The potential field computation protocol • Pot(i ) • Pot(i)= 1 / hop(j)2 , j : danger • Algorithm 2 • The safest path to goal computation protocol • Algorithm 3 • The navigation guiding protocol
A distributed algorithm for guiding the navigation of a user (cont.)
A distributed algorithm for guiding the navigation of a user (cont.)
A distributed algorithm for guiding the navigation of a user (cont.)
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 1 F Message(A, 1,) B H G A A C D Pot(b)=1 E Pot(B)= 1 / 12 = 1
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 1 F Message (A, 2) B H G A A C D Pot(b)=1 Pot(c)=0.25 E Pot(C)= 1 / 22 = 0.25
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 1 F Message (D, 1) B H G A A C D Pot(b)= 1+0.25=1.25 Pot(c)=0.25+1=1.25 E
(Goal ID, My ID, hops, potential) M, M, 0, 0 A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 2 Goal 0.1511 0.125 1.0204 0.2777 0.1511 A E I M Q Danger zone 1.04 0.3125 0.2222 0.3125 B F J N R 0.3125 1.04 0.3125 0.2222 1.04 C G K O S 0.3125 0.2222 0.3125 1.04 D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) (Goal ID, My ID, hops, potential) • Algorithm 2 M, M, 0, 0 Goal 0.1511 0.125 1.0204 0.2777 0.1511 A E I M Q Danger zone 1.04 0.3125 0.2222 0.3125 B F J N R 0.3125 1.04 0.3125 0.2222 1.04 C G K O S 0.3125 0.2222 0.3125 1.04 D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) (Goal ID, My ID, hops, potential) • Algorithm 2 M, M, 0, 0 Goal 0.1511 0.125 1.0204 0.2777 0.1511 A E I M Q M, I, 1, 0.1511 Danger zone 1.04 0.3125 0.2222 0.3125 B F J N R M, N, 1, 0.222 0.3125 1.04 0.3125 0.2222 1.04 C G K O S 0.3125 0.2222 0.3125 1.04 D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) (Goal ID, My ID, hops, potential) • Algorithm 2 M, M, 0, 0 Goal 0.1511 0.125 1.0204 0.2777 0.1511 A E I M Q Danger zone 1.04 0.3125 0.2222 0.3125 B F J N R 0.3125 1.04 0.3125 0.2222 1.04 C G K O S 0.3125 0.2222 0.3125 1.04 D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 3 Goal A E I M Q Danger zone B F J N R C G K O S {M} D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 3 Goal A E I M Q Danger zone B F J N R C G K O S {M, G, 3, 0.6858, K } {M, L, 3, 0.6858, K } {M, H, 5, 1.2205, H} D H L P T Danger zone
A distributed algorithm for guiding the navigation of a user (cont.) • Algorithm 3 Goal A E I M Q Danger zone B F J N R C G K O S D H L P T Danger zone
Implementation Issues • Only choice high frequency link (1/5) • Wait some time to reduced broadcast • Random waiting time
Experiments • Mote MOT300 sensor
Experiments(cont.) 7 X 7 grid network hops
Experiments(cont.) Eight different Network topologies 54 experiments worst average optimal
Experiments(cont.) Danger zone goal
Experiments(cont.) Near obstacle Near source
Conclusion • Using the sensor network to guide the movement of a user • Danger zones • Safe path