Crosslayer Packet Size Optimization for Wireless Terrestrial Underwater

Cross-layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks IEEE INFOCOM 2008 Mehmet C. Vuran and Ian F. Akyildiz Database Lab. Soo Hyung Kim

Contents Introduction p Related Work p Factors Affecting the Packet Size p Packet Size Optimization Framework p Optimization Results p Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Conclusion p Database Laboratory 2

Introduction p Traditional approach n Point-to-point link p n Successful and efficient transmission Cannot be captured multi-hop, broadcast nature serial cable, phone line Node Database Laboratory 3

Introduction p Multi-hop WSN n n n p Routes established Existence of neighbor nodes Wireless channel and error control technique Nature of WSN n n n Terrestrial areas Underwater (UW-ASN) Underground (WUSN) Database Laboratory 4

Introduction p Cross-layer solution for packet size optimization n p The effects of multi-hop routing The broadcast nature of the physical wireless channel The effects of error control techniques Three objective functions n n n Packet throughput Energy consumption Resource utilization Database Laboratory 5

Related Work p Voice Packet Size between UMTS-to-PSTN [1] n p Single hop communication Improving Wireless Link [2] n Variable packet size p p Properties of the wireless channel Energy efficiency [3] n n n Most relevant work Effects of error correction on energy efficiency Energy channel model is based on single hop Database Laboratory 6

Factors Affecting the Packet Size p Factors(focus on energy consumption) n Transmit a packet and Reliability of the network p Small packet size § increase reliability § inefficient transmission p Longer packet size § provide error resiliency § increased energy consumption n Collision p Longer packet size § increase the collision rate Database Laboratory 7

Factors Affecting the Packet Size p Carrier sense mechanism n n p Successful carrier sense No collision transmission Formulation(from [4]) Probability of successful carrier sense Probability of sensing the channel free Probability of no collision Overall traffic rate Database Laboratory 8

Factors Affecting the Packet Size p Total generated packet rate (pkts/s) n p p p b : average sampling rate Ld : packet payload i : node n n p M : number of nodes in the transmission rage n p MAC Failure rate Database Laboratory 9

Packet Size Optimization Framework p Three objective function n Packet throughput n Energy per useful bit n Resource utilization p p Database Laboratory Ld : payload length PER : end-to-end packet error rate T : end-to-end latency E : end-to-end energy consumption 10

Packet Size Optimization Framework p Channel-aware algorithm n p SNR ( ) n p Signal to noise ratio Medium access n p Determine next hop using SNR RTS-CTS-DATA exchange Error correction n n ACK and ARQ FEC code p (n, k, t) - n: block length, k: payload length, t: error correcting capability in bits Database Laboratory 11

Packet Size Optimization Framework p Channel model n Log-normal channel model [5] p p Database Laboratory 12

Packet Size Optimization Framework p End-to-End energy consumption [6] n n n Database Laboratory 13

Packet Size Optimization Framework p p Etx for ARQ and FEC p Similar approach for , Database Laboratory , , 14

Optimization Results p Energy consumption n n p Packet size SNR threshold Packet size optimization is affected by the routing decisions. Database Laboratory 15

Optimization Results Database Laboratory 16

Optimization Results p Using MATLAB Database Laboratory 17

Optimization Results p Very long packet sizes have problem [7] Database Laboratory 18

Optimization Results p Certain WSN application n n End-to-End latency Reliability constraints Database Laboratory 19

Optimization Results Database Laboratory 20

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Underwater Channel Model n Urick path loss formula [8] p n Signal level p n SNR of channel p n Bit error rate p where Database Laboratory 21

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Underwater Channel Model n 2 -path Rayleigh model Direct path signal p Surface reflected path signal p n Bit error rate p n Combination of these signals 2 -path Rayleigh model Not closed form expression for SNR distribution p Performed simulation to find these values p Database Laboratory 22

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Underground Channel Model [9] n n n 2 -path location-based Rayleigh fading channel model VWC(volumetric water content) of the soil Total path loss p n Bit error rate p n SNR p Database Laboratory 23

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Results n Three different optimization problems p n , , Underwater p Deep water network § Two-ray underwater channel model p Shallow water network § Reflections from the sea surface n Underground Channel model presented in previous page p Effects of volumetric water content(VWC) p Database Laboratory 24

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Deep Water Environment Database Laboratory 25

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Shallow Water Environment Database Laboratory 26

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Optimum Energy Consumption Database Laboratory 27

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Optimum Packet Throughput Database Laboratory 28

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Optimum Resource Utilization Database Laboratory 29

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Optimum Packet Size for Database Laboratory 30

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underwater Sensor Networks n Optimum Energy Consumption Database Laboratory 31

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underground Sensor Networks n Optimum Packet Size Database Laboratory 32

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underground Sensor Networks n Optimum Energy Consumption Database Laboratory 33

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underground Sensor Networks n Optimum Packet Size for Database Laboratory 34

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underground Sensor Networks n Optimum Energy Consumption Database Laboratory 35

Packet Size Optimization in Wireless Underwater and Underground Sensor Networks p Wireless Underground Sensor Networks n Optimum Packet Throughput Database Laboratory 36

Conclusion Packet size optimization for wireless terrestrial, underwater, and underground sensor networks p Framework p n n p Medium access collisions Routing decisions Performance metrics n n n Throughput Energy consumption Packet error rate Environment Terrestrial 152 250 25 Underwater(Deep) 668 439 16 Underwater(Shallow) 1232 1003 236 Underground(vwc=5% ) 864 502 23 Database Laboratory 37

Thank you!! Database Laboratory

Reference p p p p p [1] F. Poppe, D. De Vleeschauwer, G. H. Petit, “Choosing the UMTS airinterface parameters, the voice packet size and the dejitteringdelay for a voice-over-IP call between a UMTS and a PSTN party, ”in Proc. IEEE INFOCOM 2001, vol. 2, pp. 805 -814, April 2001. [2] P. Lettieri, M. B. Srivastava, “Adaptive frame length control for improving wireless link throughput, range, and energy efficiency, ” in Proc. IEEE INFOCOM 1998, vol. 2, pp. 564 -571, April 1998. [3] Y. Sankarasubramaniam, I. F. Akyildiz, S. W. Mc. Laughlin, “Energy efficiency based packet size optimization in wireless sensor networks, ” in Proc. IEEE Internal Workshop on Sensor Network Protocols and Applications, pp. 1 8, 2003. [4] K. Schwieger, A. Kumar, G. Fettweis, “On the Impact of the Physical Layer on Energy Consumption in Sensor Networks, ” in Proc. EWSN ’ 05, pp. 13 - 24, Feb. 2005. [5] M. Zuniga, B. Krishnamachari, “Analyzing the Transitional Region in Low Power Wireless Links, ” in Proc. IEEE SECON ’ 04, pp. 517 – 526, Oct. 2004. [6] M. C. Vuran and I. F. Akyildiz, “Cross Layer Analysis of Error Control in Wireless Sensor Networks, ” in Proc. IEEE SECON ’ 06, Reston, VA, September 2006. [7] IEEE 802. 15. 4, “Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs), ” October 2003. [8] I. F. Akyildiz, D. Pompili, and T. Melodia, “Underwater Acoustic Sensor Networks: Research Challenges, ” Ad Hoc Networks Journal (Elsevier), vol. 3, no. 3, pp. 257 -279, March 2005. [9] L. Li, M. C. Vuran, and I. F. Akyildiz, “Characteristics of Underground Channel for Wireless Underground Sensor Networks, ” in Proc. Med-Hoc- Net ’ 07, Corfu, Greece, June 2007. Database Laboratory 39