Skip to main content

Autonomous Cooperative Routing for Mission-Critical Applications

  • Chapter
  • First Online:
Mission-Oriented Sensor Networks and Systems: Art and Science

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 164))

Abstract

We are entering an era where three previously decoupled domains of technology are rapidly converging together: robotics and wireless communications. We have seen giant leaps and improvements in computational efficiency of vision processing and sensing circuitry coupled with continuously miniaturized form factors. As a result, a new wave of mission-critical systems has been unleashed in fields like emergency response, public safety, law enforcement, search and rescue, as well as industrial asset mapping. There is growing evidence showing that the efficacy of team-based mission-critical systems is substantially improved when situational awareness data, such as real-time video, is disseminated within the network. Field commanders or operation managers can make great use of live vision feeds to make educated decisions in the face of unfolding circumstances or events. In the likely absence of adequate cellular service, this translates into the need for a mobile ad hoc networking technology (MANET) that supports high throughput but more importantly low end-to-end latency. However, classical MANET technologies fall short in terms of scalability, bandwidth, and latency; all three metrics being quite essential for mission-critical applications. The real bottleneck has always been in how fast packets can be routed through the network. To that end, autonomous cooperative routing (ACR) has gained traction as the most viable MANET routing proposition. Compared to classical MANET routing schemes, ACR is poised to offer up to 2X better throughput, more than 4X reduction in end-to-end latency, while observing a given target of transport rate normalized to energy consumption. Nonetheless, ACR is also associated with a few practical implementation challenges. If these go unaddressed, it will deem ACR practically infeasible. In this chapter, efficient and low-complexity remedies to those issues are presented, analyzed, and validated. The validation is based on field experiments carried out using software-defined radio (SDR) platforms. This chapter sheds light on the underlying networking challenges and practical remedies for ACR to fulfill its promise.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    LTE-Unlicensed hotspots is obviously a very comparable option to Wi-Fi. In other words, it will suffer more or less from the same scalability issues outlined herewith for the case of Wi-Fi.

  2. 2.

    A video capture of the turnaround time measurement is posted online for the interested reader (https://youtu.be/lDYVHZ6GcIM).

  3. 3.

    The choice of a value for the path availability metric is indeed relative and subject to the underlying application. In mission-critical applications, robustness and high reliability are often stressed as key performance indicators by end users. Thus, selecting 95% as a benchmark mainly stems from feedback the authors accumulated through interactions with end users.

References

  1. Suriyachai, P., Roedig, U., Scott, A.: A survey of mac protocols for mission-critical applications in wireless sensor networks. IEEE Commun. Surv. Tutor. 14(2), 240–264 (2012)

    Article  Google Scholar 

  2. Fink, J., Ribeiro, A., Kumar, V.: Robust control of mobility and communications in autonomous robot teams. IEEE Access 1, 290–309 (2013)

    Article  Google Scholar 

  3. Ghafoor, S., Sutton, P.D., Sreenan, C.J., Brown, K.N.: Cognitive radio for disaster response networks: survey, potential, and challenges. IEEE Wirel. Commun. 21(5), 70–80 (2014)

    Article  Google Scholar 

  4. Akyildiz, I., Melodia, T., Chowdhury, K.: A survey on wireless multimedia sensor networks. Elsevier J. Comput. Netw. 51(4), 921–960 (2007)

    Article  Google Scholar 

  5. Zhang, Z.J., Lai, C.F., Chao, H.C.: A green data transmission mechanism for wireless multimedia sensor networks using information fusion. IEEE Wirel. Commun. 21(4), 14–19 (2014)

    Article  Google Scholar 

  6. Yang, L., Yang, S.-H., Plotnick, L.: How the Internet of Things technology enhances emergency response operations. Technol. Forecast. Soc. Change Elsevier 80(9), 1854–1867 (2013)

    Article  Google Scholar 

  7. Chai, P.R.: Wearable devices and biosensing: Future frontiers. J. Med. Toxicol. 1–3 (2016)

    Google Scholar 

  8. Panayides, A., Antoniou, Z.C., Mylonas, Y., Pattichis, M.S., Pitsillides, A., Pattichis, C.S.: High-resolution, low-delay, and error-resilient medical ultrasound video communication using h.264/avc over mobile wimax networks. IEEE J. Biomed. Health. Inform. 17(3), 619–628 (2013)

    Google Scholar 

  9. Bergstrand, F., Landgren, J.: Using live video for information sharing in emergency response work. Int. J. Emerg. Manag. 6(3–4), 295–301 (2009)

    Article  Google Scholar 

  10. Blair, A., Brown, T., Chugg, K.M., Halford, T.R., Johnson, M.: Barrage relay networks for cooperative transport in tactical manets. In MILCOM 2008—2008 IEEE Military Communications Conference, Nov 2008, pp. 1–7

    Google Scholar 

  11. Bergstrand, F., Landgren, J.: Visual reporting in time-critical work: exploring video use in emergency response. In: Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services, pp. 415–424 (2011)

    Google Scholar 

  12. Nunes, D.S., Zhang, P., Sa Silva, J.: A survey on human-in-the-loop applications towards an internet of all. IEEE Commun. Surv. Tutor. 17(2), 944–965 (2015)

    Article  Google Scholar 

  13. Felts, R., Leh, M., McElvaney, T.: Public safety analytics r&d roadmap. National Institute of Standards and Technology (NIST), U.S. Department of Commerce, Technical Note 1917, Apr 2016

    Google Scholar 

  14. Bayezit, I., Fidan, B.: Distributed cohesive motion control of flight vehicle formations. IEEE Trans. Ind. Electron. 60(12), 5763–5772 (2013)

    Article  Google Scholar 

  15. Berni, J., Zarco-Tejada, P.J., Suarez, L., Fereres, E.: Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sens. 47(3), 722–738 (2009)

    Article  Google Scholar 

  16. Siebert, S., Teizer, J.: Mobile 3d mapping for surveying earthwork projects using an unmanned aerial vehicle (uav) system. Autom. Constr. Elsevier 41, 1–14 (2014)

    Article  Google Scholar 

  17. Lin, X., Andrews, J.G., Ghosh, A., Ratasuk, R.: An overview of 3g pp device-to-device proximity services. IEEE Commun. Mag. 52(4), 40–48 (2014)

    Article  Google Scholar 

  18. Bader, A., Ghazzai, H., Kadri, A., Alouini, M.S.: Front-end intelligence for large-scale application-oriented internet-of-things. IEEE Access 4, 3257–3272 (2016)

    Article  Google Scholar 

  19. Carl, L., Fantacci, R., Gei, F., Marabissi, D., Micciullo, L.: Lte enhancements for public safety and security communications to support group multimedia communications. IEEE Netw. 30(1), 80–85 (2016)

    Article  Google Scholar 

  20. Gharbieh, M., ElSawy, H., Bader, A., Alouini, M.-S.: Tractable stochastic geometry model for iot access in lte networks. In: To Appear in Proceedings of IEEE Globecom 2016, Washington D.C., December 2016

    Google Scholar 

  21. Kiess, W., Mauve, M.: A survey on real-world implementations of mobile ad-hoc networks. Ad Hoc Netw. 5(3), 324–339 (2007)

    Article  Google Scholar 

  22. Bellalta, B.: IEEE 802.11ax: high-efficiency wlans. IEEE Wirel. Commun. 23(1), 38–46 (2016)

    Article  Google Scholar 

  23. Abouzeid, A.A., Bisnik, N.: Geographic protocol information and capacity deficit in mobile wireless ad hoc networks. IEEE Trans. Inf. Theory 57(8), 5133–5150 (2011)

    Article  MathSciNet  Google Scholar 

  24. Request for information, novel methods for information sharing in large scale mobile ad-hoc networks, defense advanced research projects agency (darpa), darpa-sn-13-35, April 2013

    Google Scholar 

  25. Halford, T.R., Chugg, K.M., Polydoros, A.: Barrage relay networks: system and protocol design. In: 21st Annual IEEE International Symposium on Personal, pp. 1133–1138. Sept, Indoor and Mobile Radio Communications (2010)

    Google Scholar 

  26. Halford, T.R., Chugg, K.M.: Barrage relay networks. In: Information Theory and Applications Workshop (ITA), 2010, Jan 2010, pp. 1–8

    Google Scholar 

  27. Acer, U.G., Kalyanaraman, S., Abouzeid, A.A.: Weak state routing for large-scale dynamic networks. IEEE/ACM Trans. Netw. 18(5), 1450–1463 (2010)

    Article  Google Scholar 

  28. Halford, T.R., Chugg, K.M.: The stability of multihop transport with autonomous cooperation. In: 2011—MILCOM 2011 Military Communications Conference, Nov 2011, pp. 1023–1028

    Google Scholar 

  29. Bader, A., Abed-Meraim, K., Alouini, M.-S.: An efficient multi-carrier position-based packet forwarding protocol for wireless sensor networks. IEEE Trans. Wirel. Commun. 11(1), 305–315 (2012)

    Article  Google Scholar 

  30. Lakshmi, V., Thanayankizil, A.K., Ingram, M.A.: Opportunistic large array concentric routing algorithm (olacra) for upstream routing in wireless sensor networks. Ad Hoc Netw. 9(7), 1140–1153 (2011)

    Article  Google Scholar 

  31. Ke, C.-K., Chen, Y.-L., Chang, Y.-C., Zeng, Y.-L.: Opportunistic large array concentric routing algorithms with relay nodes for wireless sensor networks. Comput. Electr, Eng (2016)

    Book  Google Scholar 

  32. Halford, T.R., Courtade, T.A., Turck, K.A.: The user capacity of barrage relay networks. In: MILCOM 2012—2012 IEEE Military Communications Conference, Oct 2012, pp. 1–6

    Google Scholar 

  33. Xiang, X., Wang, X., Zhou, Z.: Self-adaptive on-demand geographic routing for mobile ad hoc networks. IEEE Trans. Mob. Comput. 11(9), 1572–1586 (2012)

    Article  Google Scholar 

  34. Intelligent transport systems (its); vehicular communications; geonetworking; part 4: geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality, v1.2.0, Oct 2013

    Google Scholar 

  35. Sanchez, J., Ruiz, P., Marin-Perez, R.: Beacon-less geographic routing made practical: challenges, design guidelines, and protocols. IEEE Commmun. Mag. 47(8), 85–91 (2009)

    Article  Google Scholar 

  36. Scaglione, A., Goeckel, D., Laneman, J.: Cooperative communications in mobile ad hoc networks. IEEE Signal Process. Mag. 23(5), 18–29 (2006)

    Article  Google Scholar 

  37. Sirkeci-Mergen, B., Scaglione, A.: Randomized space-time coding for distributed cooperative communication. ICC (2006)

    Google Scholar 

  38. Sirkeci-Mergen, B., Scaglione, A.: Randomized space-time coding for distributed cooperative communication. IEEE Trans. Signal Process. 55(10), 5003–5017 (2007)

    Article  MathSciNet  Google Scholar 

  39. Sharp, M., Scaglione, A., Sirkeci-Mergen, B.: Randomized cooperation in asynchronous dispersive links. IEEE Trans. Commun. 57(1), 64–68 (2009)

    Article  Google Scholar 

  40. Li, Y., Zhang, Z., Wang, C., Zhao, W., Chen, H.-H.: Blind cooperative communications for multihop ad hoc wireless networks. IEEE Trans. Veh. Technol. 62(7), 3110–3122 (2013)

    Article  Google Scholar 

  41. Brian, R.H., Hwang, G.: Barrage relay networks for unmanned ground systems. In: Military Communications Conference, 2010—MILCOM 2010, Oct 2010, pp. 1274–1280

    Google Scholar 

  42. Lee, D.K., Chugg, K.M.: A pragmatic approach to cooperative communication. In: MILCOM 2006—2006 IEEE Military Communications Conference, Oct 2006, pp. 1–7

    Google Scholar 

  43. Bader, A., Alouini, M.-S.: An ultra-low-latency geo-routing scheme for team-based unmanned vehicular applications. In: IEEE Globecom Workshops (GC Wkshps), 2015. IEEE, pp. 1–6 (2015)

    Google Scholar 

  44. Bader, A., Alouini, M.S.: Localized power control for multihop large-scale internet of things. IEEE Internet of Things J. 3(4), 503–510 (2016)

    Article  Google Scholar 

  45. Zorzi, M., Rao, R.: Geographic random forwarding (GeRaF) for ad hoc and sensor networks: multihop performance. IEEE Trans. Mob. Comput. 2(4), 337–348 (2003)

    Article  Google Scholar 

  46. Gupta, P., Kumar, P.R.: The capacity of wireless networks. IEEE Trans. Inf. Theory 46(2), 388–404 (2000)

    Article  MathSciNet  Google Scholar 

  47. Bisnik, N., Abouzeid, A.A.: Queuing network models for delay analysis of multihop wireless ad hoc networks. Ad Hoc Netw. Elsevier 7(1), 79–97 (2009)

    Article  Google Scholar 

  48. Bisnik, N., Abouzeid, A.A.: Queuing delay and achievable throughput in random access wireless ad hoc networks. In: 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, Sept 3, pp. 874–880 (2006)

    Google Scholar 

  49. Wu, H., Peng, Y., Long, K., Cheng, S., Ma, J.: Performance of reliable transport protocol over ieee 802.11 wireless lan: analysis and enhancement. In: INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings, vol. 2, pp. 599–607. IEEE (2002)

    Google Scholar 

  50. Bader, A., Abed-Meraim, K., Alouini, M.S.: Reduction of buffering requirements: Another advantage of cooperative transmission. IEEE Sens. J. 15(4), 2017–2018 (2015)

    Article  Google Scholar 

  51. McDonald, A.B., Znati, T.F.: A mobility-based framework for adaptive clustering in wireless ad hoc networks. IEEE J. Sel. Areas Commun. 17(8), 1466–1487 (1999)

    Article  Google Scholar 

  52. Squartini, T., Picciolo, F., Ruzzenenti, F., Garlaschelli, D.: Reciprocity of weighted networks. Scientific reports, vol. 3, 2013

    Google Scholar 

  53. Eriksson, M., Mahmud, A.: Dynamic single frequency networks in wireless multihop networks—energy aware routing algorithms with performance analysis. In: Proceedings of The 10th IEEE International Conference on Computer and Information Technology, Bradford, UK, pp. 400–406, May 2010

    Google Scholar 

  54. Bader, A., Alouini, M.S.: Mobile ad hoc networks in bandwidth-demanding mission-critical applications: practical implementation insights. IEEE Access 5, 891–910 (2017)

    Article  Google Scholar 

  55. Srinivasa, S., Haenggi, M.: Distance distributions in finite uniformly random networks: theory and applications. IEEE Trans. Veh. Technol. 59(2), 940–949 (2010)

    Article  Google Scholar 

  56. Qiu, H., Wang, K., Psounis, K., Caire, G., Chugg, K.M.: High-rate wifi broadcasting in crowded scenarios via lightweight coordination of multiple access points. In: MobiHoc ’16 Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, July 2016, pp. 301–310

    Google Scholar 

  57. Rappaport, T.: Wireless Communications: Priciples and Practice, 2nd edn. Prentice Hall (2001)

    Google Scholar 

  58. Schulze, H., Lueders, C.: Theory and Applications of OFDM and CDMA, 1st edn. John Wiley and Sons Ltd (2005)

    Google Scholar 

  59. Zhao, B., Valenti, M.C.: Practical relay networks: a generalization of hybrid-ARQ. IEEE J. Sel. Areas Commun. 23(1) (2005)

    Google Scholar 

  60. Rouphael, T.J.: Wireless Receiver Architectures and Design: Antennas, RF. Mixed Signal, and Digital Signal Processing. Elsevier, Synthesizers (2014)

    Google Scholar 

  61. Ran, J., Grunheid, R., Rohling, H., Bolinth, E., Kern, R.: Decision-directed channel estimation method for OFDM systems with high velocities. In: Vehicular Technology Conference, 2003. VTC 2003-Spring. The 57th IEEE Semiannual, April 2003, vol. 4, pp. 2358–2361

    Google Scholar 

  62. Hsieh, M.-H., Wei, C.-H.: Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels. IEEE Trans. Consum. Electron. 44(1), 217–225 (1998)

    Article  Google Scholar 

  63. Coleri, S., Ergen, M., Puri, A., Bahai, A.: Channel estimation techniques based on pilot arrangement in ofdm systems. IEEE Trans. Broadcast. 48(3), 223–229 (2002)

    Article  Google Scholar 

  64. Athaudage, C.: BER sensitivity of OFDM systems to time synchronization error. In: The 8th International Conference on Communication Systems (ICCS’02), Singapore, vol. 1, pp. 42–46, Nov 2002

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed-Slim Alouini .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bader, A., Alouini, MS. (2019). Autonomous Cooperative Routing for Mission-Critical Applications. In: Ammari, H. (eds) Mission-Oriented Sensor Networks and Systems: Art and Science. Studies in Systems, Decision and Control, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-319-92384-0_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92384-0_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92383-3

  • Online ISBN: 978-3-319-92384-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics