Throughput Optimisation in Ad Hoc Networks of Communication-Aware Mobile Robots
We study throughput optimisation of ad hoc networks of communication-aware mobile robots. The mobile robots equipped with sensing and communication capacities can maintain connectivities and estimate the quality of communication links with their neighbouring peers. The mobile robots self-organise a wireless ad hoc network for transmitting environment exploited data from sources to destinations. Graph-based network model and artificial potential force-based connectivity maintenance are integrated in different ways for the control design of mobile robots. We consider throughput optimisation in twofold: (1) routing-aware optimisation and (2) routing-unaware optimisation. The Monte Carlo simulation results are comparatively analysed and discussed according to the performance metrics.
KeywordsAd hoc networks Throughput optimisation Communication-aware optimisation Route-aware optimisation Mobile robots Sensor networks
This research was supported in part by the University Research Grant at the University of Brunei Darrusalam (UBD/PNC2/2/RG/1(259)).
We sincerely thank anonymous reviewers for their value comments.
- 1.Pham.D.H, Pham.M-T, Tran.V.Q, Ngo.T.D., Self-deployment strategy for a swarm of robots with global network preservation to assist rescuers in hazardous environments. ROBIO 2014, 2655–2660; doi: 10.1109/ROBIO.2014.7090743.
- 2.Ngo.T.D, Pham.D.H, Pham.M-T, A Kangaroo inspired heterogeneous swarm of mobile robots with global network integrity for fast deployment and exploration in large scale structured environments. ROBIO 2014, 1205–1212; doi: 10.1109/ROBIO.2014.7090497.
- 3.Royer E. M., Toh C-K., A Review of Current Routing Protocols for Ad Hoc Mobile Wireless Networks. IEEE Personal Communications, Vol. 6, Issue. 2, 46–55.Google Scholar
- 4.Hong X.; Xu K.; Gerla., M. Scalable Routing Protocols for Mobile Ad Hoc Networks. IEEE Network, Vol. 16, Issue. 4, Vol. 16, Issue. 4, 11–21.Google Scholar
- 5.Hanzo. L.; Tafazolli. R., A survey of QoS Routing Solutions for Mobile Ad hoc Networks. IEEE Communications Surveys & Tutorials, Vol. 9, Issue. 2, 50–70.Google Scholar
- 6.Nemeth. G, Z. R. Turnyi, A. Valk., Throughput of Ideally Routed Wireless Ad hoc Networks. ACM Mobile Comp. Communication. Rev., vol. 5, no. 4, pp. 4046. 2001.Google Scholar
- 7.Grossglauser. M, Tse, D., Mobility Increases the Capacity of Ad-hoc Wireless Networks. IEEE Information Communications, 477–486, 2001.Google Scholar
- 8.Mostofi. Y., Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-gain Approach. Journal of Intelligent and Robotic Systems, 233–256. 2009.Google Scholar
- 9.T.D.Ngo. LinkMind: Link optimization in swarming mobile sensor networks, Sensors 2011, 11, 8180–8202; doi: 10.3390/s110808180.
- 10.T.D.Ngo. Distributed Optimisation of Communication Capacity for Networked Robot Systems, in proceedings of the 9th IEEE International Conference in Ubiquitous Robots and Ambient Intelligence, 419–424; 10.1109/URAI.2012.6463029.Google Scholar
- 11.Khatib, O., Real-time Obstacle Avoidance for Manipulators and Mobile Robots. Int. J. Rob. Res., 1986, 5, 90–99.Google Scholar
- 12.Elkaim, G.; Siegel, M. A., Lightweight Control Methodology for Formation Control of Vehicle Swarms. In Proceedings of the 16th IFAC World Congress, Prague, Czech Republic, 4–8 July 2005.Google Scholar
- 13.Reif, J.; Wang, H., Social potential fields: A Distributed Behavioral Control for Autonomous Robots. Rob. Autonomous Syst., 1999, 27, 171–194.Google Scholar
- 14.Spears, W., Spears, D., Hamann, J. Heil, R. Distributed, Physics-based Control of Swarms of Vehicles. Autonomous Robot., 2004, 17, 137–162.Google Scholar
- 15.Ge, S.S., Cui, Y.J., New Potential Functions for Mobile Robot Path Planning. IEEE Trans. Rob. Autom., 2000, 16, 615–620.Google Scholar
- 16.Kim, H.D.; Shin, S., Wang, O.H., Decentralized Control of Autonomous Swarm Systems, Using Artificial Potential Functions: Analytical Design Guidelines. Int. J. Intell. Rob. Syst., 2006, 45, 369–394.Google Scholar
- 17.Horward, A., Mataric, M., Sukatme, G., Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem. In Proceedings of the Sixth International Symposium on Distributed Autonomous Robotics Systems, Fukuoka, Japan, 25–27 2002; 229–230.Google Scholar
- 18.Mikkelsen, B.S., Jespersen, R., Ngo, T.D., Probabilistic Communication based Potential Force for Robot Formations: A Practical Approach. In Springer Tracts in Advanced Robotics, Vol 83, 2013, pp 243–253.Google Scholar
- 19.Tanner, G.H., Jadbabai, A., Pappas, J.G., Stable Flocking of Mobile Agents, Part I: Fixed Topology. In Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, HI, USA, 12 December 2003; pp. 2010–2015.Google Scholar
- 20.Tanner, G.H., Jadbabai, A., Pappas, J.G., Stable Flocking of Mobile Agents, Part II: Dynamic Topology. In Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, HI, USA, 12 December 2003; pp. 2016–2021.Google Scholar
- 21.Desai, P.J., A Graph Theoretic Approach for Modelling Mobile Robot Team Formations. J. Rob. Syst., 2002, 19, 511–525.Google Scholar
- 22.Dong, W., Guo, Y., Formation Control of Nonholonomic Mobile Robots using Graph Theoretical Methods. Lect. Notes Econ. Math. Syst., 2007, 588, pp. 369–386.Google Scholar
- 23.Ji, M., Egerstedt, M. Distributed Coordination Control of Multi-agent Systems while Preserving Connectedness. IEEE Trans. Rob., 2007, 23, pp. 693–703.Google Scholar
- 24.Olfati-Saber, R. Murray, M.R., Consensus Problems in Networks of Agents with Switching Topology and Time-delays. IEEE Trans. Autom. Control, 49, pp. 1520–1533.Google Scholar
- 25.Haenggi. M, Analysis and Design of Diversity Schemes for Ad Hoc wireless networks. IEEE journal on Selected Areas in Communication, Vol. 23, No 1, 2005.Google Scholar
- 26.Liu, X., Haenggi. M., Throughput Analysis of Fading Sensor Networks with Regular and Random Topologies, EURASIP Journal on Wireless Communication. pp. 554–564. 2005.Google Scholar
- 27.Fida. A, H.D.Pham, Tuah.J.N, T.D.Ngo, Communication Aware Route Selection of Wireless Sensor Networks, in the 13th International Conference on Intelligent Autonomous Systems, Padova, Italia, 15–19 July 2014.Google Scholar
- 28.Ford, L.R., Fulkerson, D.R. Maximal Flow through a Network. Can. J. Math., 1956, 8, pp. 399–404.Google Scholar