Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 7611))
Included in the following conference series:
Abstract
A set of identical, mobile agents is deployed in a weighted network. Each agent possesses a battery - a power source allowing the agent to move along network edges. Agents use their batteries proportionally to the distance traveled. At the beginning, each agent has its initial information. Agents exchange the actually possessed information when they meet. The agents collaborate in order to perform an efficientconvergecast, where the initial information of all agents must be eventually transmitted to some agent.
The objective of this paper is to investigate what is the minimal value of power, initially available to all agents, so that convergecast may be achieved. We study the question in the centralized and the distributed settings. In the distributed setting every agent has to perform an algorithm being unaware of the network. We give a linear-time centralized algorithm solving the problem for line networks. We give a 2-competitive distributed algorithm achieving convergecast for tree networks. The competitive ratio of 2 is proved to be the best possible for this problem, even if we only consider line networks. We show that already for the case of tree networks the centralized problem is strongly NP-complete. We give a 2-approximation centralized algorithm for general graphs.
Partially supported by NSERC discovery grant and by the Research Chair in Distributed Computing at the Université du Québec en Outaouais.
This is a preview of subscription content,log in via an institution to check access.
Access this chapter
Subscribe and save
- Get 10 units per month
- Download Article/Chapter or eBook
- 1 Unit = 1 Article or 1 Chapter
- Cancel anytime
Buy Now
- Chapter
- JPY 3498
- Price includes VAT (Japan)
- eBook
- JPY 5719
- Price includes VAT (Japan)
- Softcover Book
- JPY 7149
- Price includes VAT (Japan)
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Albers, S.: Energy-efficient algorithms. Comm. ACM 53(5), 86–96 (2010)
Albers, S., Henzinger, M.R.: Exploring unknown environments. SIAM J. on Comput. 29(4),1164–1188
Alpern, S., Gal, S.: The theory of search games and rendezvous. Kluwer Academic Publ. (2002)
Ambühl, C.: An Optimal Bound for the MST Algorithm to Compute Energy Efficient Broadcast Trees in Wireless Networks. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 1139–1150. Springer, Heidelberg (2005)
Ando, H., Oasa, Y., Suzuki, I., Yamashita, M.: Distributed memoryless point convergence algorithm for mobile robots with limited visibility. IEEE Trans. on Robotics and Automation 15(5), 818–828 (1999)
Angluin, D., Aspnes, J., Diamadi, Z., Fischer, M.J., Peralta, R.: Computation in networks of passively mobile finite-state sensors. In: Distributed Computing, pp. 235–253 (2006)
Annamalai, V., Gupta, S.K.S., Schwiebert, L.: On Tree-Based Convergecasting in Wireless Sensor Networks. IEEE Wireless Communications and Networking 3, 1942–1947 (2003)
Augustine, J., Irani, S., Swamy, C.: Optimal powerdown strategies. SIAM J. Comput. 37, 1499–1516 (2008)
Averbakh, I., Berman, O.: A heuristic with worst-case analysis for minimax routing of two traveling salesmen on a tree. Discrete Applied Mathematics 68, 17–32 (1996)
Azar, Y.: On-line Load Balancing. In: Fiat, A., Woeginger, G. (eds.) Online Algorithms 1996. LNCS, vol. 1442, pp. 178–195. Springer, Heidelberg (1998)
Awerbuch, B., Betke, M., Rivest, R., Singh, M.: Piecemeal graph exploration by a mobile robot. Information and Computation 152, 155–172 (1999)
Baeza Yates, R.A., Culberson, J.C., Rawlins, G.J.E.: Searching in the Plane. Information and Computation 106(2), 234–252 (1993)
Bender, M., Fernandez, A., Ron, D., Sahai, A., Vadhan, S.: The power of a pebble: exploring and mapping directed graphs. In: Proc. 30th STOC, pp. 269–278 (1998)
Bender, M., Slonim, D.: The power of team exploration: two robots can learn unlabeled directed graphs. In: Proc. 35th FOCS, pp. 75–85 (1994)
Betke, M., Rivest, R.L., Singh, M.: Piecemeal learning of an unknown environment. Machine Learning 18(2/3), 231–254 (1995)
Blum, A., Raghavan, P., Schieber, B.: Navigating in unfamiliar geometric terrain. SIAM J. Comput. 26(1), 110–137 (1997)
Bunde, D.P.: Power-aware scheduling for makespan and flow. In: SPAA, pp. 190–196 (2006)
Chen, F., Johnson, M.P., Alayev, Y., Bar-Noy, A., La Porta, T.F.: Who, When, Where: Timeslot Assignment to Mobile Clients. IEEE Transactions on Mobile Computing 11(1), 73–85 (2012)
Cieliebak, M., Flocchini, P., Prencipe, G., Santoro, N.: Solving the Robots Gathering Problem. In: Baeten, J.C.M., Lenstra, J.K., Parrow, J., Woeginger, G.J. (eds.) ICALP 2003. LNCS, vol. 2719, pp. 1181–1196. Springer, Heidelberg (2003)
Cohen, R., Peleg, D.: Convergence Properties of the Gravitational Algorithm in Asynchronous Robot Systems. SIAM J. on Comput. 34(6), 1516–1528 (2005)
Cord-Landwehr, A., Degener, B., Fischer, M., Hüllmann, M., Kempkes, B., Klaas, A., Kling, P., Kurras, S., Märtens, M., Meyer auf der Heide, F., Raupach, C., Swierkot, K., Warner, D., Weddemann, C., Wonisch, D.: A New Approach for Analyzing Convergence Algorithms for Mobile Robots. In: Aceto, L., Henzinger, M., Sgall, J. (eds.) ICALP 2011, Part II. LNCS, vol. 6756, pp. 650–661. Springer, Heidelberg (2011)
Deng, X., Papadimitriou, C.H.: Exploring an unknown graph. In: Proc. 31st FOCS, vol. I, pp. 355–361 (1990)
Das, S., Flocchini, P., Santoro, N., Yamashita, M.: On the Computational Power of Oblivious Robots: Forming a Series of Geometric Patterns. In: Proc. PODC, pp. 267–276 (2010)
Dynia, M., Korzeniowski, M., Schindelhauer, C.: Power-Aware Collective Tree Exploration. In: Grass, W., Sick, B., Waldschmidt, K. (eds.) ARCS 2006. LNCS, vol. 3894, pp. 341–351. Springer, Heidelberg (2006)
Flocchini, P., Prencipe, G., Santoro, N., Widmayer, P.: Gathering of asynchronous robots with limited visibility. Th. Comp. Science 337, 147–168 (2005)
Fraigniaud, P., Gąsieniec, L., Kowalski, D.R., Pelc, A.: Collective Tree Exploration. In: Farach-Colton, M. (ed.) LATIN 2004. LNCS, vol. 2976, pp. 141–151. Springer, Heidelberg (2004)
Garey, M.R., Johnson, D.S.: Computers and Intractability. A Guide to the Theory of NP-Completeness, 96–105, 224 (1979)
Frederickson, G., Hecht, M., Kim, C.: Approximation algorithms for some routing problems. SIAM J. on Comput. 7, 178–193 (1978)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Microsensor Networks. Transactions on Wireless Communication 1(4), 660–670 (2002)
Irani, S., Shukla, S.K., Gupta, R.: Algorithms for power savings. ACM Trans. on Algorithms 3(4), Article 41 (2007)
Kesselman, A., Kowalski, D.R.: Fast distributed algorithm for convergecast in ad hoc geometric radio networks. Journal of Parallel and Distributed Computing 66(4), 578–585 (2006)
Krishnamachari, L., Estrin, D., Wicker, S.: The impact of data aggregation in wireless sensor networks. In: ICDCS Workshops, pp. 575–578 (2002)
Megow, N., Mehlhorn, K., Schweitzer, P.: Online Graph Exploration: New Results on Old and New Algorithms. In: Aceto, L., Henzinger, M., Sgall, J. (eds.) ICALP 2011, Part II. LNCS, vol. 6756, pp. 478–489. Springer, Heidelberg (2011)
Nikoletseas, S., Spirakis, P.G.: Distributed Algorithms for Energy Efficient Routing and Tracking in Wireless Sensor Networks. Algorithms 2, 121–157 (2009)
Rajagopalan, R., Varshney, P.K.: Data-aggregation techniques in sensor networks: a survey. IEEE Communications Surveys and Tutorials 8(4), 48–63 (2006)
Stojmenovic, I., Lin, X.: Power-Aware Localized Routing in Wireless Networks. IEEE Trans. Parallel Distrib. Syst. 12(11), 1122–1133 (2001)
Suzuki, I., Yamashita, M.: Distributed Anonymous Mobile Robots: Formation of Geometric Patterns. SIAM J. Comput. 28(4), 1347–1363 (1999)
Yamashita, M., Suzuki, I.: Characterizing geometric patterns formable by oblivious anonymous mobile robots. Th. Comp. Science 411(26-28), 2433–2453 (2010)
Yao, F.F., Demers, A.J., Shenker, S.: A scheduling model for reduced CPU energy. In: Proc. of 36th FOCS, pp. 374–382 (1995)
Author information
Authors and Affiliations
Université du Québec en Outaouais, C.P. 1250, succ. Hull, Gatineau, QC, J8X 3X7, Canada
Julian Anaya, Jurek Czyzowicz & Andrzej Pelc
LIF, CNRS & Aix-Marseille University, 13453, Marseille, France
Jérémie Chalopin, Arnaud Labourel & Yann Vaxès
- Julian Anaya
You can also search for this author inPubMed Google Scholar
- Jérémie Chalopin
You can also search for this author inPubMed Google Scholar
- Jurek Czyzowicz
You can also search for this author inPubMed Google Scholar
- Arnaud Labourel
You can also search for this author inPubMed Google Scholar
- Andrzej Pelc
You can also search for this author inPubMed Google Scholar
- Yann Vaxès
You can also search for this author inPubMed Google Scholar
Editor information
Editors and Affiliations
Microsoft Corporation, Building SVC6, 1065 La Avenida, 94043, Mountain View, CA, USA
Marcos K. Aguilera
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Anaya, J., Chalopin, J., Czyzowicz, J., Labourel, A., Pelc, A., Vaxès, Y. (2012). Collecting Information by Power-Aware Mobile Agents. In: Aguilera, M.K. (eds) Distributed Computing. DISC 2012. Lecture Notes in Computer Science, vol 7611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33651-5_4
Download citation
Publisher Name:Springer, Berlin, Heidelberg
Print ISBN:978-3-642-33650-8
Online ISBN:978-3-642-33651-5
eBook Packages:Computer ScienceComputer Science (R0)
Share this paper
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative