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Continuous Aggregation in Dynamic Ad-Hoc Networks

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Book cover Structural Information and Communication Complexity (SIROCCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8576))

Abstract

We study a scenario in which n nodes of a mobile ad-hoc network continuously collect data. Their task is to repeatedly update aggregated information about the data, e.g., the maximum, the sum, or the full information about all data received by all nodes at a given time step. This aggregated information has to be disseminated to all nodes.

We propose two performance measures for distributed algorithms for these tasks: The delay is the maximum time needed until the aggregated information about the data measured at some time is output at all nodes. We assume that a node can broadcast information proportional to a constant number of data items per round. A too large communication volume needed for producing an output can lead to the effect that the delay grows unboundedly over time. Thus, we have to cope with the restriction that outputs are computed not for all but only for a fraction of rounds. We refer to this fraction as the output rate of the algorithm.

Our main technical contributions are trade-offs between delay and output rate for aggregation problems under the assumption of T-stable dynamics in the mobile ad-hoc network: The network is always connected and is stable for time intervals of length where is the time needed to compute a maximal independent set. For the maximum function, we are able to show that we can achieve an output rate of with delay . For the sum, we show that it is possible to achieve an output rate of with delay if , and if , we can achieve an output rate of with delay .

This work was partially supported by the German Research Foundation (DFG) within the Priority Program “Algorithms for Big Data” (SPP 1736), by the EU within FET project MULTIPLEX under contract no. 317532, and the International Graduate School “Dynamic Intelligent Systems”.

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References

  1. Abshoff, S., Benter, M., Cord-Landwehr, A., Malatyali, M., Meyer auf der Heide, F.: Token dissemination in geometric dynamic networks. In: Flocchini, P., Gao, J., Kranakis, E., Meyer auf der Heide, F. (eds.) ALGOSENSORS 2013. LNCS, vol. 8243, pp. 22–34. Springer, Heidelberg (2014)

    Google Scholar 

  2. Abshoff, S., Benter, M., Malatyali, M., Meyer auf der Heide, F.: On two-party communication through dynamic networks. In: Baldoni, R., Nisse, N., van Steen, M. (eds.) OPODIS 2013. LNCS, vol. 8304, pp. 11–22. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  3. Awerbuch, B.: Optimal distributed algorithms for minimum weight spanning tree, counting, leader election and related problems (detailed summary). In: Aho, A.V. (ed.) STOC, pp. 230–240. ACM (1987)

    Google Scholar 

  4. Chaudhuri, S., Dubhashi, D.P.: Probabilistic recurrence relations revisited. Theor. Comput. Sci. 181(1), 45–56 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  5. Cornejo, A., Gilbert, S., Newport, C.C.: Aggregation in dynamic networks. In: Kowalski, D., Panconesi, A. (eds.) PODC, pp. 195–204. ACM (2012)

    Google Scholar 

  6. Dutta, C., Pandurangan, G., Rajaraman, R., Sun, Z., Viola, E.: On the complexity of information spreading in dynamic networks. In: Khanna, S. (ed.) SODA, pp. 717–736. SIAM (2013)

    Google Scholar 

  7. Haeupler, B., Karger, D.R.: Faster information dissemination in dynamic networks via network coding. In: Gavoille, C., Fraigniaud, P. (eds.) PODC, pp. 381–390. ACM (2011)

    Google Scholar 

  8. Haeupler, B., Kuhn, F.: Lower bounds on information dissemination in dynamic networks. In: Aguilera, M.K. (ed.) DISC 2012. LNCS, vol. 7611, pp. 166–180. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  9. Karp, R.M.: Probabilistic recurrence relations. J. ACM 41(6), 1136–1150 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  10. Kuhn, F., Locher, T., Schmid, S.: Distributed computation of the mode. In: Bazzi, R.A., Patt-Shamir, B. (eds.) PODC, pp. 15–24. ACM (2008)

    Google Scholar 

  11. Kuhn, F., Locher, T., Wattenhofer, R.: Tight bounds for distributed selection. In: Gibbons, P.B., Scheideler, C. (eds.) SPAA, pp. 145–153. ACM (2007)

    Google Scholar 

  12. Kuhn, F., Lynch, N.A., Oshman, R.: Distributed computation in dynamic networks. In: Schulman, L.J. (ed.) STOC, pp. 513–522. ACM (2010)

    Google Scholar 

  13. Linial, N.: Locality in distributed graph algorithms. SIAM J. Comput. 21(1), 193–201 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  14. Luby, M.: A simple parallel algorithm for the maximal independent set problem. SIAM J. Comput. 15(4), 1036–1053 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  15. Mosk-Aoyama, D., Shah, D.: Computing separable functions via gossip. In: Ruppert, E., Malkhi, D. (eds.) PODC, pp. 113–122. ACM (2006)

    Google Scholar 

  16. Panconesi, A., Srinivasan, A.: Improved distributed algorithms for coloring and network decomposition problems. In: Kosaraju, S.R., Fellows, M., Wigderson, A., Ellis, J.A. (eds.) STOC, pp. 581–592. ACM (1992)

    Google Scholar 

  17. Schneider, J., Wattenhofer, R.: A log-star distributed maximal independent set algorithm for growth-bounded graphs. In: Bazzi, R.A., Patt-Shamir, B. (eds.) PODC, pp. 35–44. ACM (2008)

    Google Scholar 

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Abshoff, S., Meyer auf der Heide, F. (2014). Continuous Aggregation in Dynamic Ad-Hoc Networks. In: Halldórsson, M.M. (eds) Structural Information and Communication Complexity. SIROCCO 2014. Lecture Notes in Computer Science, vol 8576. Springer, Cham. https://doi.org/10.1007/978-3-319-09620-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-09620-9_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09619-3

  • Online ISBN: 978-3-319-09620-9

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