Communication Problems for Mobile Agents Exchanging Energy

A set of mobile agents is deployed in the nodes of an edge-weighted network. Agents originally possess amounts of energy, possibly different for all agents. The agents travel in the network spending energy proportional to the distance traversed. Some nodes of the network may keep information which is acquired by the agents visiting them. The meeting agents may exchange currently possessed information, as well as any amount of energy. We consider communication problems when the information initially held by some network nodes have to be communicated to some other nodes and/or agents. The paper deals with two communication problems: data delivery and convergecast. These problems are posed for a centralized scheduler which has full knowledge of the instance. It is already known that, without energy exchange, both problems are NP-complete even if the network is a line. In this paper we show that, if the agents are allowed to exchange energy, both problems have linear-time solutions on trees. On the other hand for general undirected and directed graphs we show that these problems are NP-complete.

[1]  Sandy Irani,et al.  Algorithms for power savings , 2003, SODA '03.

[2]  Jérémie Chalopin,et al.  Data Delivery by Energy-Constrained Mobile Agents on a Line , 2014, ICALP.

[3]  Chul E. Kim,et al.  Approximation Algorithms for Some Routing Problems , 1978, SIAM J. Comput..

[4]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[5]  Andrzej Pelc,et al.  Collecting Information by Power-Aware Mobile Agents , 2012, DISC.

[6]  Paolo Penna,et al.  Data Delivery by Energy-Constrained Mobile Agents , 2013, ALGOSENSORS.

[7]  Yossi Azar.  On-line Load Balancing , 1996, Online Algorithms.

[8]  Susanne Albers,et al.  Exploring Unknown Environments , 2000, SIAM J. Comput..

[9]  John Augustine,et al.  Optimal Power-Down Strategies , 2008, SIAM J. Comput..

[10]  F. Frances Yao,et al.  A scheduling model for reduced CPU energy , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[11]  Andrzej Pelc,et al.  Collective Tree Exploration , 2004, LATIN.

[12]  René Schott,et al.  Parallel Searching in the Plane , 1995, Comput. Geom..

[13]  Sandeep K. S. Gupta,et al.  On tree-based convergecasting in wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[14]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[15]  Oded Berman,et al.  A Heuristic with Worst-case Analysis for Minimax Routing of Two Travelling Salesmen on a Tree , 1996, Discret. Appl. Math..

[16]  Susanne Albers,et al.  Energy-efficient algorithms , 2010, Commun. ACM.

[17]  Christian Schindelhauer,et al.  Power-Aware Collective Tree Exploration , 2006, ARCS.

[18]  Shantanu Das,et al.  Collaborative Exploration by Energy-Constrained Mobile Robots , 2015, SIROCCO.

[19]  Dariusz R. Kowalski,et al.  Fast Distributed Algorithm for Convergecast in Ad Hoc Geometric Radio Networks , 2005, Second Annual Conference on Wireless On-demand Network Systems and Services.