Information and Computation
Piecemeal Learning of an Unknown Environment
Machine Learning - Special issue on COLT '93
A heuristic with worst-case analysis for minimax routing of two travelling salesmen on a tree
Discrete Applied Mathematics
Navigating in Unfamiliar Geometric Terrain
SIAM Journal on Computing
The power of a pebble: exploring and mapping directed graphs
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Distributed Anonymous Mobile Robots: Formation of Geometric Patterns
SIAM Journal on Computing
Piecemeal graph exploration by a mobile robot
Information and Computation
Exploring Unknown Environments
SIAM Journal on Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Power-Aware Localized Routing in Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Developments from a June 1996 seminar on Online algorithms: the state of the art
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Convergence Properties of the Gravitational Algorithm in Asynchronous Robot Systems
SIAM Journal on Computing
Gathering of asynchronous robots with limited visibility
Theoretical Computer Science
Fast distributed algorithm for convergecast in ad hoc geometric radio networks
Journal of Parallel and Distributed Computing - Special issue: Algorithms for wireless and ad-hoc networks
Power-aware scheduling for makespan and flow
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
Computation in networks of passively mobile finite-state sensors
Distributed Computing - Special issue: PODC 04
ACM Transactions on Algorithms (TALG)
SIAM Journal on Computing
SFCS '90 Proceedings of the 31st Annual Symposium on Foundations of Computer Science
The power of team exploration: two robots can learn unlabeled directed graphs
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Communications of the ACM
Solving the robots gathering problem
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Characterizing geometric patterns formable by oblivious anonymous mobile robots
Theoretical Computer Science
On the computational power of oblivious robots: forming a series of geometric patterns
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Online graph exploration: new results on old and new algorithms
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
A new approach for analyzing convergence algorithms for mobile robots
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
Who, When, Where: Timeslot Assignment to Mobile Clients
IEEE Transactions on Mobile Computing
Power-Aware collective tree exploration
ARCS'06 Proceedings of the 19th international conference on Architecture of Computing Systems
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Data-aggregation techniques in sensor networks: a survey
IEEE Communications Surveys & Tutorials
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
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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 efficient convergecast , 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.