Topology control in ad-hoc networks tries to lower node energy consumption by reducing transmission power and by confining interference, collisions and consequently retransmissions. Commonly low interference is claimed to be a consequence to sparseness of the resulting topology. In this paper we disprove this implication. In contrast to most of the related work-claiming to solve the interference issue by graph sparseness without providing clear argumentation or proofs-, we provide a concise and intuitive definition of interference. Based on this definition we show that most currently proposed topology control algorithms do not effectively constrain interference. Furthermore we propose connectivity-preserving and spanner constructions that are interference-minimal.

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In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For foreign coding we propose the MEGA algorithm which yields a minimum-energy data gathering topology in O n 3 time. We also consider self-coding for which the problem of finding an optimal data gathering tree was recently shown to be NP-complete; with LEGA, we present the first approximation algorithm for this problem with approximation ratio 2(1 + √ 2) and running time O(m + n log n).

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Abstract. The infrastructure for mobile distributed tasks is often formed by cellular networks. One of the major issues in such networks is interference. In this paper we tackle interference reduction by suitable assignment of transmission power levels to base stations. This task is formalized introducing the Minimum Membership Set Cover combinatorial optimization problem. On the one hand we prove that in polynomial time the optimal solution of the problem cannot be approximated more closely than with a factor ln n. On the other hand we present an algorithm exploiting linear programming relaxation techniques which asymptotically matches this lower bound.

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The inherent trade-off between energy-efficiency and rapidity of event dissemination is characteristic for wireless sensor networks. Scarcity of energy renders it necessary for nodes to spend a large portion of their lifetime in an energyefficient sleep mode during which they do neither receive nor send messages. On the other hand, the longer nodes stay in sleep mode, the slower will be the reaction time for disseminating an external event. The trade-off is prominently exhibited during the deployment phase of sensor networks, if some nodes are deployed earlier than others. In this paper, we study this fundamental trade-off by giving a formal model that enables us to compare the performance of different protocols and algorithms. Based on this model, we propose, analyze, and simulate two novel algorithms which significantly outperform existing solutions.