The Spatial Node Distribution of the Random Waypoint Mobility Model
Mobile Ad-Hoc Netzwerke, 1. deutscher Workshop über Mobile Ad-Hoc Netzwerke WMAN 2002
The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Geometry of information propagation in massively dense ad hoc networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
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IEEE/ACM Transactions on Networking (TON)
Spatial Node Distribution of the Random Waypoint Mobility Model with Applications
IEEE Transactions on Mobile Computing
Interperf '06 Proceedings from the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer & communications sytems
Random waypoint mobility model in cellular networks
Wireless Networks
Stationary Distributions for the Random Waypoint Mobility Model
IEEE Transactions on Mobile Computing
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IEEE Transactions on Information Theory
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IEEE Transactions on Information Theory
On optimality of single-path routes in massively dense wireless multi-hop networks
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On the optimality of field-line routing in massively dense wireless multi-hop networks
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Fine grained load balancing in multi-hop wireless networks
Journal of Parallel and Distributed Computing
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ACM Transactions on Sensor Networks (TOSN)
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We study the load balancing problem in a dense wireless multihop network, where a typical path consists of a large number of hops, that is, the spatial scales of a typical distance between source and destination and mean distance between the neighboring nodes are strongly separated. In this limit, we present a general framework for analyzing the traffic load resulting from a given set of paths and traffic demands. We formulate the load balancing problem as a minmax problem and give two lower bounds for the achievable minimal maximum traffic load. The framework is illustrated by considering the load balancing problem of uniformly distributed traffic demands in a unit disk. For this special case, we derive efficient expressions for computing the resulting traffic load for a given set of paths. By using these expressions, we are able to optimize a parameterized set of paths yielding a particularly flat traffic load distribution which decreases the maximum traffic load in the network by 40% in comparison with the shortest-path routing.