Capacity of Ad Hoc wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Throughput Achievable with No Relaying in a Mobile Interference Network
ISCC '03 Proceedings of the Eighth IEEE International Symposium on Computers and Communications
Towards mobility as a network control primitive
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Movement-Assisted Sensor Deployment
IEEE Transactions on Mobile Computing
Mobility control for throughput maximization in ad hoc networks: Research Articles
Wireless Communications & Mobile Computing - Wireless Ad Hoc Networks: Technologies and Challenges
Connectivity-Guaranteed and Obstacle-Adaptive Deployment Schemes for Mobile Sensor Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Power-Law Distributions in Empirical Data
SIAM Review
End-to-end delay in wireless random networks
IEEE Communications Letters
Guest editorial: wireless communications in networked robotics
IEEE Wireless Communications
Multi-robot path finding with wireless multihop communications
IEEE Communications Magazine
The capacity of wireless networks
IEEE Transactions on Information Theory
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The performance of wireless stationary and mobile networks is known to be limited by the throughput-delay trade-off. In this paper, we exploit controlled mobility to overcome the performance limit of random networks. Although many literature on controlled mobility have studied about the optimal relay relocation algorithm to improve the throughput of individual source-destination pair, the improved throughput is limited by the capacity scale of an arbitrary network @Q(1/n). By adopting more autonomous controlled mobility, we propose a mobility control strategy achieving the constant per-node capacity scale with bounded delay. For the purpose of this, we identify the key control factors for controlled mobility by analyzing a random network. To estimate the cost-effectiveness of the proposed mobility control strategy, we provide the delay scales and the energy consumption model. Finally, we propose a heuristic mobility control algorithm to verify the applicability of our theoretic results to a practical system. Through extensive simulations, we show the proposed mobility control algorithm considerably improves the network performance.