A lower bound for radio broadcast
Journal of Computer and System Sciences
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DIALM '00 Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications
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DIALM '01 Proceedings of the 5th international workshop on Discrete algorithms and methods for mobile computing and communications
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Deterministic Broadcasting Time in Radio Networks of Unknown Topology
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
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ISTCS'92 Proceedings of the Israel Symposium on Theory of Computing and Systems
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Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Timed grid routing (TIGR) bites off energy
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
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ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
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IEEE Wireless Communications
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Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Grid emulation for managing random sensor networks
Ad Hoc Networks
On Radio Broadcasting in Random Geometric Graphs
DISC '08 Proceedings of the 22nd international symposium on Distributed Computing
Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
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SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
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A common assumption in sensor networks is that the sensors are located according to a uniform random distribution. In this paper we show that uniform random points on the two dimensional unit square are almost a “grid”. In particular, for a synchronous geographic sensor network we show how to emulate any grid protocol on random sensor networks, with high probability. This suggests the following framework. In order to solve a problem on a random sensor network we solve the same problem on the grid. Then we use our emulation to make the obtained solution suitable for random sensor network. We analyze the cost of the emulation in terms of consumed energy and time. Finally we provide three examples that illustrate our method.