Interperf '06 Proceedings from the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer & communications sytems
On traffic load distribution and load balancing in dense wireless multihop networks
EURASIP Journal on Wireless Communications and Networking
On optimality of single-path routes in massively dense wireless multi-hop networks
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Computer Networks: The International Journal of Computer and Telecommunications Networking
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Mathematics of Routing in Massively Dense Ad-Hoc Networks
ADHOC-NOW '08 Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks
On the optimality of field-line routing in massively dense wireless multi-hop networks
Performance Evaluation
Numerical solutions of continuum equilibria for routing in dense ad-hoc networks
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
Structured and real time heterogeneous sensor deployment in preferential areas
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Energy spaced placement for bidirectional data flows in wireless sensor network
IEEE Communications Letters
Lattice green functions and diffusion for modeling traffic routing in ad hoc networks
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Continuum equilibria and global optimization for routing in dense static ad hoc networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Wireless Innovations as Enablers for Complex & Dynamic Artificial Systems
Wireless Personal Communications: An International Journal
Multiobjective K-connected deployment and power assignment in WSNs using constraint handling
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Implementing information paths in a dense wireless sensor network
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Magnetworks: how mobility impacts the design of mobile ad hoc networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Combining trust with location information for routing in wireless sensor networks
Wireless Communications & Mobile Computing
Hi-index | 754.84 |
A spatially distributed set of sources is creating data that must be delivered to a spatially distributed set of sinks. A network of wireless nodes is responsible for sensing the data at the sources, transporting them over a wireless channel, and delivering them to the sinks. The problem is to find the optimal placement of nodes, so that a minimum number of them is needed. The critical assumption is made that the network is massively dense, i.e., there are so many sources, sinks, and wireless nodes, that it does not make sense to discuss in terms of microscopic parameters, such as their individual placements, but rather in terms of macroscopic parameters, such as their spatial densities. Assuming a particular interference-limited, capacity-achieving physical layer, and specifying that nodes only need to transport the data (and not to sense them at the sources, or deliver them at the sinks once their location is reached), the optimal node placement induces a traffic flow that is identical to the electrostatic field created if the sources and sinks are replaced by a corresponding distribution of positive and negative charges. Assuming a general model for the physical layer, and specifying that nodes must not only transport the data, but also sense them at the sources and deliver them at the sinks, the optimal placement of nodes is given by a scalar nonlinear partial differential equation found by calculus of variations techniques. The proposed formulation and derived equations can help in the design of large wireless sensor networks that are deployed in the most efficient manner, not only avoiding the formation of bottlenecks, but also striking the optimal balance between reducing congestion and having the data packets follow short routes.