Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
Geometry of information propagation in massively dense ad hoc networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Characterizing achievable rates in multi-hop wireless mesh networks with orthogonal channels
IEEE/ACM Transactions on Networking (TON)
Scheduling Efficiency of Distributed Greedy Scheduling Algorithms in Wireless Networks
IEEE Transactions on Mobile Computing
Balancing traffic load in wireless networks with curveball routing
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
On the optimality of field-line routing in massively dense wireless multi-hop networks
Performance Evaluation
Approximating maximum directed flow in a large wireless network
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
On the achievable forwarding capacity of an infinite wireless network
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
A distributed CSMA algorithm for throughput and utility maximization in wireless networks
IEEE/ACM Transactions on Networking (TON)
The capacity of wireless networks
IEEE Transactions on Information Theory
Closing the Gap in the Capacity of Wireless Networks Via Percolation Theory
IEEE Transactions on Information Theory
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The problem of the capacity of a massively dense wireless multihop network can be broken down into separate problems at macroscopic and microscopic levels. At the microscopic level, from the local perspective, the network appears like an infinite plane with traffic that is uniform but flowing in many directions. Previous studies have assumed that it is sufficient to find the maximum sustainable density of packet flow in a single direction and use time sharing to serve flows in different directions. We show that this time-sharing limit can be exceeded by scheduling that truly interleaves the traffic flows in different directions. Determining the forwarding capacity for multidirectional traffic defines a new problem that has not been studied earlier. For finding numerical values, we adopt a constructive approach by simulating a finite but large network using greedy maximum weight scheduling. Bi- and four-directional balanced traffic patterns are studied. For the latter, an improved greedy algorithm is developed, using insights from our earlier work. Isotropic traffic plausibly yields the highest benefits for multidirectional forwarding, and our results show that a significant gain compared with single-directional forwarding can be achieved.