Data networks
Large Tandem Queueing Networks with Blocking
Queueing Systems: Theory and Applications
Scalability of wireless networks
IEEE/ACM Transactions on Networking (TON)
The capacity of wireless networks
IEEE Transactions on Information Theory
On throughput in stochastic linear loss networks
ACM SIGMETRICS Performance Evaluation Review
Improved approximations for the Erlang loss model
Queueing Systems: Theory and Applications
Elucidating the instability of random access wireless Mesh networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
A hierarchical and topological classification of linear sensor networks
WTS'09 Proceedings of the 2009 conference on Wireless Telecommunications Symposium
Performance management of IT services delivery
ACM SIGMETRICS Performance Evaluation Review
An ad-hoc unicursal protocol for stable and long-lived communication systems in disaster situations
International Journal of Knowledge and Web Intelligence
Linear wireless sensor networks: Classification and applications
Journal of Network and Computer Applications
Tandem queueing networks with neighbor blocking and back-offs
Queueing Systems: Theory and Applications
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This paper investigates fundamental properties of throughput and energy cost in large wireless linear networks with very limited local resources that do not grow with the size of the network. The maximum throughput of the network is derived and the arrival process that maximizes throughput, given a fixed arrival rate, is established. An asymptotically critical loading regime is identified such that the probability of an arbitrary packet being lost is strictly within (0, 1) as the network size increases. Such a regime delivers throughput comparable to the maximum at a reasonable energy cost. The paper also establishes the asymptotic network energy cost under this critical loading. These results are then used to consider a performance-cost tradeoff within an optimization problem for which the unique equilibrium point that maximizes the difference between performance benefits and costs is derived. Finally, from a mathematical perspective, the paper furthers our understanding of large stochastic linear networks for which, in general, no explicit solutions have been previously available.