Proceedings of the 11th annual international conference on Mobile computing and networking
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Network adiabatic theorem: an efficient randomized protocol for contention resolution
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Towards utility-optimal random access without message passing
Wireless Communications & Mobile Computing - Recent Advances in Wireless Communications and Networks
Implementing utility-optimal CSMA
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Multichannel mesh networks: challenges and protocols
IEEE Wireless Communications
Performance of CSMA in multi-channel wireless networks
Queueing Systems: Theory and Applications
Stability and delay of distributed scheduling algorithms for networks of conflicting queues
Queueing Systems: Theory and Applications
CSMA over time-varying channels: optimality, uniqueness and limited backoff rate
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
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We consider a widely applicable model of resource allocation where two sequences of events are coupled: on a continuous time axis (t), network dynamics evolve over time. On a discrete time axis [t], certain control laws update resource allocation variables according to some proposed algorithm. The algorithmic updates, together with exogenous events out of the algorithm's control, change the network dynamics, which in turn changes the trajectory of the algorithm, thus forming a loop that couples the two sequences of events. In between the algorithmic updates at [t - 1] and [t], the network dynamics continue to evolve randomly as influenced by the previous variable settings at time [t - 1]. The standard way used to avoid the subsequent analytic difficulty is to assume the separation of timescales, which in turn unrealistically requires either slow network dynamics or high complexity algorithms. In this paper, we develop an approach that does not require separation of timescales. It is based on the use of stochastic approximation algorithms with continuous-time controlled Markov noise. We prove convergence of these algorithms without assuming timescale separation. This approach is applied to develop simple algorithms that solve the problem of utility-optimal random access in multi-channel, multiradio wireless networks.