Utility-optimal random access without message passing

Abstract

Abstract-Random access has been studied for decades as a simple and practical wireless medium access control (MAC). Some of the recently developed distributed scheduling algorithms for throughput or utility maximization also take the form of random access, although extensive message passing among the nodes is required. In this paper, we would like to answer this question: is it possible to design a MAC algorithm that can achieve the optimal network utility without message passing? We provide the first positive answer to this question through a simple Aloha-type random access protocol. We prove the convergence of our algorithm for certain sufficient conditions on the system parameters, e.g., with a large enough user population. If each wireless node is capable of decoding the source MAC address of the transmitter from the interferring signal, then our algorithm indeed converges to the global optimal solution of the NUM problem. If such decoding is inaccurate, then the algorithm still converges, although optimality may not be always guaranteed. Proof of these surprisingly strong performance properties of our simple random access algorithm leverages the idea from distributed learning: each node can learn as much about the contention environment through the history of collision as through instantaneous but explicit message passing.

Cross-layer design with optimal dynamic gateway selection for wireless mesh networks

“…Utility functions are generally assumed to be increasing and concave, which is a conventional means of measuring throughput and fairness. In this paper, we set g ðf Þ ðÁÞ to be logðÁÞ as usually done in literature [19][20][21][22][23] We denote the solution of the above NUM problem byr à . In previous works [19][20][21][22][23], similar NUM problems have been formulated and different joint rate control, routing and scheduling algorithms (later referred to as CLC algorithms) have been proposed.…”

“…Note that the problem above has a similar form to the routing and scheduling problem in cross-layer literature [19][20][21][22][23]27]. However, the organization of packets is essentially different.…”

“…In contrast to heuristic-based approaches, cross-layer design provides a systematic theory-driven framework to develop performance-optimal data transmission control mechanisms for wireless multihop networks including WMNs. Following the seminal work of Tassiulas and Ephremides in [18], significant progress has been made on cross-layer control algorithms (see [19][20][21][22][23][24][25][26] and the references therein). It has been proven that cross-layer control algorithms can fully explore the capacity region of a network so as to guarantee maximum network utility, 1 that is, cross-layer control algorithms can achieve maximal overall throughput and at the same http://dx.doi.org/10.1016/j.comcom.2014.08.011 0140-3664/Ó 2014 Elsevier B.V. All rights reserved.…”

Fairness for All, Rate Allocation for Mobile Wireless Networks

“…On the contrary, we are interested in attaining a range of fairness trade-offs. An algorithm that operates optimally without message-passing has also been proposed by Mohsenian-Rad et al [12]. The applicability of the solution is however limited to complete networks, whereas we require a solution for arbitrary topologies.…”

Competition of wireless providers for atomic users: Equilibrium and social optimality

“…It is satisfied by some commonly used utility functions (such as log(1 + x) and the α−fairness [36]). Based on this assumption, the providers maximize their profit when demand equals the supply.…”