Efficiently using the network resources of Mobile Ad-hoc NETworks (MANETs) is challenging. The absence of a centralized administration leads to a congestion problem (Transport layer). The flows are usually routed through shortest routes, typically through the same central part of the network (Network layer). Communicating via shared wireless links raises a contention problem (MAC layer). Multi-hop transmissions cause flows not only to interfere with each other, but also with themselves.
We focus on jointly solving the contention and congestion distributed control problem in a bounded queue MANETs. The resulting flow rates satisfy fairness criteria according to a given Network Utility Maximization (NUM) function. In recent years a number of papers have presented solutions to the same problem based on NUM algorithms. However, this work typically necessitates either complex computations, heavy signaling/control overhead, and/or approximated sub-optimal results. In this work, we employ and adapt the IEEE 802.11 protocol in the NUM with a simple and efficient queue management mechanism. Unlike the majority of the published work in this area, we focus on the feasibility of the proposed solution in case of random static and mobile networks considering the overheads and the signaling methods.
We propose a novel algorithm that jointly solves the congestion, multipath routing, and contention distributed control problem for MANETs. The objective is to find the end-to-end optimal source rates at the transport layer, sub-flow rates for each path of the multipath sessions at the network layer, and persistence probability at the MAC layer. The primal problem formulation is a non-convex, non-separable NUM optimization. By introducing new variables, applying certain transformations, and using an analogy based on Ohm's law, we develop a distributed algorithm that can find the optimal solution for general concave utility functions.
The algorithms are implemented in NS-3 and evaluated against non-idealistic scenarios, i.e. link failures, message losses, asynchronous updates, and with the presence of inaccurate topology information. We evaluate the overhead and signaling associated with the algorithms quantitatively and qualitatively and provide absolute gain values. The results show that the proposed algorithms significantly outperforms layered approaches, using standard protocols such as TFRC.