Congestion Control for Wireless Ad-Hoc Networks

We study joint design of end-to-end congestion control and Per-link medium access control (MAC) in ad-hoc networks. In the current scenario wireless communication is emerging the world. Wireless Ad Hoc networks demands for higher intermediate node supports for long-range communication. Wireless Ad Hoc network is an emerging communication approach. Ad Hoc networks are usually defined as an autonomous system of nodes connected by wireless links and communicating in a multi-hop fashion. The wireless ad-hoc networks are for easy of deployment without centralized administration or fixed infrastructure, to achieve the goal of less interference communication. In wireless Ad-hoc network the connections between the wireless links are not fixed but dependent on channel conditions as well as the specific medium access control (MAC). The channel medium and transmission links are affected by the interference, delay, and buffer overflow these may cause the network congestion. To avoid network congestion various congestion control methods were developed in past but they were performed less control of end-to-end congestion and less in per link connection control. To overcome the above problems and to improve the resource allocation an efficient method has to be developed

Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks

This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models

Layering as Optimization Decomposition: Questions and Answers

Network protocols in layered architectures have historically been obtained on an ad-hoc basis, and much of the recent cross-layer designs are conducted through piecemeal approaches. Network protocols may instead be holistically analyzed and systematically designed as distributed solutions to some global optimization problems in the form of generalized Network Utility Maximization (NUM), providing insight on what they optimize and on the structures of network protocol stacks. In the form of 10 Questions and Answers, this paper presents a short survey of the recent efforts towards a systematic understanding of "layering" as "optimization decomposition". The overall communication network is modeled by a generalized NUM problem, each layer corresponds to a decomposed subproblem, and the interfaces among layers are quantified as functions of the optimization variables coordinating the subproblems. Furthermore, there are many alternative decompositions, each leading to a different layering architecture. Industry adoption of this unifying framework has also started. Here we summarize the current status of horizontal decomposition into distributed computation and vertical decomposition into functional modules such as congestion control, routing, scheduling, random access, power control, and coding. We also discuss under-explored future research directions in this area. More importantly than proposing any particular crosslayer design, this framework is working towards a mathematical foundation of network architectures and the design process of modularization

Distributed Adaptive Algorithms for Optimal Opportunistic Medium Access

We examine threshold-based transmission strategies for distributed opportunistic medium access in a scenario with fairly general probabilistic interference conditions. Specifically, collisions between concurrent transmissions are governed by arbitrary probabilities, allowing for a form of channel capture and covering binary interference constraints as an important special case. We address the problem of setting the threshold values so as to optimize the aggregate throughput utility of the various users, and particularly focus on a weighted logarithmic throughput utility function (Proportional Fairness). We provide an adaptive algorithm for finding the optimal threshold values in a distributed fashion, and rigorously establish the convergence of the proposed algorithm under mild statistical assumptions. Moreover, we discuss how the algorithm may be adapted to achieve packet-level stability with only limited exchange of queue length information among the various users. We also conduct extensive numerical experiments to corroborate the theoretical convergence results.14 page(s

Cross-layer rate control for end-to-end proportional fairness in wireless networks with random access

In this paper, we address the rate control problem in a multihop random access wireless network, with the objective of achieving proportional fairness amongst the end-to-end sessions. The problem is considered in the framework of nonlinear optimization. Compared to its counterpart in a wired network where link capacities are assumed to be fixed, rate control in a multi-hop random access network is much more complex and requires joint optimization at both the transport layer and the link layer. This is due to the fact that the attainable throughput on each link in the network is ‘elastic’ and is typically a non-convex and non-separable function of the transmission attempt rates. Two cross-layer algorithms, a dual based algorithm and a primal based algorithm, are proposed in this paper to solve the rate control problem in a multi-hop random access network. Both algorithms can be implemented in a distributed manner, and work at the link layer to adjust link attempt probabilities and at the transport layer to adjust session rates. We prove rigorously that the two proposed algorithms converge to the globally optimal solutions. Simulation results are provided to support our conclusions

Throughput Optimization in Multi-hop Wireless Networks with Random Access

This research investigates cross-layer design in multi-hop wireless networks with random access. Due to the complexity of the problem, we study cross-layer design with a simple slotted ALOHA medium access control (MAC) protocol without considering any network dynamics. Firstly, we study the optimal joint configuration of routing and MAC parameters in slotted ALOHA based wireless networks under a signal to interference plus noise ratio based physical interference model. We formulate a joint routing and MAC (JRM) optimization problem under a saturation assumption to determine the optimal max-min throughput of the flows and the optimal configuration of routing and MAC parameters. The JRM optimization problem is a complex non-convex problem. We solve it by an iterated optimal search (IOS) technique and validate our model via simulation. Via numerical and simulation results, we show that JRM design provides a significant throughput gain over a default configuration in a slotted ALOHA based wireless network. Next, we study the optimal joint configuration of routing, MAC, and network coding in wireless mesh networks using an XOR-like network coding without opportunistic listening. We reformulate the JRM optimization problem to include the simple network coding and obtain a more complex non-convex problem. Similar to the JRM problem, we solve it by the IOS technique and validate our model via simulation. Numerical and simulation results for different networks illustrate that (i) the jointly optimized configuration provides a remarkable throughput gain with respect to a default configuration in a slotted ALOHA system with network coding and (ii) the throughput gain obtained by the simple network coding is significant, especially at low transmission power, i.e., the gain obtained by jointly optimizing routing, MAC, and network coding is significant even when compared to an optimized network without network coding. We then show that, in a mesh network, a significant fraction of the throughput gain for network coding can be obtained by limiting network coding to nodes directly adjacent to the gateway. Next, we propose simple heuristics to configure slotted ALOHA based wireless networks without and with network coding. These heuristics are extensively evaluated via simulation and found to be very efficient. We also formulate problems to jointly configure not only the routing and MAC parameters but also the transmission rate parameters in multi-rate slotted ALOHA systems without and with network coding. We compare the performance of multi-rate and single rate systems via numerical results. We model the energy consumption in terms of slotted ALOHA system parameters. We found out that the energy consumption for various cross-layer systems, i.e., single rate and multi-rate slotted ALOHA systems without and with network coding, are very close