text: The focus of this paper is on the rate and power control algorithms in Dedicated Short Range Communication (DSRC) for vehicular networks. We first propose a utility maximization framework by leveraging the well-developed network congestion control, and formulate two subproblems, one on rate control with fixed transmit powers and the other on power control with fixed rates. Distributed rate control and power control algorithms are developed to solve these two subproblems, respectively, and are proved to be asymptotically optimal. Joint rate and power control can be done by using the two algorithms in an alternating fashion. The performance enhancement of our algorithms compared with a recent rate control algorithm, called EMBARC, is evaluated by using the network simulator ns2.
  @cite_1: Cooperative inter-vehicular applications rely on the exchange of broadcast single-hop status messages among vehicles, called beacons. The aggregated load on the wireless channel due to periodic beacons can prevent the transmission of other types of messages, what is called channel congestion due to beaconing activity. In this paper we approach the problem of controlling the beaconing rate on each vehicle by modeling it as a Network Utility Maximization (NUM) problem. This allows us to formally define the notion of fairness of a beaconing rate allocation in vehicular networks. The NUM model provides a rigorous framework to design a broad family of simple and decentralized algorithms, with proved convergence guarantees to a fair allocation solution. In this context, we propose the Fair Adaptive Beaconing Rate for Intervehicular Communications (FABRIC) algorithm, which uses a particular scaled gradient projection algorithm to solve the dual of the NUM problem. Simulation results validate our approach and show that, unlike recent proposals, FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.
  @cite_8: In order for the large-scale realization of vehicular networks to be feasible, the problem of congestion control must be addressed to ensure the reliability of safety applications. The latter rely on single-hop broadcasts of safety packets in the control channel to acquire up-to-date knowledge of the local neighbourhood. However, high transmission ranges of onboard radios and the highly dynamic mobility of vehicles may result in fast-forming pockets of high node density in the network. Subsequently, the excessive load caused by safety packets broadcasts may degrade the network performance and subsequently reduce the level safety provided by applications. Existing congestion control schemes in the literature aim to reach a fair rationing of available channel resources throughout the network. However, a particular vehicle, depending on its distance and relative velocity with respect to its neighbours may require less or more network resources than another vehicle to achieve the same level of safety benefit. We examine the problem of adapting the probability of transmission of each node under a slotted p-persistent vehicular broadcast medium access control (MAC) scheme. A network utility maximization (NUM) problem is formulated, in which utility incorporates both the expected delay and a notion of safety benefit. A distributed algorithm is proposed to solve this problem in a decentralized manner and its performance is studied through simulations.
summary: A parallel work @cite_8 introduced a network utility maximization (NUM) formulation on the rate control problem when specified to safety-awareness. A distributed algorithm was proposed to adjust the rate with the objective to maximize the utility function. Similarly, @cite_1 also provided a NUM formulation on the rate control problem and proposed a fair adaptive beaconing rate for intervehicular communications (FABRIC) algorithm, which essentially is a particular scaled gradient projection algorithm to solve the dual of the NUM problem.