Joint optimization of link scheduling and resource allocation in cooperative vehicular networks

Abstract

Vehicular networks are a cornerstone of the envisioned intelligent transportation system (ITS) by enabling vehicles to communicate with each other via vehicle-to-vehicle (V2V) communications to overcome the current and future needs for increasing traffic safety and efficiency. In this paper, we employ the knapsack problem (KP) to formulate the problem of cooperative scheduling and radio resource management in vehicular networks for non-real time services. For the sake of maximizing sum utility (MSU) of the networks, we propose two-dimensional-multi-choice knapsack problem (2D-MCKP)-based scheduling scheme to select the coordinator vehicles for the sink vehicle and allocate radio resource to V2V and vehicle-to-infrastructure (V2I) links to solve the MSU optimization problem. Simulation results indicate that the proposed scheme significantly improves the average utility and average data rates with sustainable computational complexity. Moreover, the designed cooperative communication system achieves higher spectral efficiency and better fairness.

Cooperative Vehicular Networking: A Survey

“…Link scheduling and resource allocation as a joint optimization problem is proposed by Zheng et al [20]. They present a two-dimensional-multi-choice knapsack problem (2D-MCKP)-based scheduling scheme for 2-hop vehicular networks.…”

“…The work reported in [20] maximizes sum utility of vehicular networks by incorporating a two-dimensional multi-choice knapsack problem- based scheduling in cooperative vehicular networks. In order to cooperatively transmit failed packets of neighboring nodes, the relay nodes have to reserve time slots to transmit failed packets.…”

A Software-Defined Networking Roadside Unit Cloud Resource Management Framework for Vehicle Ad Hoc Networks

“…Tang et al have proposed an RSU empowered vehicular network that consists of three hierarchical layers-vehicular cloud, RSUenabled cloudlet, and central cloud, respectively, where RSUs are enhanced with edge servers so that the entire system can intelligently respond to the real-time resource requests [14]. Zheng et al employ the knapsack problem to formulate the problem of cooperative scheduling and radio resource management in vehicular networks, but their research only orients to the radio resources for nonreal-time services where they assume the problem in the 2-hop vehicular network, greatly restricting the application scenario [15]. eir proposed methods are not efficient enough considering the high mobility of vehicles in VANETs with strict delay requirements.…”

“…e delay on the edge matches with the load on it, where the index is used to find it in the lookup table (LUT). Equation (13) represents that the load on an edge e is mapped to a bunch of ξ. Constraint (14) ensures that the traffic load on an edge cannot exceed its capacity, where (15) and ( 16) state that there is only one specific value for the load on edge e and the delay corresponding to it.…”

Scheduling users in drive-thru Internet: a multi-armed bandit approach

“…For example, these users can be cars or pedestrians moving on (or along) a long avenue. Various question related to link-layer scheduling and resource allocation [5,6], MAC layer retransmissions [7], message scheduling using network coding [8] have recently been investigated by taking into account the specific mobility pattern of the drive-thru internet systems.…”