Distributed Resource Allocation for V2V Communications in D2D Networks Using MapReduce-Based Ant Colony Optimization

Vehicle-to-Vehicle (V2V) technology-based Device-to-Device (D2D) communication has become a potential paradigm for enhancing the effectiveness and quality of wireless network connection. However, because of the dynamic nature of the network, resource limitations, and the requirement for efficient use of network resources, resource allocation for V2V communication in D2D networks is a difficult topic. The distribution of resources for vehicle-to-vehicle (V2V) communications and quality of service (QoS)—including data rate, sum time, and average interference is problem. For V2V communications in D2D networks, a distributed resource allocation approach based on MapReduce and Ant Colony Optimization (ACO) is described in this paper. The suggested method takes into account a number of network factors, including interference, sum time, and data rates, in order to improve resource allocation. An effective metaheuristic approach method for resource allocation optimization of network aggregation rate while maintaining (QoS) standards is the ACO swarm intelligence algorithm. In comparison to alternative methods, the simulation results demonstrated a notable increase in resource allocation performance. Data transfer rates were improved by 5% and reached (77,832) bits compared to 30 pairs of D2D during a sum time period of (1 ms), and the average interference also decreased (− 63.5). The less interference, the greater, it increases the probability of resource allocation.