Distributed computing approach to optimize road traffic simulation

Distributed computing is the method of running CPU intensive computations on multiple computers collectively in order to achieve a common objective. Common problems that can be solved on the distributed systems include climate/weather modeling, earthquake simulation, evolutionary computing problems and so on. These type of problems may involve billions or even trillions of computations. A single computer is not capable to finish these computations in short span of time, which is typically in days. Distributed computation helps to solve these problems in hours, which could take weeks to solve on a single computer. Distributed computing generally uses the existing resources of the organization. Traffic simulation is the process of simulating transportation systems through software on a virtual road network. Traffic simulation helps in analyzing city traffic at different time intervals of a single day. Common use cases could be analyzing city wide traffic, estimating traffic demand at a particular traffic junction and so on. This paper discusses about the approach to use distributed computing paradigm for optimizing the traffic simulations. Optimizing simulations involves running a number of traffic simulations followed by estimating the nearness of that simulation to the real available traffic data. This real data could be obtained by either manual counting at traffic junctions, or using the probes such as loop inductors, CCTV cameras etc. This distributed computing based approach works to find the best traffic simulation corresponding to the real data in hand, using evolutionary computing technique.