Task Allocation in Edge Based VANET

Abstract

As we know that in last ten years there is huge use of cloud for the storing, computation and for the historical data analysis. In present days there is more than 23 billion devices connected to cloud. These devices produced huge amount of data day-by-day. Due to the continuous generation of the data by the devices will leads to congestion in cloud, this congestion will create delay in the sharing of information or data this will affects the real time applications like VANET, health care. In this thesis work I proposed an architecture for VANET where the computation of the data shared by vehicles is done within local mesh network of the RSU’s. For the computation of the data tasks must be allocated to the RSU’s. Task allocation is important to remove many problems in distributed environment (e.g. WSN’s, VANET etc.) like use of resources in a convenient way, best allocation of resources as they are limited, etc. In this work we also give a genetic algorithm for task allocation in RSU’s. This allocation algorithm shows that how the tasks are divided within the limited amount of the RSU’s. The proposed task allocation using genetic algorithm gives 22.38% improvement in terms of fitness value and 8.34% improvement in terms of cost of energy consumption