In this paper, we propose a dynamic load balancing scheme, EdgeSafe, for provisioning Safety-as-a-Service (Safe-aaS) (Roy et al., 2018). Typically, in a Safe-aaS infrastructure, the sensor nodes are either static or mobile in nature. With the variation in the geographical location of the vehicles, the sensor nodes attached to them attain mobility. Consequently, the distance between the mobile sensor node and the edge nodes present within their vicinity changes. As the data is time-critical, it is necessary to be primarily processed at the edge nodes. Considering road transportation as the application scenario of Safe-aaS, we perform load balancing in two stages. In the first stage, we calculate the preferred capacity ratio of the edge nodes present within the communication range of the sensor nodes. We apply Markowitz Portfolio Selection Theory in the second stage to select the appropriate edge node. The profit return and risk incurred in their selection is calculated to design the portfolio of the edge nodes. Thereafter, the utility of each edge node is computed. We formulate an optimization function to obtain the minimum value of the utility of the edge nodes. Extensive simulation results show that the proposed scheme, EdgeSafe, is capable of improving the data rate by 41.37%, 35.64%, and 21.05% respectively, compared to the existing schemes, $HO$ (Park et al. , 2018), $MLB$ (Lobinger et al. , 2010), and Honeybee (Fernando et al. , 2019).