Nowadays, data centers and servers are rising in size by order of magnitude due to increasing CCTV footages. Therefore, load balancing (LB) becomes a primary concern in scalable computing system involves mobile edge cloud computing environment. In mobile edge cloud computing system, a mobile user offloading their task to neighboring edge server for supporting realistic application. But while user is situated in a hot spot, various edge servers are over-loaded as a result of sudden offloading task from the mobile user. The LB process can be considered as an optimization problem, which can be resolved by the use of metaheuristic optimization algorithms. This article introduces an Improved Search and Rescue Optimization based LB Scheme for Edge Computing Environment (ISROLBS-ECE). The presented ISROLBS-ECE technique majorly concentrates on the distribution of offloading tasks to neighboring edge servers effectively. In addition, the ISROLBS-ECE technique involves the hybridization of chaotic concept into the conventional search and rescue optimization (SRO) approach. In the ISROLBS-ECE technique, the moderately lightest and task arrival nodes are employed as target node for allocating new task whereas rest of the nodes are not provisionally allocated tasks to accomplish dynamic balancing of the network. The experimental validation of the ISROLBS-ECE technique is tested and the outcomes are investigated under various aspects. The comparative study shows the better performance of the ISROLBS-ECE approach over other recent techniques.