1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science, Dongduk Women's University, Seoul 02748, Korea  
[EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.); [EMAIL_ADDRESS] (H.Y.) 1 Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea;  
[EMAIL_ADDRESS] (H.C.  
composed of many mobile devices, a smaller number of edge cloud servers, and one central cloud server [2]. For example, when a user executes a task on his/her device, if the processing power of the device is insufficient to perform the task, it is offloaded to an edge server. If the processing power on the edge cloud server is not sufficient enough, the task is offloaded to the central cloud server. This system provides applications with ultra-low latency, high-bandwidth, and real-time access to network information. Currently, standardization of MEC is being performed by the European Telecommunications Standards Institute, while the industrial world is attempting to develop long-term evolution in mobile networks. Additionally, MEC technology is emerging as the core technology for 5G networks that will be introduced within the next decade, with software-defined networks and network function virtualization as auxiliary technologies [3]. Although research on MEC has been very active, there are certain limitations in handling real-time services requiring strict adherence to response time standards [4]. In general, an application service can be classified as a latency-sensitive service or a latency-tolerant service according to the urgency level of task end-time violation [5; 6; 7; 8]. A service ought to be distinguished as a latency-sensitive service that must adhere to deadlines or a latency-tolerant service that may be allowed to violate a deadline by an arbitrary amount. In latency-sensitive services, such as autonomous driving services, one second of delay could have serious consequences--the service must be terminated within a deadline. However, in current MEC systems, it is not possible to guarantee the task-end time of services with real-time properties because resources are allocated to all virtual machines without considering the characteristics of these applications. For example, assume that a latency-sensitive service and a latency-tolerant service are running on the same server. If computing resources are allocated to the virtual machine performing the latency-tolerant service first, the latency-sensitive service will not be guaranteed to meet the task deadline. Additionally, if the tasks of latency-sensitive services, whose deadline is close, are offloaded without considering those deadlines, a deadline violation will be incurred, and the service's real-time availability will not be guaranteed. In this paper, we propose a novel latency-classification-based deadline-aware task offloading algorithm (LCDA) for MEC environments to solve the problems discussed above. The MEC environments of the proposed algorithm and the performance evaluation are as follows. The devices (users) randomly move the path and upload and download data by accessing the AP of one of the edge cloud servers in a WLAN (wireless local area network).