# Key Technologies for 6G-Enabled Smart Sustainable City
## 4 Key Candidate Technologies for Future SSC
### Prime Technologies for SSC
#### 4.2.2 Advanced Mobile Edge Computing  
With the advancement of IoT technology and machine-type communications, the number of connected devices is growing exponentially. In SSC, the internet of everything (IoE) services will emerge with the aim of improving the quality of life in urban spaces [79]. Future applications, such as extended reality (XR) and mobile holograms, will require the capabilities of extensive computations to deliver a large volume of data. When there are thin and light mobile devices, it would be challenging to satisfy the high computational requirements. Traditional centralized cloud computing can be applied to overcome the limitation of computing power in mobile devices, but there are many drawbacks, such as high latency, low spectral efficiency, and overload [80]. To overcome these drawbacks, mobile edge computing can be exploited to process high computational tasks on edge computing servers adjacent to user devices [81], as shown in Figure 3. Recently, advanced mobile edge computing, called split computing, has been introduced. With split computing, computing loads can be properly distributed among various network entities such as mobile devices, edge computing servers, and cloud data centers. For example, when the same amount of computational task is given, low-end devices, such as smart watches, offload heavy computation tasks to computation resources available in the network, while high-end mobile devices are capable of performing the necessary computation by themselves. This approach allows for the optimization of computing task efficiency by appropriately leveraging edge servers in terms of computing and storage. This optimization is achieved via collaborative scheduling of computing tasks and resource allocation [82; 83]. In the following, we discuss the key challenges in applying advanced mobile computing for 6G-enabled SSC. Figure 3: Various advanced MEC use cases on SSC. **Diverse security requirements**: Due to the limited resources of the edge nodes and their lack of intelligence against attacks, UEs connected to edge nodes are more vulnerable to attacks compared to centralized networks [84]. In addition, security requirements vary depending on the devices and applications used within the edge network. Lightweight security is required for applications with only a few functions, while robust security is required for applications that are sensitive to privacy issues or delays. Therefore, it is difficult to apply traditional security mechanisms to advanced mobile edge computing networks, which require access technologies and security mechanisms based on diverse security requirements [85]. **Privacy leakage**: To ensure secure transmissions, information should not be disclosed to parties other than the intended recipients. In this sense, the hierarchical and heterogeneous characteristics of MEC networks pose a significant privacy threat [86]. Unauthorized access to MEC nodes, for example, has the potential to compromise both privacy and network information [87]. Although the MEC architecture partitions information and access to mitigate privacy leakage, there is still a potential for privacy information leakage, including client status details, traffic statistics, and local network conditions, at the edge network [88]. Therefore, robust security and privacy measures should be implemented to counter the problem of privacy leakage in edge nodes and networks. **Mobility and resource allocation**: Note that the mobility of UE causes frequent disconnections from the edge network, which degrades the quality of service (QoS) [84]. UEs can use different network access technologies, and managing the tradeoff between energy consumption and system performance is important. Hence, efficient resource allocation via computation offloading and dynamic task partitioning is crucial, taking into account the mobility of UEs connected to edge nodes [89]. It is imperative to develop a system management architecture that enables the seamless handover of services based on the mobility of UEs.