# A Survey on IoT-Edge-Cloud Continuum Systems: Status, Challenges, Use Cases, and Open Issues
## 4 Recent Works in IoT-Edge-Cloud Continuum Architectures  
In this section, all recent advances in the area of IEC continuum systems are presented. In this context, in [75], hybrid cloud deployments for supporting data-intensive, 5G-enabled IoT applications were investigated. Moreover, a decentralized hybrid cloud MEC architecture, resulting in a Platform-as-a-Service (PaaS) is proposed and its main building blocks and layers are thoroughly described. In this context, a security and privacy module makes anomaly detection, anonymization, encryption, and identity management feasible. In addition, serverless computing is supported along with AI optimization. Moreover, two indicative use cases are provided, in particular a smart city scenario as well as e-health applications. Due to the PaaS deployment of the proposed architecture, potential stakeholders and business models are identified as well. In [76], an IEC framework is proposed and evaluated for the visual control of IoT devices in a user's smartphone. This approach couples various technologies for DNS naming and indoor localization to support the visual control of IoT devices. To this end, the DNS Name Autoconfiguration (DNSNA)  
Figure 8: IEC cloud architecture in a maritime environment for just-in-time arrival and ML model training [17]. for IoT devices is used, where an IoT device is registered to a router that sends a broadcast message. Afterwards, a unique DNS name and IPv6 address are generated for the specific IoT device. Localization is based on periodic WiFi beacon messages from the smartphone and the received signal strength indicator (RSSI) value for such a beacon message that is received by each IoT device. In the same context, open research challenges were identified as well, such as secure communications among the user terminal and the involved IoT devices, as well as an extension of the proposed approach in multiuser scenarios. In [77], the UNITE architecture was described, where all available resources across the entire IEC architecture are classified into three major classes: computing, networking, and storage. To this end, holistic resource monitoring and management takes place, where the UNITE framework evaluates certain KPIs, such as latency or throughput. If one of these KPIs falls below a predefined value, then the appropriate actions take place (e.g., application migration, network rerouting, etc.) transparently to the end user. Moreover, the UNITE framework allows agnostic application development, which is not bound to any specific running environment. In [78], an optimized IoT-enabled big data analytics architecture for edge-cloud computing using ML is proposed and evaluated. The considered scheme is composed of two layers, i.e., IoT-edge and cloud processing. In this context, an edge intelligence node is introduced, which handles and stores big amounts of data at the edges of the network with the integration of cloud technology. The proposed data design is experimentally simulated with an authentic data set using Apache Spark. In [79], the goal is to combine edge and cloud computing for IoT data analytics by taking advantage of edge nodes to reduce data transfer. In order to process data close to the source, sensors are grouped according to their locations, and feature learning is performed on the node that is closer to the edge. The results showed that transmission data and the corresponding network traffic could be reduced even up to about 80% without significant loss of accuracy. In [80], a sharing resource allocation problem among multiple service providers in the edge-cloud is investigated. In this context, the authors study distributed algorithms to find a near-optimal solution with fast convergence. In particular, the dual decomposition and alternating direction method of multipliers were used. In [81], the concept of volunteer edge-cloud was introduced, where blockchain technology is used to deal with the problem of service payment and data credibility in a decentralized system.