# A Survey on Modeling Languages for Applications Hosted on Cloud-Edge Computing Environments
## 4 Conclusions and Future Research Directions  
### Main Findings  
Based on the findings presented in Section 3 and summarized in Tables 3 and 4, the main conclusion is that there is no single CML that can fully support all the concepts of edge-cloud computing. This work highlights the ongoing effort from academia to extent existing CMLs to address the limitations of existing solutions in terms of meeting the demands of developers for effortless application migration to cloud-edge continuum environments. Particularly, researchers frequently utilize and extend TOSCA, CAMEL [1], and HOT due to their effectiveness in describing a wide range of concepts within existing CMLs. TOSCA typically serve as the baseline for creating new CMLs tailored to novel requirements. The availability of analytical documentation further enhances the popularity and widespread adoption of TOSCA among researchers. In our survey, we examine five TOSCA extensions [17; 18; 30; 32], one HOT extension [27], and identify no CAMEL extensions. On the other hand, HOT does not provide straightforward extension capabilities for researchers as it lacks cloud-agnosticism and focuses solely on virtual machine descriptions. While CAMEL provides robust support for orchestrating multiple cloud providers, it lacks comprehensive documentation on extension methodologies. Our results showcase that TOSCA offers a rich set of generic entities that can be extended to describe diverse aspects, making it a perfect candidate among the existing CMLs to be used in multiple cloud-edge platforms for deployment and runtime adaptation descriptions. In edge-cloud computing, the placement of application components plays a vital role, but only a few CMLs support it as a deployment criterion. Among the 22 CMLs, only 6 support this crucial feature, which is considered highly significant for cloud edge continuum platforms. In particular, TOSCA IOT ext. [18], ADOx Definition Language [36], SMADA-Fog [12], TOSCA for Edge and Fog [20], FRACTAL4 EDGE in [35] and Self-adaptive IoT DSL [21] are the only sources that provide comprehensive semantics beneficial for orchestrating cloud edge continuum platforms. The observation that only 27.2% of the languages analyzed permit developers to specify whether their application components should be deployed on the edge or in a cloud environment highlights the need for further research to address the lack of support for this feature. Similarly, the representation of runtime adaptation is supported by more than half of the presented CMLs. Among the 22 CMLs discussed, 12 (EDDM [7], TOSCA light [30], Wrangler [25], CAMEL [1, 31], TOSCA lifecycle ext. [32], TOSCA MICADO [17], TOSCA for Edge and Fog [20], SMADA-Fog [12], Self-adaptive IoT DSL [21], GENTL [9], TOSCA and MoDMaCAO [23]) possess the capability to describe QoS criteria in different formats. Based on our analysis in Section 3.9, SYBL [34], Self-adaptive IoT DSL [21], ADOxx Definition Language [36], CAMEL [1], HOT, SMADA-Fog [12] and HOT extension [27] are seven of these languages that exhibit a condition syntax suitable for event-driven logic based on QoS rules. While GENTL [9] does not inherently support this description, it can achieve it by utilizing lower-level languages given its nature as a high-level language. Developers need to consider both the requirements of the target platform/provider and their own preferences when selecting a CML to describe runtime adaptation, as there are various supported syntaxes available. This presents an ongoing issue, as researchers may introduce a syntax in the future that could potentially supersede the others. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**TOSCA IOT nt.