# Digital Twins, Virtual Devices, and Augmentations for Self-Organising Cyber-Physical Collectives +
## 3 Motivation and Related Work
### Summary and Related Work  
In a nutshell, the motivation of the proposed _augmented CDT_ notion has two parts:  
1. _Motivation for the CDT notion_. Taking a collective viewpoint leverages abstracting groups of devices (cf. virtual aggregates in Table 1) and \"macro-programming\" groups of devices, as discussed previously in this section. This aligns with approaches like aggregate computing that are explicitly designed to address the global behaviour of collective adaptive and self-organising systems. 2. _Motivation for the \"augmentation\" of CDTs_. The part of augmentation leverages on concepts proposed in the literature, such as virtual agents, that are exploited for soft control of swarms [13; 14]. Therefore, the novel concept of augmented CDT integrates the collective viewpoint with augmentation, making it--we believe--especially interesting and a useful contribution towards tackling some challenges of self-organising CPS engineering. Our proposal differs from related work for it provides an integrated approach that considers: (i) a meta-model where logical entities are decoupled from physical entities (see Section 4 for details)--like in [32; 33]; (ii) a distinction between identity and execution relationships, allowing to distinguish between digital twins and virtual devices; and (iii) a collective computing approach whereby the focus is on collective-level behaviour, rather than individual behaviour (so, e.g., we do not assume behavioural differences between digital twins and virtual devices). * **Models for self-organising Cyber-Physical Systems. **  
Figure 2: Pictorial representation of the crowd-aware navigation scenario. Physical devices are depicted with a solid square, logical devices are depicted with a dashed circle; an overlap of the two indicates that a logical device is associated to a physical device, a circle outside any box denotes a purely virtual device. Nodes sensing overcrowding are depicted in grey, the requester is coloured in blue, and the PoI is filled in red. The requester desires to reach the red device, walking along a path that can avoid overcrowded areas. Considering solely the physical devices as part of the system, no available route can be computed in a self-organising way; however, by populating the system with virtual nodes, a route circumventing the problematic area can still be found. The system could also (in principle) continuously look at strategies to self-improve such an integration for non-functional benefits. The approach aims to provide a structure for self-organising collective systems. This is in contrast with approaches that distinguish between _managed system_ and _managing system_--the latter being typically organised around the MAPE-K pattern [3]. In particular, there are similarities with the idea of _self-organising software models_[32], where the goal is to reduce the need for manual composition. In our case, we assume a composition of collective behaviours is specified by a developer (e.g., using aggregate programming), and let the platform deal automatically with deployment and possibly with the de/augmentation (management of virtual devices) for example, given high-level goal specifications. A similar approach for separating cyber entities from physical entities as well as other responsibilities when modelling self-organising Cyber-Physical Systems is provided in [33], with a focus on production systems; however, it somewhat neglects the collective viewpoint, and does not clarify a difference between digital twins and virtual devices.