Up to date, Social Internet of Things (SIoT) and Fog Computing (FC) are two standing-alone technological paradigms under the realm of the Future Internet. SIoT relies on the self-establishment and self-management of inter-thing social relationships, in order to guarantee scalability to large IoT networks composed by both human and non-human agents. FC extends cloud capabilities to the access network, in order to allow resource-poor IoT devices to support delay-sensitive applications. Motivated by these complementary features of the SIoT and FC models, the two-year project "Fog of Social IoT (SoFT): when the Fog becomes social" aims at proposing their integration into the novel SoFT platform.
Specifically, FC natively supports three main services, namely, thing virtualization, Thing-to-Fog task offloading and inter-Fog resource pooling. In principle, these services could be efficiently exploited, in order to implement the SIoT social network as an overlay network of thing clones, that entirely relies on the bandwidth/computing resources of the supporting Fog Nodes. So doing, the native resources of the physical things could be employed only for the synchronization with the corresponding Fog-hosted clones. This is, indeed, the main idea behind the proposed SoFT paradigm.
Overall, main goals of the SoFT project are to:
i) formalize the main building blocks and functionalities of the proposed SoFT technological platform. It merges the physical things at the IoT layer and their virtual clones at the Fog layer into a cyber-physical overlay network of social clones;
ii) design and validate through software simulations the performance of a small-scale SoFT prototype, and compare its energy-vs.-delay performance with the corresponding ones of the state-of-the-art; and,
iii) design and validate through software simulations novel distributed machine learning and deep learning algorithms for the analysis and forecasting of Big Data diffusion through the SoFT social network.
4) INNOVATIVE EXPECTED PROJECT OUTPUTS AND EXPECTED POTENTIAL TECHNO-SOCIAL IMPACT
The SoFT technological platform is expected to quickly foster the development of Fog-supported Future Internet Applications [8], that are considered a world-wide huge business opportunity (Fig.2). In particular, it is foreseen that the Fog related outputs could move from the research cycle to prototype cycle in the next years (Fig.2). In the following, we detail the main technological and social impact of the proposed SoFT project.
Expected Technological Impact: The proposed SoFT project is expected to have a significant positive impact on the development of future low-latency and energy-aware application inspired by the FC and SIoT paradigms. This is expected to have a relevant technological impact on many novel families of technologies, such as Smart Wireless Sensor Networks (SWSNs), Smart Objects of IoT and Intelligent Embedded Systems. Overall, it is expected that proposed SoFT research permit to enter a new phase where real-world problems emerging from complex IoT applications are addressed.
Expected Social Impact: It is expected that intelligent and green FC platforms are able to provide more robust, energy-efficient and higher QoS and, for this reason, are expected to increase the trust people have in machine-related and real-time critical applications. Furthermore, the novel SoFT platform would enable to quickly acquire a full awareness about hazards and situations that cannot be foreseen and promptly activate appropriate countermeasures. Overall, the proposed SoFT platform will be of paramount to enable and efficiently support a wide class of IoT-involving application scenarios, all having a high significant social impact, e.g. smart grid where energy load balancing applications may run on end-devices at the edge of network to autonomously switch to alternative energies, i.e. solar, wind-based, on energy demand, availability, environment conditions and economic convenience.
5) PROJECT PLAN AND PROJECT TARGETS
The two-year research activity of the overall SoFT workprogramme is organized into two Workpackages (e.g., WP.1 and WP.2), coordinated by Prof. E. Baccarelli (DIET Dpt.) and Prof. M. Scarpiniti (DIET Dpt.), respectively. As detailed in Table III, each WP comprises two tasks.
The SoFT project will be coordinated by Prof. Enzo Baccarelli. The team of 5 researchers (3 promoters supported by 2 PhD researchers) is organized into two Research Units located at the DIET Dpt. The multiple scientific sectors involved by the SoFT project (ING-INF/03 and ING-IND/31) confirm, indeed, the inter-disciplinary nature of the SoFT project. Table IV details the role/task covered by each participant, together with the planned workprogramme over the TWO-year life cycle of the project, and related cross-interactions.
T1.1 - Minimum-energy wireless live migration of SoFT clones under hard delay constraints -- Main task of the SoFT technological platform of Fig. 1 is to exploit the computing/networking resource virtualization by augmenting the limited resources of each IoT wireless device through the seamless live (e.g., real-time) migration of Virtual Machines (VMs) towards the serving Fog data center over the underlying Fog Radio Access Network (shortly, the FOGRAN). In principle, for this purpose, the bandwidths of the multiple Wireless Network Interface Cards (WNICs) typically equipping each wireless device could be aggregated (e.g., used in parallel) under the control of the emerging MultiPathTCP (MPTCP) protocol [11,12,13]. However, due to fading and mobility-induced phenomena, the energy consumptions of current state-of-the-art VM migration techniques may still offset their expected benefits [9]. Motivated by these considerations, goal of the T1.1 task is to design and numerically test the optimal minimum-energy Settable-Complexity Bandwidth Manager (SCBM) for the live migration of VMs over the FOGRAN MPTCP connections of the envisioned SoFT technological platform of Fig. 1. The key expected features of the proposed SCBM would be that: (i) its implementation complexity would be settable on-line, according to the energy consumption-vs.-implementation complexity tradeoff targeted by the wireless device; (ii) it would minimize the network energy consumed by the wireless device for sustaining the migration process under hard constraints on the tolerated migration times and downtimes; and, (iii) by leveraging a suitably designed adaptive mechanism, it would be capable to quickly react to (possibly, unpredicted) fading and/or mobility-induced abrupt changes of the wireless environment without requiring forecasting. Furthermore, in the case in which the required research grant would be funded, additional goals of this T1.1 task will be: (i) the implementation in software of the designed SCBM; and, (ii) the test of the actual energy-vs.-delay performance of the proposed SCBM through extensive trials.