The vision of NEPHELE is to enable the efficient, reliable and secure end-to-end orchestration of hyper-distributed applications over programmable infrastructure that is spanning across the compute continuum from Cloud-to-Edge-to-IoT, removing existing openness and interoperability barriers in the convergence of IoT technologies against cloud and edge computing orchestration platforms, and introducing automation and decentralized intelligence mechanisms powered by 5G and distributed AI technologies.
The NEPHELE project aims to introduce two core innovations, namely:
(i) an IoT and edge computing software stack for leveraging virtualization of IoT devices at the edge part of the infrastructure and supporting openness and interoperability aspects in a device-independent way. Through this software stack, management of a wide range of IoT devices and platforms can be realised in a unified way, avoiding the usage of middleware platforms, while edge computing functionalities can be offered on demand to efficiently support IoT applications’ operations.
(ii) a synergetic meta-orchestration framework for managing the coordination between cloud and edge computing orchestration platforms, through high-level scheduling supervision and definition, based on the adoption of a “system of systems” approach.
The NEPHELE outcomes are going to be demonstrated, validated and evaluated in a set of use cases across various vertical industries, including areas such as disaster management, logistic operations in ports, energy management in smart buildings and remote healthcare services. Two successive open calls will also take place, while a wide open-source community is envisaged to be created for supporting the NEPHELE outcomes.
We participate in the project in cooperation with the NetCloud Group of University of Macedonia.
The overall aim of CODECO is to contribute to a smoother and more flexible support of services across the Edge-Cloud continuum via the creation of a novel, cognitive Edge-Cloud management framework. CODECO will implement software toolkits suitable for a smarter management of highly distributed environments based on heterogeneous networks and integrating mobile, resource-constrained devices. The CODECO components shall extend management and orchestration of Edge-Cloud services with cognitive cross-layer adaptability and with features that allow for intelligent decisions about computational offloading and network adaptation, while taking into consideration application requirements, networking requirements, data security and sensitivity, as well as other context specific aspects related with the data flow, which may emerge.
CODECO aims at providing support for the next generation of smart services, focusing on dense deployments in B5G/6G services. For this, CODECO considers multiple use-cases across different vertical domains (Smart Cities, Manufacturing, Energy and Smart Facilities), involving mobile, far Edge devices and addressing the IoT-Edge-Cloud orchestration based on a cross-layer approach that envisions data, compute, and network adaptation.
We participate in the project in association with ATHENA Research and Innovation Center.
The NECOS project addresses the limitations of current cloud computing infrastructures to respond to the demand of new services, as presented in two use-cases, that will drive the whole execution of the project. The first use-case is Telco service provider focused and is oriented towards the adoption of cloud computing in their large networks. The second use-case is targeting the use of edge clouds to support devices with low computation and storage capacity. The envisaged solution is based on a new concept “Lightweight Slice Defined Cloud (LSDC)” as an approach that extends the virtualization to all the resources in the involved networks and data centers and provides a uniform management with a high-level of orchestration. The NECOS approach will be manifested in a platform whose main distinguishing features are:
The NECOS platform is based on state of the art open software platform. This baseline platform is enhanced with the management and orchestration algorithms and the APIs that constitute the research activity of the project. Finally, the NECOS platform will be validated, in the context of the two proposed use cases, using a number of testing frameworks that include the SWN test-bed.
The exponential growth of Internet content, in size, quantity and network traffic demands, enabled new network architectures realizing efficient hosting, discovery and dissemination of content, such as the Content Delivery Networks (CDNs). CDNs are usually based on large data centers, proprietary software and may not be responsive enough to dynamic changes in network conditions and user requirements. Such an approach is becoming inefficient for 5G networks targeting ultra-low latency services through lightweight edge clouds that host (or cache) the content near the end-users.
Along these lines, we propose a novel CDN paradigm utilizing lightweight Unikernel-based Virtual Machines (VMs), under which limited-content web servers hosted on Unikernel VM’s boot rapidly and on-demand, serve users’ requests and then shutdown. FED4FIRE is the ideal experimentation environment to conduct such research, since it provides all the aspects we are missing (i.e., scalability, heterogeneity of physical / virtual resources and low barrier of experimentation difficulty).
A main research challenge in 5G Networks is an efficient synergy of the mobile network edge with nearby cloud deployments that achieves ultra-low latency and high bandwidth, while enabling innovative applications. However, in high-mobility environments is not easy to deploy traditional clouds nearby. Furthermore, such technologies use full-scale operating systems with unneeded most of their codebase (e.g., a web server may require 50MB but reserve a 20GB virtual machine). We suggest that Unikernel Virtual Machines (UVMs) fit this context very well, since they have a very small size and rapid boot-up times, i.e., can be responsive to dynamic changes in the network conditions.
The MONROE project offers unique experimentation capabilities utilizing both highly-mobile environments and real operational Mobile Broadband (MBB) networks. In MEC, we complement the MONROE platform with lightweight cloud capabilities residing in the mobile nodes. We plan to experiment with: (i) Intelligent orchestrated cloud resources that improve mobile communication and adapt to the conditions of the MBB networks, (ii) Multi-homing capabilities that consider resource offloading to the nearby cloud resources, and (iii) Novel forecasting mechanisms for the dynamic network conditions. The above will be demonstrated with three novel scenarios utilizing the MONROE platform and our SWN test-bed (i.e., Web Load Balancing, Ephemeral VMs Orchestration and Internet of Things).
New flexible network architectures emerged lately, such as the Software-Defined Networks (SDNs) that decouple network control from data plane and provide logically-centralized management of the network. However, SDNs were introduced for infrastructure networks and have not yet fully evolved for heterogeneous wireless networks. Furthermore, their flow control does not consider the diverse wireless channel characteristics, which is essential for improved QoS and energy-efficiency of mobile devices. We believe the radio-interface flexibility can complement such solutions, enabling cross-layer optimization of network operation.
The CORAL project focuses on the experimentation of SDN-inspired capabilities aiming at improved QoE of users and QoS of applications over resource-constrained devices. It experiments with novel network control features and protocols that: (i) realize optimized routing over mobile devices with signal issues and intermittent connectivity; and (ii) improve resource allocation and energy consumption of mobile devices. Such novel features can only be experimented in the WiSHFUL platform, since it provides the required realistic experimentation capabilities, such as the appropriate radio- and network-control abstractions over heterogeneous wireless environments.