Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment.

Inadequate Internet access is widening the digital divide between town and countryside, degrading both social communication and business advancements in rural areas. Wireless mesh networking can provide an excellent framework for delivering broadband services to such areas. With this in mind, Lancaster University deployed a WMN in the rural village of Wray over a three-year period, providing the community with Internet service that exceeds many urban offerings. The project gave researchers a real-world testbed for exploring the technical and social issues entailed in deploying WMNs in the heart of a small community.

Network slicing has become a fundamental property for next-generation networks, especially because an inherent part of 5G standardisation is the ability for service providers to migrate some or all of their network services to a virtual network infrastructure, thereby reducing both capital and operational costs. With network function virtualisation (NFV), network functions (NFs) such as firewalls, traffic load balancers, content filters, and intrusion detection systems (IDS) are either instantiated on virtual machines (VMs) or lightweight containers, often chained together to create a service function chain (SFC). In this work, we review the state-of-the-art NFV and SFC implementation frameworks and present a taxonomy of the current proposals. Our taxonomy comprises three major categories based on the primary objectives of each of the surveyed frameworks: (1) resource allocation and service orchestration, (2) performance tuning, and (3) resilience and fault recovery. We also identify some key open research challenges that require further exploration by the research community to achieve scalable, resilient, and high-performance NFV/SFC deployments in next-generation networks.

Software-defined networking (SDN) is an emerging paradigm to logically centralize the network control plane and automate the configuration of individual network elements. At the same time, in cloud data centers (DCs), although network and server resources are collocated and managed by a single administrative entity, disjoint control mechanisms are used for their respective management. In this paper, we propose a unified server-network resource management for such converged information and communication technology (ICT) environments. We present a SDN-based orchestration framework for live virtual machine (VM) management that exploits temporal network information to migrate VMs and minimize the network-wide communication cost of the resulting traffic dynamics. A prototype implementation is presented, and a cloud DC testbed is used to evaluate the impact of diverse orchestration algorithms. Our live VM management has been shown to reduce the network-wide communication cost, especially for the high-cost and congestion-prone core and aggregation layers of the DC. Our results show an increase in network-wide throughput by over six times, as well as over 70% communication cost reduction by migrating less than 50% of the VMs.

Operational Technology (OT) systems have become increasingly interconnected and automated, consequently resulting in them becoming targets of cyber attacks, with the threat towards a range of critical national infrastructure (CNI) sectors becoming heightened. This is particularly the case for Industrial Control Systems (ICS), which control and operate the physical processes in CNI sectors such as water treatment, electrical generation and manufacturing. Unlike information technology (IT) systems, ICS have unique cyber-physical characteristics and related safety requirements, making them an attractive target for attacks given the physical consequences that can occur. As a result, the requirement to respond and learn from previous and new attacks is also increasing, with digital forensics playing a significant role in this process. The aim of this paper is to discuss the main issues and existing limitations related to ICS digital forensic. The field of ICS digital forensics is relatively under-developed and does not have the same levels of maturity as IT digital forensics. Although the amount of research on cyber security for ICS is increasing, many unique challenges still exist that pose as barriers to the development and deployment of ICS forensic capabilities. We provide an extensive discussion on these challenges, categorising them into technical, socio-technical, and operational and legal themes. Furthermore, the relationship between these challenge themes as well as the inter-challenge dependencies are also examined. Furthermore, this work discusses ICS forensic advances in relation to the digital forensics life chain, specifically forensic readiness and investigations. The areas of digital forensic training and processes models for ICS are given particular focus. Moreover, we assess the technologies and tools that have been either applied to or developed for ICS components and networks, giving special attention to forensic acquisition and analysis methods. An examination into the specific ICS digital forensic data sources and artefacts is also presented, highlighting that until recently, this was limited to descriptions of generic data formats. In addition, this paper provides an overview of several key ICS attacks, summarising the specific techniques used, data artefacts of interest, and proposing lessons learnt. Finally, this paper presents open discussions on future ICS digital forensics research directions and on-going issues, covering both short and long-term areas that can be addressed to improve the ICS digital forensics capability.