Open Radio Access Networks (O-RAN) aims to transition telecommunication networks from vendor-specific hardware to open, virtualised control architectures. As interest grows in deploying O-RAN in non-terrestrial networks (NTNs), understanding the robustness of its protocol specifications becomes critical. This paper reports on the formal modelling of the stable O2 O-RAN interface specification using the Alloy modelling language. We encode ten representative operational scenarios from the O2 specification and formalise safety and feasibility properties relevant to deployment constraints. Bounded model checking reveals several classes of specification weaknesses, including underconstrained pre/post conditions, ambiguous sequencing of protocol steps, and conflicting simultaneous triggers that permit inconsistent system states or violate intended progress conditions.

Federated learning (FL) has been increasingly applied to smart city applications to enable distributed model training while preserving data privacy. However, conventional weight-sharing FL still incurs high communication costs in bandwidth-constrained edge environments. Recently introduced Federated Prompt Learning (FPL) significantly reduces communication bandwidth usage to alleviate this issue. Nevertheless, performance degradation persists due to the coexistence of inference and training tasks and communication overhead, defined as delays arising from the transfer of tasks and associated data. Managing priorities between latency-sensitive inference and delay-tolerant training tasks is a critical challenge.This paper models the offloading of inference and training tasks in FPL environments using queuing theory. Compared to the Task-Type Separation (TTS) method, we expand the control model and propose an improved offloading scheme that minimizes the mean sojourn time of training tasks while meeting delay requirements for inference tasks. This scheme allows for bidirectional offloading among multiple edge servers, reducing inference latency while maintaining training continuity. Analytical evaluations show that the proposed method satisfies inference delay requirements while maintaining acceptable training delays. This provides an automatic, scalable task control mechanism for FPL-based edge systems.

With the exponential growth of data traffic, ensuring reliable and efficient network testing has become critical throughout design, implementation, and management operations. As testing is essential to ensure that changes in configuration or traffic conditions do not degrade user experience, current testing practices rely heavily on manual configuration and simulators. This reliance leads to time-consuming, difficult-to-scale, and expert-dependent processes. To address these limitations, our work explores the role of Automated Machine Learning (AutoML)–based automatically generated Digital Twin (DT) in network testing to enable rapid and scalable testing across diverse network conditions. By integrating this approach with a network service controller for configuration optimization, our results evidence an improvement that DT-enabled testing achieves high accuracy while being approximately 25,000 times faster than simulator-based testing. The implications of these findings, suggest that automated DT generation through AutoML can reduce dependence on manual modeling, allow DTs to adapt to diverse test scenarios, and enhance scalability for complex network.

Open Radio Access Networks (O-RAN) aims to transition telecommunication networks from vendor-specific hardware to open, virtualised control architectures. As interest grows in deploying O-RAN in non-terrestrial networks (NTNs), understanding the robustness of its protocol specifications becomes critical. This paper reports on the formal modelling of the stable O2 O-RAN interface specification using the Alloy modelling language. We encode ten representative operational scenarios from the O2 specification and formalise safety and feasibility properties relevant to deployment constraints. Bounded model checking reveals several classes of specification weaknesses, including underconstrained pre/post conditions, ambiguous sequencing of protocol steps, and conflicting simultaneous triggers that permit inconsistent system states or violate intended progress conditions.

Transportation accounts for around 27% of green house gas emissions in the UK. While an obvious priority area for decarbonisation, and aligned to the UK government goal of reducing emissions by 68% for 2030, the free-market nature of the transportation sector combined with its fundamentally implicit and pervasive connections to all aspects of society and national infrastructure mean that all decarbonisation efforts to date have been siloed within a single transport sector, e.g. only considering greener aviation fuels. Truly decarbonising transport requires radical changes to the entire transport infrastructure, and since that transport does not happen in isolation, a single user often using multiple modes, we need a view over the whole transport system. The first step to solving a problem is to understand it. As a result of the fragmented nature of the transportation sector, there is currently no system level view. Without the ability to monitor even adjacent transport domains, the ability for people or organisations to (dynamically) adapt their operations for decarbonisation outcomes is unrealistic. As transportation is a complex social-techno-economic system, information and knowledge sharing is a must to be able to understand and explore potential solutions to the decarbonisation challenge. We believe a Federated Digital Twinning Approach has the potential to tackle transport decarbonisation problems, and, in this extended abstract, we give an overview of the research required to tackle the fundamental challenges around digital twin design, generation, validation and verification.

Scientific research in many fields routinely requires the analysis of large datasets, and scientists often employ workflow systems to leverage clusters of computers for their data analysis. However, due to their size and scale, these workflow applications can have a considerable environmental footprint in terms of compute resource use, energy consumption, and carbon emissions. Mitigating this is critical in light of climate change and the urgent need to reduce carbon emissions. In this chapter, we exemplify the problem by estimating the carbon footprint of three real-world scientific workflows from different scientific domains. We then describe techniques for reducing the energy consumption and, thereby, carbon footprint of individual workflow tasks and entire workflow applications, such as using energy-efficient heterogeneous architectures, generating optimised code, scaling processor voltages and frequencies, consolidating workloads on shared cluster nodes, and scheduling workloads for optimised energy efficiency.

5G and beyond mobile telecommunication networks are increasingly embracing software technologies in their operation and control, similar to what has powered the growth of the cloud. This is most recently seen in the radio access network (RAN). In this new approach, the RAN is increasingly controlled by software applications known as xApps, and opens the door to third party development of xApps bringing diversity to the ecosystem, similar to mobile phone apps. This model aligns closely with the controllers in the ITU-T architecture for autonomous networks, and provides a pathway towards autonomous operation in the RAN. Unfortunately, no marketplace to host or supply xApps currently exists.

Name-based protocols give an opportunity to revisit aspects of content delivery including Quality of Service (QoS). Prior named-based approaches require additional signalling, distinct from forwarding, adding complexity. We propose a new name-based QoS mechanism, leveraging the simplicity of the name-prefix forwarding model. We demonstrate: (i) the effectiveness of our QoS prioritisation via a proof-of-concept implementation, (ii) scalability through analytical evaluation, and (iii) simplicity and clarity of the trust model through an analytical model.

Federated Learning (FL) is a popular approach for distributed machine learning while protecting data privacy, especially in smart city applications. However, FL at the edge faces challenges due to high communication overhead and limited computational resources. Recently, Federated Prompt Learning (FPL) has been developed to reduce data transfer costs by sharing sophisticated prompts instead of model weights, shifting the bottleneck from communication to computation scheduling. In this paper, we use queueing theory as a lightweight evaluation mechanism to investigate the effectiveness of task offloading in an edge-based FPL environment. We analyze the impact of scheduling (both preemptive and non-preemptive) based on the priority of inference and training tasks on task execution latency. To address the limitations of these conventional methods, we propose a novel offloading strategy that distributes inference and training tasks across multiple edge servers. Experimental results demonstrate that the proposed method significantly reduces inference latency while maintaining efficient training and outperforms the baseline scheduling method. The paper provides insights into load balancing optimizations in edge-based federated learning environments, contributing to more responsive, scalable, and autonomous systems.

Much contemporary usage of the Internet is content-driven. The traffic originates from highly distributed services where users exclusively care about the data they are receiving, not where it comes from. However the longstanding architecture of the Internet and its management are largely host-oriented. Namebased networks address this dichotomy by proposing a content- and data-centric approach. In name-based networks, every interaction is driven by the name of the data that is being requested. Although this aligns with the large proportion of the way data is retrieved over the Internet, it remains an open question as to how this mechanism could be used to manage the forwarders in name-based networks and support autonomous operation. Specifically, in the context of a name-prefix based QoS mechanism, policies need to be present on every forwarder on the network, requiring policy distribution and continuous updates. Currently there is no standard solution to distribute and manage QoS policies on name-based networks. This paper explores how name-based networks could be managed autonomously, identifying mechanisms to control QoS policies across a network by examining an example scenario. We present a novel design for a QoS distribution mechanism that is conceptually coherent with existing name-based protocols; we subsequently illustrate this proposal by sketching out a concrete use case scenario.

The increased use of software in the operation and management of telecommunication networks has moved the industry one step closer to realizing autonomous network operation. One consequence of this shift is the significantly increased need for testing and validation before such software can be deployed. Complementing existing simulation or hardware-based approaches, digital twins present an environment to achieve this testing; however, they require significant time and human effort to configure and execute. This paper explores the automatic generation of digital twins to provide efficient and accurate validation tools, aligned to the ITU-T autonomous network architecture's experimentation subsystem. We present experimental results for an initial use case, demonstrating that the approach is feasible in automatically creating efficient digital twins with sufficient accuracy to be included as part of existing validation pipelines.

Transportation accounts for around 27

Social assistance in Somalia has become deeply embedded in the country’s political economy and struggles with systemic diversion and corruption, which negatively affects how programmes on accountability of aid function in practice (Majid et al. 2021; Ground Truth Solutions 2023; Africa’s Voices Foundation 2022b; Loop Somalia 2023). This paper examines systems for accountability of social assistance in Somalia. It explores how and why accountability outcomes and pathways are not working for people, particularly for marginalised groups. It is based on consultations with people receiving social assistance, community representatives and leaders, community-based organisations, local authorities, local and international non-governmental organisations, United Nations agencies, international donors, and the Ministry of Labour and Social Affairs. The report examines opportunities for strengthening accountability capacities and pathways based on community-generated suggestions and feedback from social assistance decision makers.

This paper explores the accountability of social assistance in the Kurdistan Region of Iraq (KRI), focusing on the roles of frontline staff of local and international organisations since government-led programmes became inactive in 2015. It highlights how local organisations can bridge gaps in social assistance by informing communities, supporting referrals, and contributing to social protection reform. The research also highlights cultural challenges faced by social assistance workers in Iraq. Participants recommend integrating local networks into social assistance design, enhancing coordination between organisations, and involving frontline staff in decision-making. They also encourage proactive community engagement, making social protection policies more accessible, and using storytelling for accountability.

Yemen has sometimes been held up as an impressive example of how existing social protection systems and capacities can be maintained and supported even during a prolonged war. While providing support to meet immediate life-saving needs is the humanitarian priority in Yemen, aid organisations also want to ensure that recurrent emergency operations are delivered in a way that will support, and not undermine, national reconstruction and rehabilitation for a post-conflict Yemen. Through a literature review and interviews with Yemeni and international stakeholders conducted in 2022 and 2023, this study has interrogated that narrative, examining the evidence on what capacities are being supported, and what that means for the effective provision of assistance through a protracted crisis. It is important to acknowledge the enormous challenges all actors in Yemen must confront in trying to find ways to help people survive in the face of conflict and other shocks. Widespread conflict, insecurity, and contested governance have made providing assistance extremely hard. The huge scale of need has also necessitated one of the biggest aid operations in the world, creating incentives for control and diversion. In the face of these challenges, focusing on the two main social assistance operations in Yemen – the World Food Programme’s General Food Assistance Programme and the World Bank’s Unconditional Cash Transfer Programme (implemented by the United Nations Children’s Fund and the Social Fund for Development, with the Social Welfare Fund) – this study has found impressive achievements in getting assistance to people, and in maintaining and strengthening Yemeni organisational and individual capacities. However, while some capacities have been maintained and built, others have been relatively neglected (in particular, valuable capacities for community engagement and accountability, which are vital for achieving more inclusive and conflict-sensitive approaches), whereas others (around the highly politicised issues of targeting and transfer value) have been difficult to tackle. The study found that partnerships with Yemeni non-governmental organisations are narrowly subcontractual and limited to managing distribution, with only a small proportion of funding directly reaching national organisations. Overall, the process of providing external support for ‘capacity strengthening’ of national actors is somewhat opaque. More coordinated strategic efforts to support local capacities, informed by shared analysis and learning from past endeavours, could help improve future social assistance interventions.

ُعتبر اليمن أحياناً مثالاً يُحتذى به على كيفية الحفاظ على نُظُم وقدرات الحماية الاجتماعية القائمة ودعمها حتى خلال حربٍ طال أمدها. في حين يُعدّ تقديم الدعم لتلبية الاحتياجات الفورية المنقذة للحياة الأولوية الإنسانية في اليمن، إلا أن المنظمات الفاعلة في مجال تقديم المعونة حريصة أيضاً على ضمان تنفيذ عمليات الطوارئ المتكررة بطريقة تساند عملية إعادة الإعمار وإعادة التأهيل الوطني لليمن بعد انتهاء الصراع في البلاد، لا أن تقوضها. من خلال مراجعة للوثائق ومقابلات مع أصحاب مصلحة يمنيين ودوليين أجريت في عامي 2022 و2023، ناقشت هذه الدراسة تلك السرديّة فبحثت في البراهين التي تشير إلى القدرات المدعومة وما يعنيه ذلك بالنسبة لتقديم المساعدات بطريقة فعّالة خلال أزمةٍ طال أمدها. من المهم التسليم بالتحديات الهائلة الملقاة على عاتق جميع الجهات الفاعلة في اليمن في مساعيها لإيجاد طرق تساعد الناس على البقاء على قيد الحياة وسط الصراع والصدمات الأخرى؛ فقد صعّب انتشار النزاع وانعدام الأمن والحكم المتنازع عليه بصورة كبيرة من عملية تقديم المساعدة، كما استلزم الحجم الهائل للاحتياجات القيام بواحدة من أكبر عمليات تقديم المعونة في العالم، مما خلق دوافع للسيطرة على المعونات وتحويل مسارها. في مواجهة هذه التحديات، ومع التركيز على العمليتين الرئيسيتين لتقديم المساعدات الاجتماعية في اليمن––برنامج المساعدات الغذائية العامة التابع لبرنامج الأغذية العالمي وبرنامج الحوالات النقدية غير المشروطة التابع للبنك الدولي (ينفذهما اليونيسف والصندوق الاجتماعي للتنمية بالتعاون مع صندوق الرعاية الاجتماعية)––وجدت هذه الدراسة أن هناك إنجازات رائعة تتمثل في تقديم المساعدات للناس والحفاظ على القدرات التنظيمية والفردية اليمنية وتعزيزه قد تحققت؛ إلا أنه في الوقت الذي تم فيه الحفاظ على بعض القدرات وبناؤها، ولا سيما تلك القدرات القيّمة الخاصة بالمشاركة المجتمعية والمساءلة، والتي تكتسي أهمية حيوية لتحقيق نهجاً أكثر شمولاً ومراعاةً للنزاعات هذا وقد كان من الصعب معالجة مسائل أخرى تتعلق بقضايا الاستهداف وقيمة التحويلات والتي تتسم بالتسييس الشديد. علاوةً على ما ذكر، وجدت الدراسة أيضاً أن الشراكات مع المنظمات غير الحكومية اليمنية كناية عن شراكات تعاقدية فرعية ضيقة ومحصورة في إدارة التوزيع، حيث تصل نسبة ضئيلة فقط من التمويل إلى المنظمات الوطنية مباشرةَ. يحيط الغموض إلى حدٍّ ما بعملية تقديم الدعم الخارجي الهادفة إلى تعزيز قدرات الجهات الفاعلة الوطنية. من شأن زيادة تنسيق الجهود الاستراتيجية لدعم القدرات المحلية، بالاسترشاد بالتحليلات المشتركة والتعلم من المساعي السابقة، أن يساعد مستقبلاً في التحسين من تدخلات المساعدة الاجتماعية.

Much of Yemen’s population needs basic assistance to avoid famine. As well as providing food and cash-based support during a decade of war, international aid actors have sustained and strengthened the capacities of local organisations involved. Yet these efforts have overlooked some capacities – particularly valuable skills for community engagement and accountability, seen as vital for inclusion and conflict sensitivity. As conflict in Yemen continues and aid budgets come under further pressure, this Policy Briefing offers a series of recommendations to improve the effectiveness of donor and aid agency support for local capacities for social assistance.

Operation and management of telecommunication networks are increasingly difficult with the demands and behaviors of users exceeding the capacity of network engineers to keep pace. This has led to increased automation of the network, enabled by various forms of intelligent software. One such proposal from the ITU-T Focus Group on Autonomous Networks (standardization group) is an architecture to achieve self-driven automation (i.e. autonomy) of network operation, whereby technology from different operators and third parties is self-assembled and deployed in production networks. This raises questions and challenges regarding transparency, auditability, and trust while maintaining interoperability.This work presents an initial study of a distributed and decentralized marketplace to bring transparent and auditable trust to the proposed architecture without sacrificing interoperable functionality. We demonstrated this by our proof of concept implementation of both the proposed architecture and marketplace based on the combination of Ethereum and IPFS.

In this paper we give an overview of an open disaggregated network architecture based on an Open Radio Access Network (O-RAN), including the current work from standards bodies and industry bodies in this area. Based on this architecture, a framework for the automation of xApp development and deployment is proposed. This is then aligned with the key concepts described in ITU-T in terms of the evolution, experimentation, and adaptation of controllers. The various steps in such an aligned workflow, including design, validation, and deployment of xApps, are discussed, and use case examples are provided to illustrate further our position regarding the mechanisms needed to achieve automation.

Next Generation Networks (NGNs) are expected to handle heterogeneous technologies, services, verticals and devices of increasing complexity. It is essential to fathom an innovative approach to automatically and efficiently manage NGNs to deliver an adequate end-to-end Quality of Experience (QoE) while reducing operational expenses. An Autonomous Network (AN) using a closed loop can self-monitor, self-evaluate and self-heal, making it a potential solution for managing the NGN dynamically. This study describes the major results of building a closed-loop Proof of Concept (PoC) for various AN use cases organized by the International Telecommunication Union Focus Group on Autonomous Networks (ITU FG-AN). The scope of this PoC includes the representation of closed-loop use cases in a graph format, the development of evolution/exploration mechanisms to create new closed loops based on the graph representations, and the implementation of a reference orchestrator to demonstrate the parsing and validation of the closed loops. The main conclusions and future directions are summarized here, including observations and limitations of the PoC.