Trust-aware caching-constrained tasks offloading in multi-access edge computing

Multi-access edge computing (MEC) networks face significant challenges in managing congestion and safeguarding personal privacy data on a massive scale. Integrating trust awareness into MEC networks presents an opportunity to enhance security and privacy by correlating human relationships with connected devices. Moreover, leveraging trust-aware task caching and offloading holds promise in mitigating latency and reducing energy consumption. Despite existing research efforts to address these challenges, they often overlook either trust awareness or caching optimization in task offloading, potentially compromising security or leading to task failures. To address this gap, this paper proposes a novel approach: a trust-aware task offloading strategy with cache constraints (TCTO) in MEC networks, which considers social relationships, task offloading, and caching. Drawing on the characteristics of bipartite graphs and bipartite perfect matching, we develop a trust-aware caching-constrained task offloading algorithm based on bipartite graphs. This algorithm aims to select task offloading strategies that minimize delay, energy consumption in task transmission and execution, while maximizing security among devices in MEC networks. Extensive simulations demonstrate that our proposed method has a better performance than other task offloading strategies for reducing delay and energy consumption in the process of task transmission and execution. Compared with the other baselines, the overhead of our proposed method is reduced 55 . 65 % ∼ 96 . 20 % compared with other baselines

The British migration-citizenship regime : from decolonisation to Brexit

Objectives • This chapter asks how recognising connected sociologies and histories transforms how we understand who can move, where, and on what terms, today • It sets out the connections between the formation of national citizenships and the colonial governance of populations, including their access to mobility. This is illustrated through a retelling of the development of the British immigration and citizenship regime over the course of the twentieth century • It examines, in detail, the shifting status of the people of Hong Kong to demonstrate the significance of the coloniality of British citizenship for making sense of the post-Brexit migration regime • It reveals that the provisionality and contingency of the legal statuses are an integral mechanism of migration governanc

A unified threshold-constrained optimization framework for consistent and interpretable cross-machine condition monitoring

Accurate detection of incipient faults during lifecycle degradation is crucial for continuous condition monitoring of industrial equipment. Condition indices (CIs) with pre-set thresholds are widely used in engineering practice due to their intuitiveness, simplicity, and convenience. However, uncertainties and variations in degradation patterns and fault initiation times across different industrial systems or even within the same system lead to inconsistent CI scales and thresholds, creating challenges for reliable and practical monitoring. To address this challenge, we propose a unified threshold-constrained optimization framework for consistent and interpretable cross-machine condition monitoring based on frequency-domain data fusion. Rather than directly using CIs, we introduce degradation rates of CIs, computed via first-order differences, which enable a consistent definition of normal operating levels across heterogeneous degradation patterns and multiple machines. Afterwards, a degradation rate and threshold constrained convex optimization model is formulated to automatically optimize weights in the frequency domain, ensuring sensitivity to incipient faults while preserving consistent thresholds across machines. Extensive experiments on multiple endurance datasets of rotating equipment demonstrate the consistency and superiority of the proposed approach over some famous and advanced CIs. Results show that a unified threshold can be established for the proposed CIs across diverse degradation patterns and multiple machines. Furthermore, the optimized frequency-domain weights highlight diagnostic frequency bands closely associated with system faults, thereby enhancing incipient fault sensitivity and offering interpretability compared with existing data-driven approaches

Sub-THz Traveling Wave Tubes: A Route Towards Ultra Capacity 6G Wireless Networks

When we imagine wireless communications in the next ten or twenty years, we picture a ubiquitous stream of data moving at unlimited speed, to enabling a new ecosystem where real and virtual merge. Vastly and endlessly increase of data volume in the sixth generation of wireless networks 6G (G stands for generation of mobile networks) will fuel disruptive applications, immersive user experience, creativity and societal enhancements. Terrestrial and satellite networks, already cooperating, will be intimately integrated in a multidimensional datasphere. While computational power has grown enormously, enabling the processing of huge amounts of data, data wireless transmission is presently a bottleneck of communication infrastructures confined to the microwave spectrum. Wireless links with tens or hundreds gigabits per second (Gb/s) will be possible only by the widespread adoption of the sub-THz spectrum (0.1 – 0.4 THz) for paving the way to a new era of wireless communications

Tools for Implementing Multi-Agent Systems Based on Protocols

Interaction-Oriented Programming (IOP) is an approach to building a multi-agent system by modeling the interactions between its roles via a flexible interaction protocol and implementing agents to realize the interactions of the roles they play in the protocol. In recent years, we have developed an extensive suite of software that enables multi-agent system developers to apply IOP. These include tools for efficiently verifying protocols for properties such as liveness and safety and middleware that simplifies the implementation of agents. This chapter presents some of that software suite

Metaphors and identities on an online forum dedicated to pain

Becoming seriously and/or chronically ill can challenge and disrupt our sense of who we are, in terms of our bodies, minds, and social roles. While a substantial literature exists on metaphor and illness, the use of metaphor to represent identities has received little attention. This paper focuses on similes as a particularly relevant manifestation of metaphoricity in language. An 8-million word corpus of contributions to the online forum Pain Concern is investigated via a combination of corpus linguistic methods and in-depth qualitative analysis. We explore how contributors to the forum use similes to describe their own (changing) self-perceptions due to living with pain and its consequences. To this end, we introduce and demonstrate a multi-component analytical framework, which, as we show, is equally applicable to the analysis of metaphorical expressions. The framework includes a consideration of: source concept; type of identity; and viewpoint. With regard to our data, we show how similes are used to convey mostly unwelcome changes in the persons’ perception of themselves in physical, psychological and/or social terms, potentially resulting in estrangement, low self-esteem, isolation and disempowerment. More broadly, we suggest that our framework is applicable to the study of metaphorical representations of identities in the context of illness generally

Non-Invasive Detection of Internal Potato Defects for Reduction of Food Loss in The Fresh Produce Supply Chain

The potato (Solanum tuberosum) is the most important non-grain vegetable in the world, playing a major role in human nutrition worldwide. Half of all potato grown, however, does not reach the fork of the consumer. Food waste and losses represent a substantial challenge to potato supply chains, as well as to global food systems in general. Food waste and losses negatively impact the world in a variety of ways, contributing to food insecurity, environmental degradation and economic losses. A leading cause of potato waste and losses is tuber defects, which result in produce failing to meet safety, storage or consumer standards. While defects with external symptoms are effectively screened for via optical grading lines, many defects exhibit only internal defects, which is a barrier to their detection. Internal defects are widely screened for by solely destructive means; novel non-destructive approaches are needed to improve the detection and screening of internal potato defects. Work carried out in this thesis investigates the potential for non-invasive non-destructive approaches to detect internal potato defects to address the challenges they pose to the fresh potato supply chain. This research uncovers promising avenues of non-invasive non-destructive detection of internal potato defects, applying optical and electrical spectroscopy. NIR reflectance spectroscopy successfully provided a means of detecting blackheart and spraing in intact potatoes. Blackheart was also successfully detected with a novel approach to impedance spectroscopy. In addition to these findings this work develops an exciting novel method for extending the shelf-life of fresh produce such as tomatoes to reduce losses in homes, retail and transit

Is the apparent global stilling effect on wind power generation an artefact of sampling rate? Evidence from high-frequency observations in the UK

High-resolution wind data is critical when assessing the phenomenon known as global stilling. Global stilling is the observed reduction in wind speeds due to climate change. Understanding the phenomenon is crucial due to the potential impact on wind power. Using the wind speed and wind power generation data from the Lancaster University Meteorological Station and wind turbine, analysis of the trends and the rate of change for wind speed under different sampling regimes provided an insight into the change in wind speed patterns. More importantly, daily estimated wind power generation was compared to 10-min turbine power generation data to assess the importance of high-resolution data in wind power analysis. The opposing patterns of the 10-min and daily data highlight the importance of high-resolution wind speed data for global stilling research and policymaking. The large spatiotemporal variability of wind speeds combined with the non-linearity of wind power generation necessitates high-resolution data