Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Exploring opportunities for diversification of smallholders' rice-based farming systems in the Senegal River Valley

CONTEXT: Policy-based or technological interventions are more likely to be effective if aligned with farmers' objectives, constraints, and decision-making processes. OBJECTIVE: The objective of this study was to explore trade-offs and synergies of farming systems in response to innovative rice cultivation activities by understanding current farming systems, main drivers impacting farm management and farmers' perspectives on rice intensification. Understanding these interrelations is key in rice production areas, where smallholder farmers largely depend on growing rice to subsist. METHODS: A rapid system analysis was conducted interviewing 20 farmers in 4 villages along the Senegal River Valley (SRV) to obtain a general view on farm functioning and farmers' perspectives on farming systems. A detailed system analysis with four farmers was subsequently conducted to provide an insight into the underlying processes regulating farm management. A multi-objective optimization model was used to quantitatively evaluate and explore farm performances based on four selected indicators representing: rice production, household agricultural profit, household labour and farm nutrient balance. RESULTS AND CONCLUSIONS: The results of this study showed that government programmes and farmers' Unions were strongly influencing farmers' decision-making in agricultural production. Farmers also reported that although rice was still essential for their livelihoods, there were transitions towards less rice production in the wet season with short duration rice varieties and more vegetable production. Both farmers' interviews and the modelling results suggested that farmers would be unlikely to increase or even maintain the area of rice double cropping, which has been strongly promoted by the Senegalese government. Instead, farmers would rather keep investing in vegetable production. SIGNIFICANCE: This modelling study shows the consequences of policy-based and technological interventions for farming systems and may inform both policy makers and farmers in situations where objectives are strongly divergent. Hence, modelling outcomes may be used to inspire discussion and innovation in order to align the government priority of ensuring national food security and farmers' objectives and constraints in the SRV

QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

Deep Learning for Mobile Multimedia: A Survey

Deep Learning (DL) has become a crucial technology for multimedia computing. It offers a powerful instrument to automatically produce high-level abstractions of complex multimedia data, which can be exploited in a number of applications, including object detection and recognition, speech-to- text, media retrieval, multimodal data analysis, and so on. The availability of affordable large-scale parallel processing architectures, and the sharing of effective open-source codes implementing the basic learning algorithms, caused a rapid diffusion of DL methodologies, bringing a number of new technologies and applications that outperform, in most cases, traditional machine learning technologies. In recent years, the possibility of implementing DL technologies on mobile devices has attracted significant attention. Thanks to this technology, portable devices may become smart objects capable of learning and acting. The path toward these exciting future scenarios, however, entangles a number of important research challenges. DL architectures and algorithms are hardly adapted to the storage and computation resources of a mobile device. Therefore, there is a need for new generations of mobile processors and chipsets, small footprint learning and inference algorithms, new models of collaborative and distributed processing, and a number of other fundamental building blocks. This survey reports the state of the art in this exciting research area, looking back to the evolution of neural networks, and arriving to the most recent results in terms of methodologies, technologies, and applications for mobile environments

Oceanus.

v. 36, no. 3 (1993

Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensive survey work on the use of XAI for IoT. To bridge this lacking, in this paper, we address the XAI frameworks with a focus on their characteristics and support for IoT. We illustrate the widely-used XAI services for IoT applications, such as security enhancement, Internet of Medical Things (IoMT), Industrial IoT (IIoT), and Internet of City Things (IoCT). We also suggest the implementation choice of XAI models over IoT systems in these applications with appropriate examples and summarize the key inferences for future works. Moreover, we present the cutting-edge development in edge XAI structures and the support of sixth-generation (6G) communication services for IoT applications, along with key inferences. In a nutshell, this paper constitutes the first holistic compilation on the development of XAI-based frameworks tailored for the demands of future IoT use cases.Comment: 29 pages, 7 figures, 2 tables. IEEE Open Journal of the Communications Society (2022

Land evaluation for peri-urban agriculture using analytical hierarchical process and geographic information system techniques: A case study of Hanoi

This paper presents an integrated technique of analytical hierarchical process (AHP) and geographic information system (GIS) to evaluate the land for peri-urban agriculture. Hanoi province, Vietnam was selected for the case study. Transformation of conventional agriculture to modern cash crops is the current trend in peri-urban Hanoi. A field survey with focused group discussions was conducted. Based on field survey data analysis, soil, land use, water resources, road network and market were chosen as major factors affecting the peri-urban agriculture. A map of each factor with different logical criteria was prepared. The AHP method was applied to identify the priority weight of each factor. Five spatial layers with their corresponding weights were linearly combined to prepare the suitability map. The map was further scaled as high suitable, medium suitable, low suitable and unsuitable land for the peri-urban agriculture. This empirical scenario provides a cost effective, rapid land evaluation framework which may help policy makers, urban and regional planners and researchers working in developing countries