A Novel 6G Conversational Orchestration Framework for Enhancing Performance and Resource Utilization in Autonomous Vehicle Networks

A vision of 6G aims to automate versatile services by eliminating the complexity of human effort for Industry 5.0 applications. This results in an intelligent environment with cognitive and collaborative capabilities of AI conversational orchestration that enable a variety of applications across smart Autonomous Vehicle (AV) networks. In this article, an innovative framework for AI conversational orchestration is proposed by enabling on-the-fly virtual infrastructure service orchestration for Anything-as-a-Service (XaaS) to automate a network service paradigm. The proposed framework will potentially contribute to the growth of 6G conversational orchestration by enabling on-the-fly automation of cloud and network services. The orchestration aspect of the 6G vision is not limited to cognitive collaborative communications, but also extends to context-aware personalized infrastructure for 6G automation. The experimental results of the implemented proof-of-concept framework are presented. These experiments not only affirm the technical capabilities of this framework, but also push into several Industry 5.0 applications

6G Vision: Towards Future Collaborative Cognitive Communication (3C) Systems

6G networks are expected to have a breakthrough by enabling the emergence of collaborative cognitive communication services over heterogeneous environments for industry 5.0 applications. These applications are required to adapt human-centric approach to make the most of human intuition and intelligence in Industry 4.0 automation.It calls for a transdisciplinarity research domain to investigate innovative systems with overlapping realms of Psychology, Sociology, Communication networks, Artificial Intelligence , Natural Language Processing and Collaborative Computing. The author at the Cognitive Systems Research Centre, London South Bank University has coined the expression “3C Systems" to refer to such artifacts which stands for "Collaborative Cognitive Communication Systems”. In this paper, an innovative framework for 3C Systems is proposed that is able to analyze and predict both the human as well as machine behaviors. It proactively diagnoses issues and recommends solutions without requiring any human intervention. The proposed concept of 3C Systems would potentially contribute towards 6G standardization. The automation and orchestration aspects of this research have variety of applications stretched across city infrastructures, retail, business, tourism, health, law, education and travel. A thorough insight to a broad view of 6G vision has been presented towards envisioned 3C Systems, while covering its enabling technologies. The experimental results for the proof of concept implementation has been presented. Results affirm the technical capabilities of the concept, to contribute to several industry 5.0 applications including, but not limited to holographic communication, self-driving vehicles, context-aware infrastructure and personalized interfaces

A Novel Energy-Efficient Reservation System for Edge Computing in 6G Vehicular Ad Hoc Network

The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%

Edu-Cloud: On-the-fly Employability Skills as a Service

21st Century global job market competition requires Science, Technology, Engineering and Mathematics (STEM) university curricula to support both state-of-the-art technical and soft skills learning to improve graduate employment. This necessitates the transformation of the current teaching and learning methodology powered by a social and col- laborative platform to provide a social co-learning environment. This social co-learning will provide students with opportunities for self-enrichment while supporting their technical skills and hands-on needs. The platform must also provide the required lab infrastructure for hands-on experimentation. This paper proposes the design and implementation of a cloud based platform called Edu-Cloud. The Edu-Cloud has been designed to provide automated resource provisioning and perform on-the-fly deployment of scalable virtual network functions to stream multimedia content closer to the global learners. This would help to meet the specific learning needs of a group of global interconnected students with similar learning skills and abilities. The benchmarking performance results show that the proposed framework works efficiently while reducing primary network traffic by deploying resources closer to the users and support scalability for a global deployment scenario

Area under ROC curve of energy detection over generalized fading channels

A fast and reliable detection scheme is essential in several wireless applications such as radar and cognitive radio systems. Energy detection is such a method as it does not require a priori information of the received signal while it exhibits low implementation complexity and costs. Since the detection capability of ED is largely affected by the effects of multipath fading, this paper is devoted to a thorough analysis of energy detection based spectrum sensing over generalized fading conditions. To this end, analytical expressions are firstly derived using the area under the receiver operating characteristic curve (AUC) under additive white Gaussian noise. This analysis is subsequently extended to the case of generalized fading conditions characterized by k - μ and η - μ fading distributions. The offered results are novel and are employed in analyzing the corresponding performance. It is shown that fading phenomena result to detrimental effects on the performance of spectrum sensing since the deviation between severe and non-severe conditions is rather substantial

A Comprehensive Framework for Spectrum Sensing in Non-Linear and Generalized Fading Conditions

We derive a comprehensive analytical framework for the ED over generalized, extreme, and non-linear fading conditions which addresses the topic completely. This is carried out for both conventional and diversity receptions and it is based on the area under the ROC curve (AUC), which is an efficient performance measure that is widely used in physical sciences and engineering. This differentiates the considered methodology from the aforementioned routine approaches and additionally provides generic results on the arbitrary derivatives of the MGF of useful generalized processes. The asymptotic behavior of the derived expressions is also analyzed providing direct and concrete insights on the role and effect of the involved parameters on the ED performance. The offered analytic results are subsequently employed in quantifying the performance of ED over various types of fading conditions, which exhibits that ED performance is significantly degraded by even slight variations of the severity of fading. To this end, it is shown that the detrimental effects of fading can be effectively mitigated with the aid of square-law combining and switch-and-stay combining methods, as a low number of diversity branches can ensure sufficient and holistic performance improvement even in severe fading conditions

A New Global Ocean Climatology

A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology

Autonomous, Seamless and Resilience Carrier Cloud Brokerage Solution for Business Contingencies during Disaster Recovery

The challenge of disaster recovery management for cloud based services is constantly evolving. The costs of cloud service downtime in the event of disaster striking is the subject of much international research. The key issue to resolve is developing suitably resilient and seamless live/realtime mechanisms for disaster recovery. In this paper, we have implemented a proof of concept for an autonomous and fault tolerant carrier cloud brokerage solution with resilient provisioning of on-the-fly cloud resources. When a disaster strikes, the proposed solution will trigger the migration of an entire IaaS from one cloud to another without causing any disruption to the business. In the event of non-availability of hosts for the deployment of virtual network functions for different business processes, an on-the-fly host selection mechanism is proposed and implemented to locate other active compute hosts without any disruptions. In order to evaluate the performance of the proposed solution, we defined several usecase scenarios for each cloud service. This proposed solution will not only reduce the capital expenditure but also provides a reliable and efficient way to access the data during disaste

Triethyl orthoformate covalently cross-linked chitosan-(poly vinyl) alcohol based biodegradable scaffolds with heparin-binding ability for promoting neovascularisation

There is a need to develop pro-angiogenic biomaterials to promote wound healing and to assist in regenerative medicine. To this end, various growth factors have been exploited which have the potential to promote angiogenesis. However, these are generally expensive and labile which limits their effectiveness. An alternative approach is to immobilize heparin onto biocompatible degradable hydrogels. The heparin in turn will then bind endogenous proangiogenic growth factors to induce formation of new blood vessels.In this study, we continue our development of hydrogels for wound healing purposes by exploring covalently cross-linking chitosan and polyvinyl alcohol hydrogels using triethyl orthoformate. Two concentrations of triethyl orthoformate (4 and 16%) were compared for their effects on the structure of hydrogels - their swelling, pore size, and rate of degradation and for their ability to support the growth of cells and for their heparin-binding capacity and their effects on angiogenesis in a chick chorioallantoic membrane assay.Hydrogels formed with 4 or 16% both triethyl orthoformate cross-linker were equally cyto-compatible. Hydrogels formed with 4% triethyl orthoformate absorbed slightly more water than those made with 16% triethyl orthoformate and broke down slightly faster than non-cross-linked hydrogels. When soaked in heparin the hydrogel formed with 16% triethyl orthoformate showed more blood vessel formation in the CAM assay than that formed with 4% triethyl orthoformate

Multi-Access Edge Computing: Open issues, Challenges and Future Perspective

Latency minimization is a pivotal aspect in provision of real time services while adhering to Quality of Experience (QoE) parameters for assuring spectral efficiency. Edge Cloud Computing, being a potential research dimension in the realm of 5G networks, targets to enhance the network efficiency by harnessing activeness of both cloud computing and mobile devices in user's proximity. Keeping in view the far ranging impact of Edge Cloud Computing in future mobile generations, a comprehensive review of the prevalent Edge Cloud Computing frameworks and approaches is presented with a detailed comparison of its classifications through various QoS metrics (pertinent to network performance and overheads associated with deployment/migration). Considering the knowledge accumulated, procedures analysed and theories discussed, the paper provides a comprehensive overview on sate-of-the-art and future research directions for multi-access mobile edge computing