Kiran Voderhobli

The subscription based model of cloud computing has allowed for users to migrate their processes to off-site network facilities. One of the motivations for deployment of cloud based services is to promote sustainability by reducing green-house emissions at a local level. Although some might argue that this model saves a lot of power at local network facilities, the problem of energy crisis caused by ICT is never-ending. Today, data-centres are bee-hives of exascale computing and high network dependant processing. Work-load on the cloud directly contributes to energy consumption to an extent that currently IT clouds are some of the worst contributors to CO2 emissions. This paper discusses why traffic-management on the cloud is vital to make it more power efficient and how it can be achieved by gathering live network statistics. The discussion fits with the context of “emerging clouds” as thought needs to be given on how to apply energy efficient schemes at various points including at the communication level.

Virtualisation is one of the key concepts that allows for abstraction of hardware and software resources on the cloud. Virtualisation has been employed for all aspects of cloud computing including big data processing. There have been arguments based on recent research that indicate that computational efficiency could be more efficient via virtualisation compared to their physical counterparts. A data centre not only represents physical resources but also the collection of virtualised entities that in essence, form virtual networks. Methods to monitor these virtual entities for attributes such as network traffic, performance, sustainability, etc., usually tend to be deployed on ad hoc basis. Understanding the network related attributes of virtualised entities on the cloud will help take critical decisions on management activities such as timing, selection and migration of virtual machines (VMs). In corporate physical data networks, it could have been achieved using four of the network management functional areas, i.e., performance management, configuration management, accounting management and fault management. This chapter discusses, with examples, at how network management principles could be contextualised with virtualisation on the cloud. In particular, the discussion will be centred on the application of Simple Network Management Protocol (SNMP) for gathering behavioural statistics from each virtualised entity.

The phrase "sustainable computing" covers multiple areas of Green ICT, including architectures, infrastructure, software, hardware and computing processes. Creating a sustainable computing environment requires optimizing the above areas to adopt the "green" theme. Today's network infrastructures give sustainability a serious consideration and reducing energy consumption is usually one of the deployment policies. Bringing down the carbon foot-print of computing, needs changes to the way IT is deployed, and this is not just in terms of design decisions. There is more to sustainability than just adding energy reduction remedies on an ad-hoc basis. Modern networks deal with high volumes of network data due to wide spread deployment of corporate networks and cloud based services. Computing architectures and software are evolving to accommodate resource sharing, light-weight processes, efficient task scheduling etc. to embrace the green theme. But often, the seemingly smaller background network processes are side-stepped when it comes to optimising for sustainability. This chapter explains the importance of studying network traffic patterns to look for any scope for energy saving in a virtualized environment. This is a "position chapter" that explains the need to gather network statistics from virtual entities to save energy. It takes a network management view towards achieving green cloud data centres.

This chapter describes a novel approach to study network patterns in a data centre with the aim of reducing power consumed. Cloud infrastructures rely on numerous networked devices in data-centers to provide virtualization and sharing of resources. Network traffic is one of the key contributors to power consumption. Numerous techniques to develop power-aware data-centers have been proposed in the recent years. Virtualization management is based on many critical decisions including work-load, utilization, location of physical resources etc. This chapter takes a unique network management angle to greening a data center. It describes how Simple Network Management Protocol (SNMP) has a great potential to characterize traffic which can then feed into decisions for management of virtualized entities.

With the applicability of corporate networks on the rise, the demand for effective network managers with appropriate skills is a serious requirement. Organisations must leave all options open, including the one of having to train their own computer systems personnel on network management skills. With the possibility of the above, serious thought needs to be focused on the training scenario to be adopted. Providing trainees with hands on experience is a basic solution for acquiring skilled network managers. However, such a training scenario must ensure that there is no interference to live networks of an organisation at any level. In the forefront exists the possibility of using virtual network management tools, aimed at trainee network managers and researchers. The content presented in this paper is in direct relevance to the research work currently being conducted by researchers at the Leeds Metropolitan University (Leeds Met), and adds to the list of previous publications associated with this research. This paper explains set of processes and design paradigms, which lead to a newly developed simulation system for trainee network managers.

Advancements in digital technologies have transformed the world by providing more opportunities and possibilities. However, elderly persons have several challenges utilizing modern technology, leading to digital exclusion, which can negatively impact sustainable development. This research attempts to address the current digital exclusion by addressing the challenges older people face considering evolving digital technologies, focusing on economic, social, and environmental sustainability. Three distinct goals are pursued in this study: to perform a detailed literature review to identify gaps in the current understanding of digital exclusion among the elderly, to identify the primary factors affecting digital exclusion in the elderly, and to analyze the patterns and trends in different countries, with a focus on differentiating between High-Income Countries (HICs) and Lower Middle-Income Countries (LMICs). The research strategies used in this study involve a combination of a literature review and a quantitative analysis of the digital exclusion data from five cohorts. This study uses statistical analysis, such as PCA, chi-square test, one-way ANOVA, and two-way ANOVA, to present a complete assessment of the digital issues that older persons experience. The expected results include the identification of factors influencing the digital divide and an enhanced awareness of how digital exclusion varies among different socio-economic and cultural settings. The data used in this study were obtained from five separate cohorts over a five-year period from 2019 to 2023. These cohorts include ELSA (UK), SHARE (Austria, Germany, France, Estonia, Bulgaria, and Romania), LASI (India), MHAS (Mexico), and ELSI (Brazil). It was discovered that the digital exclusion rate differs significantly across HICs and LMICs, with the UK having the fewest (11%) and India having the most (91%) digitally excluded people. It was discovered that three primary factors, including socio-economic status, health-related issues, and age-related limitations, are causing digital exclusion among the elderly, irrespective of the income level of the country. Further analysis showed that the country type has a significant influence on the digital exclusion rates among the elderly, and age group plays an important role in digital exclusion. Additionally, significant variations were observed in the life satisfaction of digitally excluded people within HICs and LMICs. The interaction between country type and digital exclusion also showed a major influence on the health rating. This study has a broad impact since it not only contributes to what we know academically about digital exclusion but also has practical applications for communities. By investigating the barriers that prevent older people from adopting digital technologies, this study will assist in developing better policies and community activities to help them make use of the benefits of the digital era, making societies more equitable and connected. This paper provides detailed insight into intergenerational equity, which is vital for the embedding principles of sustainable development. Furthermore, it makes a strong case for digital inclusion to be part of broader efforts (and policies) for creating sustainable societies.

This research highlights the importance of Emotion Aware Technologies (EAT) and their implementation in serious games to assist children with Autism Spectrum Disorder (ASD) in developing social-emotional skills. As AI is gaining popularity, such tools can be used in mobile applications as invaluable teaching tools. In this paper, a new AI framework application is discussed that will help children with ASD develop efficient social-emotional skills. It uses the Jetpack Compose framework and Google Cloud Vision API as emotion-aware technology. The framework is developed with two main features designed to help children reflect on their emotions, internalise them, and train them how to express these emotions. Each activity is based on similar features from literature with enhanced functionalities. A diary feature allows children to take pictures of themselves, and the application categorises their facial expressions, saving the picture in the appropriate space. The three-level minigame consists of a series of prompts depicting a specific emotion that children have to match. The results of the framework offer a good starting point for similar applications to be developed further, especially by training custom models to be used with ML Kit.

Modern networks are migrating from being just simple data networks to hybrid networks that support different types of media and applications. The term convergence refers to such networks that are integrated in terms of network types and/or the types of applications being supported. Often, building a convergence network gets complicated due to the interlinking of numerous devices and compatibility issues. Due to such complexity, it becomes difficult to implement security and guarantee reliability. The issues with security are more visible in converged networks than traditional data networks. Although, networks are converging, the standards have not yet matured to cater to the requirements of converged networks. There are no definitive standards that network engineers can use to build secure convergence networks. The idea of this paper is to pave the way for standards development for modern networks. We believe that modifications of protocols are a fundamental requirement for reliability and security in modern and future networks. Current work being carried out in our research labs is directed towards using simulation in studying protocol alterations to make them more suited to convergence. The research is a work in progress.