Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

On Content-centric Wireless Delivery Networks

The flux of social media and the convenience of mobile connectivity has created a mobile data phenomenon that is expected to overwhelm the mobile cellular networks in the foreseeable future. Despite the advent of 4G/LTE, the growth rate of wireless data has far exceeded the capacity increase of the mobile networks. A fundamentally new design paradigm is required to tackle the ever-growing wireless data challenge. In this article, we investigate the problem of massive content delivery over wireless networks and present a systematic view on content-centric network design and its underlying challenges. Towards this end, we first review some of the recent advancements in Information Centric Networking (ICN) which provides the basis on how media contents can be labeled, distributed, and placed across the networks. We then formulate the content delivery task into a content rate maximization problem over a share wireless channel, which, contrasting the conventional wisdom that attempts to increase the bit-rate of a unicast system, maximizes the content delivery capability with a fixed amount of wireless resources. This conceptually simple change enables us to exploit the "content diversity" and the "network diversity" by leveraging the abundant computation sources (through application-layer encoding, pushing and caching, etc.) within the existing wireless networks. A network architecture that enables wireless network crowdsourcing for content delivery is then described, followed by an exemplary campus wireless network that encompasses the above concepts.Comment: 20 pages, 7 figures,accepted by IEEE Wireless Communications,Sept.201

Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme

This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation provides promising results

St Helens College: report from the Inspectorate (FEFC inspection report; 53/94 and 73/98)

The Further Education Funding Council has a legal duty to make sure further education in England is properly assessed. The FEFC’s inspectorate inspects and reports on each college of further education according to a four-year cycle. This record comprises the reports for periods 1993-94 and 1997-98

PoliSave: Efficient Power Management of Campus PCs

In this paper we study the power consumption of networked devices in a large Campus network, focusing mainly on PC usage. We first define a methodology to monitor host power state, which we then apply to our Campus network. Results show that typically people refrain from turning off their PC during non-working hours so that more than 1500 PCs are always powered on, causing a large energy waste. We then design PoliSave, a simple web-based architecture which allows users to schedule power state of their PCs, avoiding the frustration of wasting long power-down and bootstrap times of today PCs. By exploiting already available technologies like Wake-On-Lan, Hibernation and Web services, PoliSave reduces the average PC uptime from 15.9h to 9.7h during working days, generating an energy saving of 0.6kW/h per PC per day, or a saving of more than 250,000 Euros per year considering our Campus Universit

Taking our learning and teaching strategy to the next level through technology enhanced campus development

Over the last three years Abertay University has radically evolved its strategy for teaching and supporting learning. This paper outlines Abertay’s journey over the last few years, including the key features of our new pedagogic approach and its impact so far. For example, in 2016 Abertay was the highest ranked modern Scottish University in the National Student Survey (NSS) and shortlisted for the prestigious Times Higher Education “University of the Year” award.In order to further enhance our students’ progression, attainment and employability we have recognized the need to invest further in two key (and related) areas: technology enhanced learning and estate development in order to create a so-called “sticky campus” i.e. somewhere our students will want to come and stay. This has included full implementation of electronic management of assessment (EMA); blended learning; new technology-rich collaborative learning environments and science laboratories which promote richer student-staff interactions and new ways of learning; and a planned complete refurbishment of the University library which will provide a variety of learning environments (formal and informal) from summer 2017.The paper will detail the drivers for these changes; the change management processes involving a staff-student partnership involving management, academic and professional services; successes;challenges; lessons learned and future plans