4,406 research outputs found
Secure Cloud-Edge Deployments, with Trust
Assessing the security level of IoT applications to be deployed to
heterogeneous Cloud-Edge infrastructures operated by different providers is a
non-trivial task. In this article, we present a methodology that permits to
express security requirements for IoT applications, as well as infrastructure
security capabilities, in a simple and declarative manner, and to automatically
obtain an explainable assessment of the security level of the possible
application deployments. The methodology also considers the impact of trust
relations among different stakeholders using or managing Cloud-Edge
infrastructures. A lifelike example is used to showcase the prototyped
implementation of the methodology
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
Quality of service differentiation for multimedia delivery in wireless LANs
Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below:
1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss.
2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system.
3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference âOptimisation of Mobile Communication Networksâ 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
Survey of context provisioning middleware
In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles. © 2009-2012 IEEE
IoT trust and reputation: a survey and taxonomy
IoT is one of the fastest-growing technologies and it is estimated that more
than a billion devices would be utilized across the globe by the end of 2030.
To maximize the capability of these connected entities, trust and reputation
among IoT entities is essential. Several trust management models have been
proposed in the IoT environment; however, these schemes have not fully
addressed the IoT devices features, such as devices role, device type and its
dynamic behavior in a smart environment. As a result, traditional trust and
reputation models are insufficient to tackle these characteristics and
uncertainty risks while connecting nodes to the network. Whilst continuous
study has been carried out and various articles suggest promising solutions in
constrained environments, research on trust and reputation is still at its
infancy. In this paper, we carry out a comprehensive literature review on
state-of-the-art research on the trust and reputation of IoT devices and
systems. Specifically, we first propose a new structure, namely a new taxonomy,
to organize the trust and reputation models based on the ways trust is managed.
The proposed taxonomy comprises of traditional trust management-based systems
and artificial intelligence-based systems, and combine both the classes which
encourage the existing schemes to adapt these emerging concepts. This
collaboration between the conventional mathematical and the advanced ML models
result in design schemes that are more robust and efficient. Then we drill down
to compare and analyse the methods and applications of these systems based on
community-accepted performance metrics, e.g. scalability, delay,
cooperativeness and efficiency. Finally, built upon the findings of the
analysis, we identify and discuss open research issues and challenges, and
further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin
IoT trust and reputation: a survey and taxonomy
IoT is one of the fastest-growing technologies and it is estimated that more
than a billion devices would be utilized across the globe by the end of 2030.
To maximize the capability of these connected entities, trust and reputation
among IoT entities is essential. Several trust management models have been
proposed in the IoT environment; however, these schemes have not fully
addressed the IoT devices features, such as devices role, device type and its
dynamic behavior in a smart environment. As a result, traditional trust and
reputation models are insufficient to tackle these characteristics and
uncertainty risks while connecting nodes to the network. Whilst continuous
study has been carried out and various articles suggest promising solutions in
constrained environments, research on trust and reputation is still at its
infancy. In this paper, we carry out a comprehensive literature review on
state-of-the-art research on the trust and reputation of IoT devices and
systems. Specifically, we first propose a new structure, namely a new taxonomy,
to organize the trust and reputation models based on the ways trust is managed.
The proposed taxonomy comprises of traditional trust management-based systems
and artificial intelligence-based systems, and combine both the classes which
encourage the existing schemes to adapt these emerging concepts. This
collaboration between the conventional mathematical and the advanced ML models
result in design schemes that are more robust and efficient. Then we drill down
to compare and analyse the methods and applications of these systems based on
community-accepted performance metrics, e.g. scalability, delay,
cooperativeness and efficiency. Finally, built upon the findings of the
analysis, we identify and discuss open research issues and challenges, and
further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin
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