• Integration, Interconnection, and Interoperability of IoT Systems

      Gravina, Raffaele; Palau, Carlos E; Manso, Marco; Liotta, Antonio; Fortino, Giancarlo (Springer International Publishing, 2018)
    • An intelligent anti-collision system for electric vehicles applications

      Chinazaekpere Ijeh, Ikenna; Shafik, Mahmoud; University of Derby (IOS Press, 2016-09)
      This paper presents the initial outcomes of the ongoing research to develop an intelligent online fault monitoring and anti-collision system for electric vehicle industrial applications. This is aiming to utilise the latest development in sensors technology and multi-level of redundancy approach, to improve the safety of electric vehicle and minimize the risk of road collision. This paper is focused on the development of the anti-collision system. The system is a network of sensors utilising the near real time embedded system. Four operational conditions were considered and some activities have been taken to control the speed and steering control system of the vehicle at an imminent collision. Visual alerts using LEDs were developed to indicate vehicles or obstacles along the path of the host vehicle even at an opposite direction. The proposed system was tested indoor using offshelf mini vehicle model and further field test have been planned to ensure the operability of the system in relevant applications. Research is still undertaken to develop the online fault detection, monitoring and online recovery tolerance system using multi-level of redundancy and a hot-standby dual control unit.
    • Intelligent augmented keyword search on spatial entities in real-life internet of vehicles

      Li, Yanhong; Wang, Meng; Du, Xiaokun; Feng, Yuhe; Luo, Changyin; Tian, Shasha; Anjum, Ashiq; Zhu, Rongbo; University of Derby (Elsevier, 2018-12-28)
      Internet of Vehicles (IoV) has attracted wide attention from both academia and industry. Due to the popularity of the geographical devices deployed on the vehicles, a tremendous amount of spatial entities which include spatial information, unstructured information and structured information, are generated every second. This development calls for intelligent augmented spatial keyword queries (ASKQ), which intelligently takes into account the locations, unstructured information (in the form of keyword sets), structured information (in the form of boolean expressions) of 182MinzuAvespatial entities. In this paper, we take the first step to address the issue of processing ASKQ in real traffic networks of IoV environments (ASKQIV) and focus on Top-k ASKQIV queries. To support network distance pruning, keyword pruning, and boolean expression pruning intelligently and simultaneously, a novel hybrid index structure called ASKTI is proposed. Note in the real-life traffic networks of IoV environments, travel cost is not only decided by the network distance, but also decided by some additional travel factors. By considering these additional factors, a combined factor Cftc of each road (edge) in the traffic network of IoV environments is calculated, and weighted network distance is calculated and adopted. Based on ASKTI, an efficient algorithm for Top-k ASKQIV query processing is proposed. Our method can also be extended to handle boolean range ASKQIV Queries and ranking ASKQIV Queries. Finally, simulation experiments on one real traffic network of IoV environments and two synthetic spatial entity sets are conducted. The results show that our ASKTI based method is superior to its competitors.
    • Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks

      Liu, Xiaozhu; Zhu, Rongbo; Anjum, Ashiq; Wang, Jun; Zhang, Hao; Ma, Maode; Wuhan University of Technology, Wuhan, China; South-Central University for Nationalities, Wuhan, China; University of Derby; Nanyang Technological University, Singapore (Elsevier, 2019-10-04)
      Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks (WSNs). However the existing data fusion schemes lead to additional delay overhead and power consumptions. In order to improve the performance of WSNs, an intelligent data fusion algorithm based on hybrid delay-aware clustering (HDC) in WSNs is proposed, which combines the advantages of single-layer cluster structure and multi-layer cluster structure, and adaptive selects the clustering patterns of the cluster by the decision function to achieve the tradeoff between network delay and energy consumption. The network model of HDC is presented, and theoretical analysis of the delay and energy consumption of single-layer cluster and multi-layer cluster are provided. And the energy efficient clustering algorithm and the dynamic cluster head re-selection algorithm are proposed to optimize network energy consumption and load balancing of the network. Simulation results show that, compared with the existing delay-aware models, the proposed scheme can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously.
    • Intelligent grid enabled services for neuroimaging analysis

      McClatchey, Richard; Habib, Irfan; Anjum, Ashiq; Munir, Kamran; Branson, Andrew; Bloodsworth, Peter; Kiani, Saad Liaquat; University of West England; University of Derby; National University of Science and Technology (Elsevier, 2013-12)
      This paper reports our work in the context of the neuGRID project in the development of intelligent services for a robust and efficient Neuroimaging analysis environment. neuGRID is an EC-funded project driven by the needs of the Alzheimer's disease research community that aims to facilitate the collection and archiving of large amounts of imaging data coupled with a set of services and algorithms. By taking Alzheimer's disease as an exemplar, the neuGRID project has developed a set of intelligent services and a Grid infrastructure to enable the European neuroscience community to carry out research required for the study of degenerative brain diseases. We have investigated the use of machine learning approaches, especially evolutionary multi-objective meta-heuristics for optimising scientific analysis on distributed infrastructures. The salient features of the services and the functionality of a planning and execution architecture based on an evolutionary multi-objective meta-heuristics to achieve analysis efficiency are presented. We also describe implementation details of the services that will form an intelligent analysis environment and present results on the optimisation that has been achieved as a result of this investigation.
    • An intelligent medical care solution for elderly people with long term health condition based on wireless sensors network technology

      Elsaadi, Riyad; Shafik, Mahmoud; University of Derby (UNSYS Digital, 2015-12-26)
      Older Adults are facing serious difficulties, on a regular basis, to manage their own daily life activities. To live independently and have a good quality of life is quite a challenge, since the majorly of them have long term health condition diseases. Health services providers across EU, informal and formal carer plays major roles in providing the necessary services and support. Diseases on this society are one of the leading causes of death, from which thousands of people die every year. Many of the non-communicable diseases can be prevented by tackling associated risk factors. The cost of treatment of such diseases in the EU is estimated to be over 70% of the Health Service budget. Treatment includes home-care, medication, consultation and many other relevant services. However, these services are still not adequate, due to the lack of implemented technology that enable the older adults to manage their daily life activities independently, taking medications, receive the necessary health services on time, which, in many cases leads to loss of lives and waste of NHS resources. Daily life activities management and telehealth remote monitoring system is one of the potential innovative approaches, to improve the older adult’s quality of life, help live independently, improve NHS services, sustain its economic growth and improve social development. It is a rapidly developing concept where daily life activities, health condition, medical information is transferred through interactive data, and audiovisual media and shared between services provider, informal and formal carer. This paper presents the initial outcomes of the ongoing research program that is planned to develop an Integrated Assisted Living Technology (ALT) multi-functional case driven wireless ad-hoc management system of the daily life activities of older adults using smart sensors and actuators, 3d-video, audio, radio frequency identification and wireless technology, combined with secure cloud and semantic data engineering.
    • Intelligent price alert system for digital assets - cryptocurrencies

      Chhem, Sronglong; Anjum, Ashiq; Arshad, Bilal; University of Derby (ACM Press, 2019-12)
      Cryptocurrency market is very volatile, trading prices for some tokens can experience a sudden spike up or downturn in a matter of minutes. As a result, traders are facing difficulty following with all the trading price movements unless they are monitoring them manually. Hence, we propose a real-time alert system for monitoring those trading prices, sending notifications to users if any target prices match or an anomaly occurs. We adopt a streaming platform as the backbone of our system. It can handle thousands of messages per second with low latency rate at an average of 19 seconds on our testing environment. Long-Short-Term-Memory (LSTM) model is used as an anomaly detector. We compare the impact of five different data normalisation approaches with LSTM model on Bitcoin price dataset. The result shows that decimal scaling produces only Mean Absolute Percentage Error (MAPE) of 8.4 per cent prediction error rate on daily price data, which is the best performance achieved compared to other observed methods. However, with one-minute price dataset, our model produces higher prediction error making it impractical to distinguish between normal and anomaly points of price movement.
    • An Inter-Cloud Meta-Scheduling (ICMS) simulation framework: architecture and evaluation

      Sotiriadis, Stelios; Bessis, Nik; Anjum, Ashiq; Buyya, Rajkumar; University of Derby; Technical University of Crete (Institute of Electrical and Electronic Engineers, 2015-02-03)
      Inter-cloud is an approach that facilitates scalable resource provisioning across multiple cloud infrastructures. In this paper, we focus on the performance optimization of Infrastructure as a Service (IaaS) using the meta-scheduling paradigm to achieve an improved job scheduling across multiple clouds. We propose a novel inter-cloud job scheduling framework and implement policies to optimize performance of participating clouds. The framework, named as Inter-Cloud Meta-Scheduling (ICMS), is based on a novel message exchange mechanism to allow optimization of job scheduling metrics. The resulting system offers improved flexibility, robustness and decentralization. We implemented a toolkit named “Simulating the Inter-Cloud” (SimIC) to perform the design and implementation of different inter-cloud entities and policies in the ICMS framework. An experimental analysis is produced and an improved performance is observed for a number of parameters such as job execution, makespan, and turnaround times. The results highlight that the overall performance of individual clouds is improved when these are brought together under the proposed ICMS framework.
    • Interest-aware content discovery in peer-to-peer social networks.

      Guo, Yonghong; Liu, Lu; Wu, Yan; Hardy, James; University of Derby (Association for Computing Machinery, 2018-05-01)
      With the increasing popularity and rapid development of Online Social Networks (OSNs), OSNs not only bring fundamental changes to information and communication technologies, but also make extensive and profound impact on all aspects of our social life. Efficient content discovery is a fundamental challenge for large-scale distributed OSNs. However, the similarity between social networks and online social networks leads us to believe that the existing social theories are useful for improving the performance of social content discovery in online social networks. In this paper, we propose an interest-aware social-like peer-to-peer (IASLP) model for social content discovery in OSNs by mimicking ten different social theories and strategies. In the IASLP network, network nodes with similar interests can meet, help each other and co-operate autonomously to identify useful contents. The presented model has been evaluated and simulated in a dynamic environment with an evolving network. The experimental results show that the recall of IASLP is 20% higher than the existing method SESD while the overhead is 10% lower. The IASLP can generate higher flexibility and adaptability and achieve better performance than the existing methods.
    • Interference mitigation through adaptive power control in wireless sensor networks

      Chincoli, Michele; Bacchiani, Claudio; Syed, Aly Aamer; Exarchakos, Geogios; Liotta, Antonio (IEEE, 2015)
    • Internet of everything: A large-scale autonomic IoT gateway

      Kang, Byungseok; Kim, Daecheon; Choo, Hyunseung; Sungkyunkwan University (IEEE, 2017-05-18)
      Gateways are emerging as a key element of bringing legacy and next generation devices to the Internet of Things (IoT). They integrate protocols for networking, help manage storage and edge analytics on the data, and facilitate data flow securely between edge devices and the cloud. Current IoT gateways solve the communication gap between field control/sensor nodes and customer cloud, enabling field data to be harnessed for manufacturing process optimization, remote management, and preventive maintenance. However, these gateways do not support fully-automatic configuration of newly added IoT devices. In this paper, we proposed a self-configurable gateway featuring real time detection and configuration of smart things over the wireless networks. This novel gateway's main features are: dynamic discovery of home IoT device(s), automatic updates of hardware changes, connection management of smart things connected over AllJoyn. We use the `option' field for automatic configuration of IoT devices rather than modify standard format of CoAP protocol. Proposed gateway functionality has been validated over the large-scale IoT testbed.
    • Internet-of-Things-based smart cities: Recent advances and challenges.

      Mehmood, Yasir; Ahmad, Farhan; Yaqoob, Ibrar; Adnane, Asma; Imran, Muhammad; Guizani, Sghaier; University of Bremen; University of Malaya; University of Derby; King Saud University; et al. (IEEE, 2017-09-08)
      The Internet of Things (IoT) is a revolutionary communication paradigm that aims to bring forth an invisible and innovative framework to connect a plethora of digital devices with the Internet. Thus, it intends to make the Internet more immersive and pervasive [1]. The emerging IoT market is continously gaining momentum as operators, vendors, manufacturers, and enterprises begin to recognize the opportunities it offers. According to the latest IDC forecast.1 https://www.telecompaper.com/news/global-iot-market-to-reach-usd-17-tln-in-2020-idc-1085269, accessed October 20, 2016. the worldwide IoT market will reach US 1.7trillionin2020upfromUS655.8 billion in 2014 with a compound annual growth rate of 16.9 percent. The devices alone are expected to represent 31.8 percent of the total worldwide IoT market in 2020. This greater percentage of the revenue in 2020 is expected through building IoT platforms, application softwares, and service-related offerings.
    • Intersections between IoT and distributed ledger

      Atlam, Hany F.; Wills, Gary B.; University of Southampton; Menoufia University, Shebeen El-Kom, Egypt (Elsevier, 2019-01-14)
      The Internet of Things (IoT) is growing exponentially. It allows not only humans but also all various devices and objects in the environment to be connected over the Internet to share their data to create new applications and services which result in a more convenient and connected lifestyle. However, the current centralized IoT architecture faces several issues. For instance, all computing operations of all nodes in the network are carried out using a single server. This creates a single point of failure in which if the server goes down, the entire system will be unavailable. Also, the IoT centralized architecture is an easy target of various types of security and privacy attacks, since all IoT data collected from different devices is under the full authority of a single server. Therefore, adopting one of the Distributed Ledger Technologies (DLTs) for the IoT may be the right decision. One of the popular types of DLTs is the blockchain. It provides an immutable ledger with the capability of maintaining the integrity of transactions by decentralizing the ledger among participating nodes in the blockchain network which eliminates the need for a central authority. Integrating the IoT system with the blockchain technology can provide several benefits which can resolve the issues associated with the IoT centralized architecture. Therefore, this chapter provides a discussion of the intersection between IoT and DLTs. It started by providing an overview of the DLT by highlighting its main components, benefits and challenges. The centralized IoT system is also discussed with highlighting its essential limitations. Then, the integration of blockchain with IoT is presented by highlighting the integration benefits. Various application and challenges of integrating blockchain with IoT are also discussed.
    • Introduction to special issue on risk and trust in embedded critical systems

      Rossebø, Judith E. Y.; Houmb, Siv H.; Georg, Geri; Franqueira, Virginia N. L.; Serpanos, Dimitrios; ABB Corporate Research, Norway; SecureNOK Ltd., Norway; Colorado State University; University of Central Lancashire; QCRI (Association for Computing Machinery, 2014-11)
    • An introduction to the design of small-scale embedded systems

      Wilmshurst, Tim; University of Derby (Palgrave, 2001-09)
      This book offers a comprehensive and balanced introduction to the design of small embedded systems. Important topics covered include microcontroller architectures, memory technologies, data conversion, serial protocols, program design, low power design, and design for the real time environment. The final chapter ingeniously applies systematic engineering design principles to embedded system design. While the Microchip PIC 16F84 is used extensively to illustrate the early material, examples elsewhere are drawn from a range of microcontroller families, leading to a broad view of device capabilities.
    • An investigation into the impacts of task-level behavioural heterogeneity upon energy efficiency in Cloud datacentres.

      Panneerselvam, John; Liu, Lu; Lu, Yao; Antonopoulos, Nikolaos; University of Derby; Jiangsu University (Elsevier, 2018-01-02)
      Cloud datacentre resources and the arriving jobs are addressed to be exhibiting increased level of heterogeneity. A single Cloud job may encompass one to several number of tasks, such tasks usually exhibit increased level of behavioural heterogeneity though they belong to the same job. Such behavioural heterogeneity are usually evident among the level of resource consumption, resource intensiveness, task duration etc. These task behavioural heterogeneity within jobs impose various complications in achieving an effective energy efficient management of the Cloud jobs whilst processing them in the server resources. To this end, this paper investigates the impacts of the task level behavioural heterogeneity upon energy efficiency whilst the tasks within given jobs are executed in Cloud datacentres. Real-life Cloud trace logs have been investigated to exhibit the impacts of task heterogeneity from three different perspectives including the task execution trend and task termination pattern, the presence of few proportions of resource intensive and long running tasks within jobs. Furthermore, the energy implications of such straggling tasks within jobs have been empirically exhibited. Analysis conducted in this study demonstrates that Cloud jobs are extremely heterogeneous and tasks behave distinctly under different execution instances, and the presence of energy-aware long tail stragglers within jobs can significantly incur extravagant level of energy expenditures.
    • Investigation into the relationship between standing audience density and absorption.

      Hammond, Ross; Hill, Adam J.; Mapp, Peter; University of Derby; Peter Mapp Associates (Institute of Acoustics, 2018-11)
      Predicting acoustics of occupied performance venues is problematic due to difficulties in the selection of accurate audience absorption coefficients. The absorption due to a small group of people measured in a reverberation chamber cannot be accurately transferred to larger audiences due to differences between area to edge ratio. Analysis of data from an FDTD acoustic model of a reverberation chamber with an audience modelled as columns distributed at different densities with various perimeter to area ratios, allows derived absorption coefficients to be transferable to larger audience sizes. For densely-packed audiences, diffraction results in low frequencies having linear correlation between audience size and total absorption. There is less increase in total absorption per person at higher frequencies. Comparable real-world measurements confirm these findings, allowing the verified absorption coefficients to be applied to an acoustic model of a performance venue to inspect audience effects on absorption for typical configurations.
    • Investigation of indecent images of children cases: Challenges and suggestions collected from the trenches.

      Franqueira, Virginia N. L.; Bryce, Joanne; Al Mutawa, Noora; Marrington, Andrew; University of Derby; University of Central Lancashire; Zayed University (Elsevier, 2017-12-02)
      Previous studies examining the investigative challenges and needs of Digital Forensic (DF) practitioners have typically taken a sector-wide focus. This paper presents the results of a survey which collected text-rich comments about the challenges experienced and related suggestions for improvement in the investigation of Indecent Images of Children (IIOC) cases. The comments were provided by 153 international DF practitioners (28.1% survey response rate) and were processed using Thematic Analysis. This resulted in the identification of 4 IIOC-specific challenge themes, and 6 DF-generic challenges which directly affect IIOC. The paper discusses these identified challenges from a practitioner perspective, and outlines their suggestions for addressing them.
    • An investigation of security trends in personal wireless networks

      Liu, Lu; Stimpson, Thomas; Antonopoulos, Nikolaos; Ding, Zhijun; Zhan, Yongzhao; University of Derby (Springer, 2013-08-31)
      Wireless networks are an integral part of day-to-day life for many people, with businesses and home users relying on them for connectivity and communication. This paper examines the problems relating to the topic of wireless security and the background literature. Following this, primary research has been undertaken that focuses on the current trend of wireless security. Previous work is used to create a timeline of encryption usage and helps to exhibit the differences between 2009 and 2012. Moreover, a novel 802.11 denial-of-service device has been created to demonstrate the way in which it is possible to design a new threat based on current technologies and equipment that is freely available. The findings are then used to produce recommendations that present the most appropriate countermeasures to the threats found.
    • IoT forensics: A state-of-the-art review, callenges and future directions

      Alenezi, Ahmed; Atlam, Hany; Alsagri, Reem; Alassafi, Madini; Wills, Gary; University of Southampton (SCITEPRESS - Science and Technology Publications, 2019-05-10)
      The IoT is capable of communicating and connecting billions of things at the same time. The concept offers numerous benefits for consumers that alters how users interact with the technology. With this said, however, such monumental growth within IoT development also gives rise to a number of legal and technical challenges in the field of IoT forensics. Indeed, there exist many issues that must be overcome if effective IoT investigations are to be carried out. This paper presents a review of the IoT concept, digital forensics and the state-of-the-art on IoT forensics. Furthermore, an exploration of the possible solutions proposed in recent research and IoT forensics challenges that are identified in the current research literature are examined. Picks apart the challenges facing IoT forensics which have been established in recent literature. Overall, this paper draws attention to the obvious problems – open problems which require further efforts to be addressed properly.