This page has only limited features, please log in for full access.

Unclaimed
Ah-Lian Kor
School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds LS1 3HE, UK

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 07 November 2020 in Sustainability
Reads 0
Downloads 0

Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy–related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algorithms are presented and discussed.

ACS Style

Madhubala Ganesan; Ah-Lian Kor; Colin Pattinson; Eric Rondeau. Green Cloud Software Engineering for Big Data Processing. Sustainability 2020, 12, 9255 .

AMA Style

Madhubala Ganesan, Ah-Lian Kor, Colin Pattinson, Eric Rondeau. Green Cloud Software Engineering for Big Data Processing. Sustainability. 2020; 12 (21):9255.

Chicago/Turabian Style

Madhubala Ganesan; Ah-Lian Kor; Colin Pattinson; Eric Rondeau. 2020. "Green Cloud Software Engineering for Big Data Processing." Sustainability 12, no. 21: 9255.

Journal article
Published: 25 August 2020 in Energies
Reads 0
Downloads 0

The energy efficiency of Data Center (DC) operations heavily relies on a DC ambient temperature as well as its IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of smart cloud-based applications. Consequently, the increased demand for computing power will inadvertently increase server waste heat creation in data centers. To improve a DC thermal profile which could undeniably influence energy efficiency and reliability of IT equipment, it is imperative to explore the thermal characteristics analysis of an IT room. This work encompasses the employment of an unsupervised machine learning technique for uncovering weaknesses of a DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for thermal management and cooling improvement that further feeds into DC recommendations. With the aim to identify overheated zones in a DC IT room and corresponding servers, we applied analyzed thermal characteristics of the IT room. Experimental dataset includes measurements of ambient air temperature in the hot aisle of the IT room in ENEA Portici research center hosting the CRESCO6 computing cluster. We use machine learning clustering techniques to identify overheated locations and categorize computing nodes based on surrounding air temperature ranges abstracted from the data. This work employs the principles and approaches replicable for the analysis of thermal characteristics of any DC, thereby fostering transferability. This paper demonstrates how best practices and guidelines could be applied for thermal analysis and profiling of a commercial DC based on real thermal monitoring data.

ACS Style

Anastasiia Grishina; Marta Chinnici; Ah-Lian Kor; Eric Rondeau; Jean-Philippe Georges. A Machine Learning Solution for Data Center Thermal Characteristics Analysis. Energies 2020, 13, 4378 .

AMA Style

Anastasiia Grishina, Marta Chinnici, Ah-Lian Kor, Eric Rondeau, Jean-Philippe Georges. A Machine Learning Solution for Data Center Thermal Characteristics Analysis. Energies. 2020; 13 (17):4378.

Chicago/Turabian Style

Anastasiia Grishina; Marta Chinnici; Ah-Lian Kor; Eric Rondeau; Jean-Philippe Georges. 2020. "A Machine Learning Solution for Data Center Thermal Characteristics Analysis." Energies 13, no. 17: 4378.

Preprint
Published: 15 July 2020
Reads 0
Downloads 0

Energy efficiency of Data Center (DC) operations heavily relies on IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of IoT- enabled smart systems. Consequently, increased demand for computing power will bring about increased waste heat dissipation in data centers. In order to bring about a DC energy efficiency, it is imperative to explore the thermal characteristics analysis of an IT room (due to waste heat). This work encompasses the employment of an unsupervised machine learning modelling technique for uncovering weaknesses of the DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for energy efficiency improvement that will feed into DC recommendations. The methodology employed for this research includes statistical analysis of IT room thermal characteristics, and the identification of individual servers that frequently occur in the hotspot zones. A critical analysis has been conducted on available big dataset of ambient air temperature in the hot aisle of ENEA Portici CRESCO6 computing cluster. Clustering techniques have been used for hotspots localization as well as categorization of nodes based on surrounding air temperature ranges. The principles and approaches covered in this work are replicable for energy efficiency evaluation of any DC and thus, foster transferability. This work showcases applicability of best practices and guidelines in the context of a real commercial DC that transcends the set of existing metrics for DC energy efficiency assessment.

ACS Style

Marta Chinnici; Anastasiia Grishina; Ah-Lian Kor; Eric Rondeau; Jean Philippe Georges. A Machine Learning Solution for Data Center Thermal Characteristics Analysis. 2020, 1 .

AMA Style

Marta Chinnici, Anastasiia Grishina, Ah-Lian Kor, Eric Rondeau, Jean Philippe Georges. A Machine Learning Solution for Data Center Thermal Characteristics Analysis. . 2020; ():1.

Chicago/Turabian Style

Marta Chinnici; Anastasiia Grishina; Ah-Lian Kor; Eric Rondeau; Jean Philippe Georges. 2020. "A Machine Learning Solution for Data Center Thermal Characteristics Analysis." , no. : 1.

Journal article
Published: 12 September 2019 in IFAC-PapersOnLine
Reads 0
Downloads 0

PERCCOM (PERvasive Computing and COMmunications in sustainable development) Masters is the first innovative international programme in Green ICT for educating and equipping new IT engineers with Green IT skills for sustainable digital applications design and implementation. After five years of running the PERCCOM programme, this paper provides an assessment of skills and employability in the context of Green jobs and skills. The paper ends with a list of recommendations for the development of environment related education curricula.

ACS Style

Kor Ah-Lian; Rondeau Eric; Andersson Karl; Porras Jari; Jean-Philippe Georges. Education in Green ICT and Control of Smart Systems : A First Hand Experience from the International PERCCOM Masters Programme. IFAC-PapersOnLine 2019, 52, 1 -8.

AMA Style

Kor Ah-Lian, Rondeau Eric, Andersson Karl, Porras Jari, Jean-Philippe Georges. Education in Green ICT and Control of Smart Systems : A First Hand Experience from the International PERCCOM Masters Programme. IFAC-PapersOnLine. 2019; 52 (9):1-8.

Chicago/Turabian Style

Kor Ah-Lian; Rondeau Eric; Andersson Karl; Porras Jari; Jean-Philippe Georges. 2019. "Education in Green ICT and Control of Smart Systems : A First Hand Experience from the International PERCCOM Masters Programme." IFAC-PapersOnLine 52, no. 9: 1-8.

Journal article
Published: 06 September 2019 in Energies
Reads 0
Downloads 0

Big Data applications have become increasingly popular with the emergence of cloud computing and the explosion of artificial intelligence. The increasing adoption of data-intensive machines and services is driving the need for more power to keep the data centers of the world running. It has become crucial for large IT companies to monitor the energy efficiency of their data-center facilities and to take actions on the optimization of these heavy electricity consumers. This paper proposes a Belief Rule-Based Expert System (BRBES)-based predictive model to predict the Power Usage Effectiveness (PUE) of a data center. The uniqueness of this model consists of the integration of a novel learning mechanism consisting of parameter and structure optimization by using BRBES-based adaptive Differential Evolution (BRBaDE), significantly improving the accuracy of PUE prediction. This model has been evaluated by using real-world data collected from a Facebook data center located in Luleå, Sweden. In addition, to prove the robustness of the predictive model, it has been compared with other machine learning techniques, such as an Artificial Neural Network (ANN) and an Adaptive Neuro Fuzzy Inference System (ANFIS), where it showed a better result. Further, due to the flexibility of the BRBES-based predictive model, it can be used to capture the nonlinear dependencies of many variables of a data center, allowing the prediction of PUE with much accuracy. Consequently, this plays an important role to make data centers more energy-efficient.

ACS Style

Raihan Ul Islam; Xhesika Ruci; Mohammad Shahadat Hossain; Karl Andersson; Ah-Lian Kor. Capacity Management of Hyperscale Data Centers Using Predictive Modelling. Energies 2019, 12, 3438 .

AMA Style

Raihan Ul Islam, Xhesika Ruci, Mohammad Shahadat Hossain, Karl Andersson, Ah-Lian Kor. Capacity Management of Hyperscale Data Centers Using Predictive Modelling. Energies. 2019; 12 (18):3438.

Chicago/Turabian Style

Raihan Ul Islam; Xhesika Ruci; Mohammad Shahadat Hossain; Karl Andersson; Ah-Lian Kor. 2019. "Capacity Management of Hyperscale Data Centers Using Predictive Modelling." Energies 12, no. 18: 3438.

Conference paper
Published: 09 July 2019 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

This study attempts to model smoking behavior in the United States using Current Population Survey data from 2010 and 2011. An array of demographic and socioeconomic variables is used in an effort to explain smoking behavior from roughly 139,000 individuals. Two regression techniques are employed to analyze the data. These methods found that individuals with children are more likely to smoke than individuals without children; females are less likely to smoke than males; Hispanics, blacks, and Asians are all less likely to smoke than whites; divorcees and widows are more likely to smoke than single individuals; married individuals are less likely to smoke than singles; retired individuals are less likely to smoke than working ones; unemployed individuals are more likely to smoke than working ones; and as education level increases after high school graduation, smoking rates decrease. Finally, it is recommended that encouraging American children to pursue higher education may be the most effective way to minimize cigarette smoking.

ACS Style

Ah-Lian Kor; Mitchell Reavis; Sanela Lazarevski; Reavis Mitch. Data Analytics: A Demographic and Socioeconomic Analysis of American Cigarette Smoking. Advances in Intelligent Systems and Computing 2019, 145 -156.

AMA Style

Ah-Lian Kor, Mitchell Reavis, Sanela Lazarevski, Reavis Mitch. Data Analytics: A Demographic and Socioeconomic Analysis of American Cigarette Smoking. Advances in Intelligent Systems and Computing. 2019; ():145-156.

Chicago/Turabian Style

Ah-Lian Kor; Mitchell Reavis; Sanela Lazarevski; Reavis Mitch. 2019. "Data Analytics: A Demographic and Socioeconomic Analysis of American Cigarette Smoking." Advances in Intelligent Systems and Computing , no. : 145-156.

Conference paper
Published: 23 June 2019 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

This research aims to assess and evaluate the impact on sustainability in buildings through implementation of ICT Smart Systems. The setting for this research will be for a large global organisation’s headquarters in Germany. The list of objectives is: to audit the ICT infrastructure used and to survey the existing smart systems implemented; to investigate the total energy expenditure and carbon footprint for ICT equipment during a yearly period; and to explore how to best transfer best green ICT practices to other buildings. Based on the findings in this paper, investing in energy-saving ICT equipment, or even a BMS, can be very cost beneficial to a company and reduce the carbon footprint of commercial buildings when implemented correctly.

ACS Style

Andreas Andressen; Lesley Earle; Ah-Lian Kor; Colin Pattinson. An Evaluation of ICT Smart Systems to Reduce the Carbon Footprint. Advances in Intelligent Systems and Computing 2019, 263 -274.

AMA Style

Andreas Andressen, Lesley Earle, Ah-Lian Kor, Colin Pattinson. An Evaluation of ICT Smart Systems to Reduce the Carbon Footprint. Advances in Intelligent Systems and Computing. 2019; ():263-274.

Chicago/Turabian Style

Andreas Andressen; Lesley Earle; Ah-Lian Kor; Colin Pattinson. 2019. "An Evaluation of ICT Smart Systems to Reduce the Carbon Footprint." Advances in Intelligent Systems and Computing , no. : 263-274.

Conference paper
Published: 02 November 2018 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

Our previous work focuses on how the nine tiles in the 2-D projection-based model for cardinal directions can be partitioned into sets based on horizontal and vertical constraints (called Horizontal and Vertical Constraints Model). In this paper, the 2-D Horizontal and Vertical Constraints model is adapted and extended into a 3-D Horizontal and Vertical Constraints Block model so that it facilitates easy reasoning with 3-D volumetric regions (i.e. without holes and single-pieced) in the real physical world (e.g. intelligent robotics, building construction, etc…). This model partitions a 3-D Euclidean space of a 3-D reference region into 9 blocks, namely, left, middlex, right, above, middley, below, left, middlez, right. The additional central block (or the Minimum Bounding Box of the 3-D reference region) is an intersection of the three blocks, namely, middlex, middley, and middlez. The added value of the 3-D Horizontal and Vertical Constraints Block model is the use of intuitive (i.e. commonsense) knowledge representation for 3-D orientation relations. However, the underlying formal representation of the model is facilitated through the use of the 3-D Cartesian Coordinate system, first order logic, and boolean algebraic expressions. The novel contribution of this research work is fostering reasoning with partial orientation relation related knowledge (note: these are called weak relations) and also integrating mereology into the 3-D model in order to render the representation of the model more expressive. Finally, composition of relations is the technique employed in this research to general new knowledge. Mereology is integrated into the model in order to render the model more expressively. Finally, several examples will demonstrate how the model could be used to make inferences about 3-D orientation relations.

ACS Style

Ah-Lian Kor. Qualitative Spatial Reasoning for Orientation Relations in a 3-D Context. Advances in Intelligent Systems and Computing 2018, 957 -984.

AMA Style

Ah-Lian Kor. Qualitative Spatial Reasoning for Orientation Relations in a 3-D Context. Advances in Intelligent Systems and Computing. 2018; ():957-984.

Chicago/Turabian Style

Ah-Lian Kor. 2018. "Qualitative Spatial Reasoning for Orientation Relations in a 3-D Context." Advances in Intelligent Systems and Computing , no. : 957-984.

Conference paper
Published: 01 October 2018 in 2018 IEEE International Conference on Computational Science and Engineering (CSE)
Reads 0
Downloads 0

The study and analysis of energy efficiency in Data Centers (DCs), through a set of globally accepted metrics, is an ongoing challenge. In particular, the area of productivity metrics is not completely explored, and there is no existing proposed metrics, which provides a direct measurement of the useful work in a DC. This paper proposes a methodology that addresses the problem of measurement, calculating, and evaluating the energy productivity assessment in Data Center (DC), which encompasses both the portion of energy employed for computing and energy wasted during computational work. It involves the estimation of productive energy consumption by a DC cluster based on the following: statistical data collection and interpretation, software for energy data analysis, and mathematical formulation. This current work is based on available data extracted through experiments conducted on the cluster "CRESCO4" from ENEA Data Center facilities. The dataset covers the power and job schedule characteristics running on the cluster for one year. This paper shows how to advance beyond state of the art for productivity metrics (e.g. useful work). It will also help enhance server performance and power management since the appropriate statistical data analysis provides a profile on server energy consumption behavior. Additionally, we make recommendations on how the productivity assessment could driver a new power efficiency management strategy, which is specifically targeted at DC manager and/or operators, and end-users of the facilities.

ACS Style

Anastasiia Grishina; Marta Chinnici; Davide De Chiara; Guido Guarnieri; Ah-Lian Kor; Eric Rondeau; Jean-Philippe Georges. DC Energy Data Measurement and Analysis for Productivity and Waste Energy Assessment. 2018 IEEE International Conference on Computational Science and Engineering (CSE) 2018, 1 -11.

AMA Style

Anastasiia Grishina, Marta Chinnici, Davide De Chiara, Guido Guarnieri, Ah-Lian Kor, Eric Rondeau, Jean-Philippe Georges. DC Energy Data Measurement and Analysis for Productivity and Waste Energy Assessment. 2018 IEEE International Conference on Computational Science and Engineering (CSE). 2018; ():1-11.

Chicago/Turabian Style

Anastasiia Grishina; Marta Chinnici; Davide De Chiara; Guido Guarnieri; Ah-Lian Kor; Eric Rondeau; Jean-Philippe Georges. 2018. "DC Energy Data Measurement and Analysis for Productivity and Waste Energy Assessment." 2018 IEEE International Conference on Computational Science and Engineering (CSE) , no. : 1-11.

Chapter
Published: 30 September 2018 in Developments in Advanced Control and Intelligent Automation for Complex Systems
Reads 0
Downloads 0

This paper is an extension of (Cristea et al. in International SEEDS conference, 2015) [1] and abstracted from (Cristea in Energy consumption of mobile phones, 2015) [2]. This research contributes to the potential of greening software application as discussed in (Kharchenko et al. in Green IT engineering: concepts, models, complex systems architectures, vol 74, 2017a) [3] and (Kharchenko et al. in Green IT engineering: components, networks and systems implementation, vol 105, 2017b) [4]. Additionally, green design principles abstracted from this research will be relevant for designing the systems in (Kondratenko et al. in Green IT Engineering: Components, Networks and Systems Implementation, 2017) [5] and (Kuchuk et al. in Green IT Engineering: Components, Networks and Systems Implementation, 2017) [6]. Battery consumption in mobile applications development is a very important aspect and has to be considered by all the developers in their applications. This study will present an analysis of different relevant concepts and parameters that may have impact on energy consumption of Windows Phone applications. This operating system was chosen because there is limited research even though there are related studies for Android and iOS operating systems. Furthermore, another reason is the increasing number of Windows Phone users. The objective of this research is to categorize the energy consumption parameters (e.g. use of one thread or several thread for the same output). The result for each group of experiments will be analyzed and a rule will be derived. The set of derived rules will serve as a guide for developers who intend to develop energy-efficient Windows Phone applications. For each experiment, one application is created for each concept and the results are presented in two ways: a table and a chart. The table presents the duration of the experiment, the battery consumed in the experiment, the expected battery lifetime and the energy consumption, while the charts display the energy distribution based on the main threads: UI thread, application thread and network thread.

ACS Style

Cristea Vlad Vasile; Colin Pattinson; Ah-Lian Kor. Mobile Phones and Energy Consumption. Developments in Advanced Control and Intelligent Automation for Complex Systems 2018, 243 -271.

AMA Style

Cristea Vlad Vasile, Colin Pattinson, Ah-Lian Kor. Mobile Phones and Energy Consumption. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2018; ():243-271.

Chicago/Turabian Style

Cristea Vlad Vasile; Colin Pattinson; Ah-Lian Kor. 2018. "Mobile Phones and Energy Consumption." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 243-271.

Chapter
Published: 30 September 2018 in Developments in Advanced Control and Intelligent Automation for Complex Systems
Reads 0
Downloads 0

This book chapter is adapted from El Khoury in Assessing the benefit of deploying EEE on commercial grade network switches, Unpublished PERCCOM Masters Dissertation, University of Lorraine, Nancy, France, 2017, [1] and it is closely linked to work published in Kharchenko et al. (eds.) in Green IT engineering: concepts, models, complex systems architectures. Studies in systems, decision and control, vol. 74. Springer, Cham, 2017, [2], Kharchenko et al. (eds.) in Green IT engineering: components, networks and systems implementation. Studies in systems, decision and control, vol. 105. Springer, Cham, 2017, [3]. Reducing power consumption of network equipment has been both driven by a need to reduce the ecological footprint of the cloud as well as the immense power costs of data centers. As data centers, core networks and consequently, the cloud, constantly increase in size, their power consumption should be mitigated. Ethernet, the most widely used access network still remains the biggest communication technology used in core networks and cloud infrastructures. The Energy-Efficient Ethernet or EEE standard introduced by IEEE in 2010, aims to reduce the power consumption of EEE ports by transitioning Ethernet ports into a low power mode when traffic is not present. As statistics show that the average utilization rate of ethernet links is 5% on desktops and 30% in data centers, the power saving potential of EEE could be immense. This research aims to assess the benefits of deploying EEE and create a power consumption model for network switches with and without EEE. Our measurements show that an EEE port runs at 12–15% of its total power when in low power mode. Therefore, the power savings can exceed 80% when there is no traffic. However, our measurements equally show that the power consumption of a single port represents less than 1% of the total power consumption of the switch. The base power consumed by the switch without any port is still significantly high and is not affected by EEE. Experiment results also show that the base power consumption of switches does not significantly increase with the size of the switches. Doubling the size of the switch between 24 and 48 ports increases power consumption by 35.39%. EEE has a greater effect on bigger switches, with a power (or energy) gain on the EEE-enabled 48-port switch compared to 2× EEE-enabled 24-port switch. On the other hand, it seems to be more energy-efficient to use 2 separate 24-port switches (NO EEE) than 2 separate 24-port switches (With EEE).

ACS Style

Joseph El Khoury; Eric Rondeau; Jean-Philippe Georges; Ah-Lian Kor. Assessing the Impact of EEE Standard on Energy Consumed by Commercial Grade Network Switches. Developments in Advanced Control and Intelligent Automation for Complex Systems 2018, 209 -242.

AMA Style

Joseph El Khoury, Eric Rondeau, Jean-Philippe Georges, Ah-Lian Kor. Assessing the Impact of EEE Standard on Energy Consumed by Commercial Grade Network Switches. Developments in Advanced Control and Intelligent Automation for Complex Systems. 2018; ():209-242.

Chicago/Turabian Style

Joseph El Khoury; Eric Rondeau; Jean-Philippe Georges; Ah-Lian Kor. 2018. "Assessing the Impact of EEE Standard on Energy Consumed by Commercial Grade Network Switches." Developments in Advanced Control and Intelligent Automation for Complex Systems , no. : 209-242.

Journal article
Published: 27 May 2018 in Advanced Information Systems
Reads 0
Downloads 0

Предметом вивчення в статті є процеси оцінювання кібербезпеки інформаційно-керуючих систем (ІКС). Метою є розробка техніки аналізу розрив процесу проведенні аналізу кібербезпеки. Завдання: розробити метод аналізу розривів у процесі оцінювання нефункціональних вимог до функціональної та кібербезпеки ІКС, заснований на класифікації вимог з урахуванням можливості їх декомпозиції, який включає в себе побудову поліпшеного кейса запевнення інформаційної безпеки і визначення контрзаходів щодо усунення виявлених розривів. Висновки. Наукова новизна отриманих результатів полягає в наступному: отримав подальшого розвитку метод забезпечення інформаційної безпеки цифрових компонентів ІКС шляхом проведення аналізу невідповідностей вимог з використанням процедур опису вразливостей і оцінки критичності наслідків вторгнень, а також визначення множини контрзаходів за критерієм «безпека-вартість», що дозволяє зменшити ризики до прийнятного рівня.

ACS Style

Oleg Illiashenko; Vyacheslav Kharchenko; Ah-Lian Kor. GAP-ANALYSIS OF ASSURANCE CASE-BASED CYBERSECURITY ASSESSMENT: TECHNIQUE AND CASE STUDY. Advanced Information Systems 2018, 2, 64 -68.

AMA Style

Oleg Illiashenko, Vyacheslav Kharchenko, Ah-Lian Kor. GAP-ANALYSIS OF ASSURANCE CASE-BASED CYBERSECURITY ASSESSMENT: TECHNIQUE AND CASE STUDY. Advanced Information Systems. 2018; 2 (1):64-68.

Chicago/Turabian Style

Oleg Illiashenko; Vyacheslav Kharchenko; Ah-Lian Kor. 2018. "GAP-ANALYSIS OF ASSURANCE CASE-BASED CYBERSECURITY ASSESSMENT: TECHNIQUE AND CASE STUDY." Advanced Information Systems 2, no. 1: 64-68.

Conference paper
Published: 01 May 2018 in 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT)
Reads 0
Downloads 0

The paper discusses a systematic approach to sustainable development. It puts forward an idea of analysing energy efficiency and sustainability of a particular product, service or even a process during the whole life-cycle. Minor carbon footprint or low energy consumption of a product during its operation or exploitation does not necessary mean that the product manufacturing, decommissioning and disposal are also sustainable. In this paper, we discuss a set of sustainable principles and propose a graphical notion describing key factors of product/process sustainability. We also consider information and communication technologies (ICT) as essential tools of sustainable development in various application domains. On the other hand, ICT themselves should be considered as an object of energy efficiency improvement. The paper discusses ICT impact on the environment and identifies the fundamental green ICT trade-off between dependability, performance and energy consumption. Finally, we consider problems and propose approaches to building green clouds and datacenters.

ACS Style

Anatoliy Gorbenko; Olga Tarasyuk; Ah-Lian Kor; Vyacheslav Kharchenko. Green economics: A roadmap to sustainable ICT development. 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT) 2018, 561 -567.

AMA Style

Anatoliy Gorbenko, Olga Tarasyuk, Ah-Lian Kor, Vyacheslav Kharchenko. Green economics: A roadmap to sustainable ICT development. 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT). 2018; ():561-567.

Chicago/Turabian Style

Anatoliy Gorbenko; Olga Tarasyuk; Ah-Lian Kor; Vyacheslav Kharchenko. 2018. "Green economics: A roadmap to sustainable ICT development." 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT) , no. : 561-567.

Journal article
Published: 01 May 2018 in Solar Energy
Reads 0
Downloads 0
ACS Style

Giuseppe Colantuono; Ah-Lian Kor; Colin Pattinson; Christopher Gorse. PV with multiple storage as function of geolocation. Solar Energy 2018, 165, 217 -232.

AMA Style

Giuseppe Colantuono, Ah-Lian Kor, Colin Pattinson, Christopher Gorse. PV with multiple storage as function of geolocation. Solar Energy. 2018; 165 ():217-232.

Chicago/Turabian Style

Giuseppe Colantuono; Ah-Lian Kor; Colin Pattinson; Christopher Gorse. 2018. "PV with multiple storage as function of geolocation." Solar Energy 165, no. : 217-232.

Journal article
Published: 30 April 2018 in Informatics
Reads 0
Downloads 0

A mobile ad hoc network (MANET) is a self-configuring wireless network in which each node could act as a router, as well as a data source or sink. Its application areas include battlefields and vehicular and disaster areas. Many techniques applied to infrastructure-based networks are less effective in MANETs, with routing being a particular challenge. This paper presents a rigorous study into simulation techniques for evaluating routing solutions for MANETs with the aim of producing more realistic simulation models and thereby, more accurate protocol evaluations. MANET simulations require models that reflect the world in which the MANET is to operate. Much of the published research uses movement models, such as the random waypoint (RWP) model, with arbitrary world sizes and node counts. This paper presents a technique for developing more realistic simulation models to test and evaluate MANET protocols. The technique is animation, which is applied to a realistic scenario to produce a model that accurately reflects the size and shape of the world, node count, movement patterns, and time period over which the MANET may operate. The animation technique has been used to develop a battlefield model based on established military tactics. Trace data has been used to build a model of maritime movements in the Irish Sea. Similar world models have been built using the random waypoint movement model for comparison. All models have been built using the ns-2 simulator. These models have been used to compare the performance of three routing protocols: dynamic source routing (DSR), destination-sequenced distance-vector routing (DSDV), and ad hoc n-demand distance vector routing (AODV). The findings reveal that protocol performance is dependent on the model used. In particular, it is shown that RWP models do not reflect the performance of these protocols under realistic circumstances, and protocol selection is subject to the scenario to which it is applied. To conclude, it is possible to develop a range of techniques for modelling scenarios applicable to MANETs, and these simulation models could be utilised for the evaluation of routing protocols.

ACS Style

Adrian Pullin; Colin Pattinson; Ah-Lian Kor. Building Realistic Mobility Models for Mobile Ad Hoc Networks. Informatics 2018, 5, 22 .

AMA Style

Adrian Pullin, Colin Pattinson, Ah-Lian Kor. Building Realistic Mobility Models for Mobile Ad Hoc Networks. Informatics. 2018; 5 (2):22.

Chicago/Turabian Style

Adrian Pullin; Colin Pattinson; Ah-Lian Kor. 2018. "Building Realistic Mobility Models for Mobile Ad Hoc Networks." Informatics 5, no. 2: 22.

Chapter
Published: 01 January 2018 in Media Influence
Reads 0
Downloads 0

Social media has become an integral part of many people's lives around the world. The main use of this communication channel is to connect with social circles. It is also widely used for commercial and business purposes. Governments are also keen to use social media as an alternative to the traditional communication channels. Nonetheless, when the level of use of social media in the government is compared to other fields, a clear gap becomes apparent. This chapter investigates the adoption of social media as a communication channel between citizens, public agencies and government departments; and considers a wide range of factors that affect the issue from the perspective of public agencies. This chapter presents an extensive literature review and proposes a framework that organises the critical factors that affect public agencies' efforts while implementing social media. We also provide a list of hypotheses to validate and evaluate the significance of these factors.

ACS Style

Reemiah Alotaibi; Muthu Ramachandran; Ah-Lian Kor; Amin Hosseinian-Far; Information Resources Management Association. Adoption of Social Media as Communication Channels in Government Agencies. Media Influence 2018, 106 -140.

AMA Style

Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far, Information Resources Management Association. Adoption of Social Media as Communication Channels in Government Agencies. Media Influence. 2018; ():106-140.

Chicago/Turabian Style

Reemiah Alotaibi; Muthu Ramachandran; Ah-Lian Kor; Amin Hosseinian-Far; Information Resources Management Association. 2018. "Adoption of Social Media as Communication Channels in Government Agencies." Media Influence , no. : 106-140.

Chapter
Published: 01 January 2018 in Technology Adoption and Social Issues
Reads 0
Downloads 0

Social media has become an integral part of many people's lives around the world. The main use of this communication channel is to connect with social circles. It is also widely used for commercial and business purposes. Governments are also keen to use social media as an alternative to the traditional communication channels. Nonetheless, when the level of use of social media in the government is compared to other fields, a clear gap becomes apparent. This chapter investigates the adoption of social media as a communication channel between citizens, public agencies and government departments; and considers a wide range of factors that affect the issue from the perspective of public agencies. This chapter presents an extensive literature review and proposes a framework that organises the critical factors that affect public agencies' efforts while implementing social media. We also provide a list of hypotheses to validate and evaluate the significance of these factors.

ACS Style

Reemiah Alotaibi; Muthu Ramachandran; Ah-Lian Kor; Amin Hosseinian-Far. Adoption of Social Media as Communication Channels in Government Agencies. Technology Adoption and Social Issues 2018, 773 -807.

AMA Style

Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far. Adoption of Social Media as Communication Channels in Government Agencies. Technology Adoption and Social Issues. 2018; ():773-807.

Chicago/Turabian Style

Reemiah Alotaibi; Muthu Ramachandran; Ah-Lian Kor; Amin Hosseinian-Far. 2018. "Adoption of Social Media as Communication Channels in Government Agencies." Technology Adoption and Social Issues , no. : 773-807.

Editorial
Published: 02 October 2017 in Mobile Information Systems
Reads 0
Downloads 0
ACS Style

Karl Andersson; Eric Rondeau; Ah-Lian Kor; Dan Johansson. Sustainable Mobile Computing and Communications. Mobile Information Systems 2017, 2017, 1 -2.

AMA Style

Karl Andersson, Eric Rondeau, Ah-Lian Kor, Dan Johansson. Sustainable Mobile Computing and Communications. Mobile Information Systems. 2017; 2017 ():1-2.

Chicago/Turabian Style

Karl Andersson; Eric Rondeau; Ah-Lian Kor; Dan Johansson. 2017. "Sustainable Mobile Computing and Communications." Mobile Information Systems 2017, no. : 1-2.

Chapter
Published: 06 September 2017 in Technology for Smart Futures
Reads 0
Downloads 0

This book chapter is an extension of (Bazarhanova et al., Belief rule-based environmental responsibility assessment for small and medium-sized enterprises (note: this includes a comparison with fuzzy logic), Proceedings of 2016 IEEE Future Technologies Conference, 6–7 December, San Francisco, US, 2016; Bazarhanova et al., A Belief Rule-Based Environmental Responsibility Assessment System for Small and Medium-Sized Enterprises (note: without comparison with fuzzy logic), International SEEDS Conference, 14–15th September, 2016, Leeds. (Won Highly Commended Award for Green Infrastructure Category, 2016)) and adaptation from (Bazarhanova, A Belief Rule-Based Environmental Responsibility Assessment System for Small and Medium-Sized Enterprises, An unpublished Masters Degree Dissertation, Leeds Beckett University. URL: https://www.doria.fi/bitstream/handle/10024/124773/Thesis%20Bazarhanova.pdf?sequence=2, 2016). This chapter proposes the use of belief rule-based (BRB) inference engine for Environmental Responsibility assessment in small- and medium-sized enterprises. Such a context-adapted approach is believed to generate well-balanced, sensible, and Green ICT readiness-adapted results, to help enterprises focus on making improvement on more sustainable business operations.

ACS Style

Anar Bazarhanova; Ah-Lian Kor; Colin Pattinson. Environmental Responsibility Assessment using Belief Rule Based Inference. Technology for Smart Futures 2017, 171 -194.

AMA Style

Anar Bazarhanova, Ah-Lian Kor, Colin Pattinson. Environmental Responsibility Assessment using Belief Rule Based Inference. Technology for Smart Futures. 2017; ():171-194.

Chicago/Turabian Style

Anar Bazarhanova; Ah-Lian Kor; Colin Pattinson. 2017. "Environmental Responsibility Assessment using Belief Rule Based Inference." Technology for Smart Futures , no. : 171-194.

Chapter
Published: 06 September 2017 in Technology for Smart Futures
Reads 0
Downloads 0

This book chapter is an extended version of (Kor et al., SMART-ITEM: IoT-Enabled Living. Proceedings of IEEE Future Technologies Conference 2016, San Francisco, 6–8 December, 2016). The main goal of this proposed project is to harness the emerging IoT technology to empower elderly population to self-manage their own health and stay active, healthy, and independent as long as possible within a smart and secured living environment. An integrated open-sourced IoT ecosystem will be developed. It will encompass the entire data life cycle which involves the following processes: data acquisition and data transportation; data integration, processing, manipulation, and computation; visualization; data intelligence and exploitation; data sharing; and data storage. This innovative cloud-based IoT ecosystem will provide a one-stop shop for integrated smart IoT-enabled services to support older people (greater or equal to 65 years old) who live alone at home (or care homes). Another innovation of this system is the design and implementation of an integrated IoT gateway for well-being wearable and home automation system sensors with varying communication protocols. The SMART-ITEM system and services will appropriately address the following: (i) smart health and care, (ii) smart quality of life, and (iii) SMART-ITEM social community. The development of the system will be based on the user-centered design methodology so as to ensure active user engagement throughout the entire project life cycle and necessary standards as well as compliances will be adhered to (e.g., security, trust, and privacy) in order to enhance user acceptance.

ACS Style

Ah-Lian Kor; Colin Pattinson; Max Yanovsky; Vyacheslav Kharchenko. IoT-Enabled Smart Living. Technology for Smart Futures 2017, 3 -28.

AMA Style

Ah-Lian Kor, Colin Pattinson, Max Yanovsky, Vyacheslav Kharchenko. IoT-Enabled Smart Living. Technology for Smart Futures. 2017; ():3-28.

Chicago/Turabian Style

Ah-Lian Kor; Colin Pattinson; Max Yanovsky; Vyacheslav Kharchenko. 2017. "IoT-Enabled Smart Living." Technology for Smart Futures , no. : 3-28.