Systematic Review on Security and Privacy Requirements in Edge Computing: State of the Art and Future Research Opportunities

Edge computing is a promising paradigm that enhances the capabilities of cloud computing. In order to continue patronizing the computing services, it is essential to conserve a good atmosphere free from all kinds of security and privacy breaches. The security and privacy issues associated with the edge computing environment have narrowed the overall acceptance of the technology as a reliable paradigm. Many researchers have reviewed security and privacy issues in edge computing, but not all have fully investigated the security and privacy requirements. Security and privacy requirements are the objectives that indicate the capabilities as well as functions a system performs in eliminating certain security and privacy vulnerabilities. The paper aims to substantially review the security and privacy requirements of the edge computing and the various technological methods employed by the techniques used in curbing the threats, with the aim of helping future researchers in identifying research opportunities. This paper investigate the current studies and highlights the following: (1) the classification of security and privacy requirements in edge computing, (2) the state of the art techniques deployed in curbing the security and privacy threats, (3) the trends of technological methods employed by the techniques, (4) the metrics used for evaluating the performance of the techniques, (5) the taxonomy of attacks affecting the edge network, and the corresponding technological trend employed in mitigating the attacks, and, (6) research opportunities for future researchers in the area of edge computing security and privacy

Nominal Curvature Design of Circular HSC Columns Confined with Post-tensioned Steel Straps

This article proposes new parameters for the practical design of circular high-strength concrete (HSC) columns confined with an innovative Steel Strapping Tensioning Technique (SSTT) using a nominal curvature approach. Previous experimental research has proven the effectiveness of the SSTT at providing active confinement and enhancing the ductility of HSC columns, but to date no practical procedures are available so that the technique can be widely adopted in design practice. The proposed design approach is based on results from segmental analyses of slender SSTT-confined circular columns subjected to eccentric loads. The results obtained from the analyses are used to determine the variables governing the design of such columns. The use of the proposed design parameters predicts conservatively the capacity of small-scale slender HSC circular columns confined using the SSTT, and can be thus used in the practical design of reinforced concrete (RC) structures

Identifying the Early Visible Symptoms of the Ganoderma-Infected Oil Palms: A Case Study on the Infected Palms Which Collapsed Within Twelve Months after Disease Census

In the region of Southeast Asia especially in Malaysia and Indonesia, Ganoderma Basal Stem Rot (BSR) disease is considered as the most devastating disease in oil palm industry. The objective of this study is to identify the important early visible symptoms which can give early signal that the palms infected by Ganoderma BSR disease will collapse within 12 months after the disease census conducted. The visible external symptoms of the disease considered were presence of bunch, presence of rotting trunk, presence of more than three unopened spears, and the number of active fruiting bodies Ganoderma species. A binary logistic regression was employed with the parameters of the model were estimated using maximum likelihood method. This study found that the infected palms which have more than five active fruiting body of Ganoderma species and did not produce any fruit bunch during the census most probably will collapse within 12 months after the census. This result suggests that the priority for curative action should be given to the infected palms which show these two visible symptoms during the census

Distribution of infected oil palms with Ganoderma basal stems root disease

The objective of this study is to spatially identify the pattern of Ganoderma disease under natural field epidemic using three different spatial point pattern analyses, which are nearest neighbor analysis and refined nearest neighbor analysis for first order spatial analysis, and Ripley’s K function for second order spatial analysis. Three commercial oil palm sites with three replicate areas per site were selected in this study with different age of palm tree. The nearest neighbor analysis showed that the spatial distribution of the infected palms in all the replicate areas at SKE0224 was clustered. Refined nearest neighbor analysis and Ripley’s K function also showed that the distribution of the infected palms in all the areas studied was clustered. But statistical test through Monte Carlo simulation showed that the cluster distribution of the infected palms in most of the areas studied was not statistically significant. Nevertheless, the study has proved that the spatial distribution of the infected palms under natural epidemic is not random, disperse or uniform but it is more to cluster pattern. This suggests the spread of the disease could be from tree to tree possibly through root contact as proved by many past studies

Water-Energy Nexus Cascade Analysis (WENCA) for simultaneous water-energy system optimisation

This paper presents a new numerical method called the Water-Energy Nexus Cascade Analysis (WENCA), developed based on the principal of Pinch Analysis. Water and energy are both valuable resources that are majorly used in industrial processes. Both water and energy are interdependent where increasing water demand will increase the energy demand and vice versa. In this paper, WENCA is introduced to simultaneously optimise both water and energy system that is interdependent. The methodology applies Cascade Analysis to individually optimise both system. As both systems are interdependent, altering one of the system will result in a change to the other system. An iterative method is then introduced to converge the analysis to obtain the optimal result for both systems. A case study comprising of both electricity and water demand of 6,875 kWh and 3,000 m3 from a residential area with 1,000 unit of houses is applied in this work. The electricity demand is met using fuel cell where hydrogen is produced through coal gasification (which utilised water as it raw material), a water treatment plant (WTP) is also introduced for water treatment to fulfil the water demands. The optimal result reveals that the WTP capacity is 3,200.73 m3, its corresponding water storage tank capacity is 175 m3, hydrogen power plant is 9 MW and its corresponding energy storage capacity is 4.13 MW

Estimating the yield loss of oil palm due to Ganoderma basal stem rot disease by using Bayesian Model Averaging

It is very crucial to planters to estimate the yield loss due to Ganoderma basal stem rot (BSR) disease in oil palm. However, currently there is a limited mathematical model available that can be used for that purpose. Therefore, this empirical study was conducted to build a mathematical model which can be used for yield loss estimation due to the disease. Three commercial oil palm plots with different production phases (i.e. steep ascent phase, plateau phase and declining phase) were selected as the study sites. The yield and disease severity of the selected palms in the three study sites were recorded for the duration of 12 months. Model averaging approach using Bayes theorem was used to build the model. This is also known as Bayesian Model Averaging (BMA). The BMA model revealed that planting preparation technique was the most important predictor of oil palm yield loss, followed by disease progress (measured using area under the disease-progress curve, AUDPC), disease severity, number of infected neighbouring palms, and two interaction terms. By using the developed BMA model, it was estimated that the economic loss can be up to 68% compared to the attainable yields of all the infected palms

Correlating health and wellness analytics for personalized decision making

© 2015 IEEE. Personalized healthcare envisions providing customized treatment and management plans to individuals at their doorstep. Key factors to ensure personalized healthcare is to involve with the individual in their daily life activities and process the gathered information to provide recommendations. We identified the mostly exposed domains for gathering chronic disease patients information that includes: clinical, social media, and daily life activities. Clinical data is related to the health-care of the patients while social media, sensory, and wearables data is related to the wellness data of the patients. A framework is required to monitor the health and wellness information of the patients for health and wellness analytics provisioning to the physicians for better decision making. We propose Personalized, Ubiquitous Life-care Decision Support System (PULSE); a state of the art decision support system that helps physicians and patients in life-style management of chronic disease patients such as Diabetes. The proposed approach not only utilizes clinical information but also personalized information by correlation to find hidden information using big data health analytic for improvement of life-care. PULSE provides health analytics by utilizing and processing clinical information of the patient. In the same way, it provides wellness analytics to the patients by using their social, activities, emotions and daily life information. The co-relation between clinical and personalized analytics is performed for better recommendations to the patients. This eventually results in improved life-care and healthy living of the individuals

Two-stages carbon emission pinch analysis for integrated system of renewable energy and electric vehicle

The introduction of electric vehicles to the transportation fleet has merged the power generation and transportation sectors into an integrated system. Rather than fuel sources, electricity is used to charge electric vehicles, so these vehicles play a vital role as an important green technology that could reduce carbon emissions in the transportation sector. This study aimed to develop a multi-stage carbon emission pinch analysis for an integrated system to optimise the energy mix for electricity generation. In the first stage, the minimum number of electric vehicles required to reduce transportation emissions was determined. In the second stage, the optimal energy mix for power generation sector was determined while including the electricity demand for the electric vehicle. Four scenarios, namely the business-as-usual scenario (S1); the public transport utilization scenario (S2); the electrification of vehicle scenario (S3); and the Integrated-Policies scenario (S4) were developed based on Peninsular Malaysia as a case study, to analyse the impact of different mitigation strategies on the country's economy. S1 was set as baseline for all the cases i.e., without any mitigation strategies. The results reveal that S4 was the best scenario, yielding a total cost saving percentage of 51.42 % compared to S1. For the power generation sector, 52 % of renewable energy (solar PV, biomass and biogas) utilisation would be needed in the energy mix to achieve the emission reduction target

A Review of Factors Affecting Ganoderma Basal Stem Rot Disease Progress in Oil Palm

In recent years, oil palm has grown on a major scale as it is a prominent commodity crop that contributes the most to almost every producing country’s gross domestic product (GDP). Nonetheless, existing threats such as the Ganoderma basal stem rot (BSR) disease have been deteriorating the oil palm plantations and suitable actions to overcome the issue are still being investigated. The BSR disease progression in oil palm is being studied using the disease progression through the plant disease triangle idea. This concept looks at all potential elements that could affect the transmission and development of the disease. The elements include pathogenic, with their mode of infection in each studied factor