Assessment of a Decision-Making Model for Monitoring the Success of a Project for Smart Buildings

Objective: To express the usage of intelligent concepts in the architectural building construction field that are primarily concerned with reducing building energy use. Improved energy-saving methods and the use of environmentally friendly design principles are essential in this field. This type of managerial decision-making is necessary for the success of these types of projects. Methods: monitoring the performance of intelligent buildings use the cost variance (CV) and schedule variation as standard metrics to track the progress of a project based on the save energy concept. Also, this research conducted a comparative study on Building Information Modelling (BIM) and (MCDM) decision-making limitations as presented in the article. Analysis: the conventional technique, on the other hand, is unable to offer data on variance from typical performance levels. The main point based on Delphi results of construction cost variables has been observed 19 effective factors. Finding and Novelty: The RII observed that the most effective aspects of an intelligent building are the number of floors in the building, the kind of structural design, and the size of the shadow cast on the surface of the building. The Multi-Criteria Decision Maker (MCDM) observed significant differences in planned value (PV) and actual value (AC) results. In addition, as a result of the current approach, it is possible to track project costs and timelines more precisely. Doi: 10.28991/CEJ-2023-09-01-010 Full Text: PD

Decision Support System to Select the Most Effective Strategies for Mitigating the Urban Heat Island Effect Using Sustainability and Resilience Performance Measures

As climate change continues to alter the temperature of the cities, various urban heat island mitigation strategies (UHIMSs) are now needed to be employed to mitigate the effects of increasing temperatures. However, to ensure their resilience and sustainability, the effectiveness of such strategies should be evaluated using a set of criteria. According to a review of the literature, there is a need for a comprehensive model and performance assessment tool that considers the various characteristics and features that are significant in assessing whether the chosen strategies are viable candidates for minimizing the effects of urban heat island (UHI). As a result, the primary purpose of this study is to develop a decision support system (DSS) to assist decision-makers in reducing the effects of the UHI by allowing them to choose the most viable mitigation method/technique based on resiliency and sustainability concerns. The DSS would function as a performance measure selecting tool in form of a quick-selection-guide-sheet of most effective method(s)/technique(s). Therefore, this study has identified, categorized, and organized affecting parameters in a comprehensive hierarchical framework based on sustainability and resilience. The system starts by creating a list of objectives (sustainability andresilience), criteria (economic, environmental, social, vulnerability, and resistance to change), attributes, and the most used mitigation methods for the UHI effect. The system\u27s second component is the main engine (using the Weighted Scoring method (WSM)), which is responsible for determining the best mitigation strategies - the system\u27s predefined goal. The WSM is being used in this study to develop matrices to do a pairwise comparison of criteria, assign a relative weight to each criterion, score each strategy against each criterion, and calculate the weighted scores based on gathered data from experts elicitation exercises. Decision-makers can analyze the UHIMSs after the matrix has been set up with weighted scores to find the best method that fits their needs (system objective). The third key component is the user-friendly interface, which combines the previous two components of the system and applies spreadsheets to present the best feasible mitigation strategy. The contribution this study seeks is to develop a DSS resembling a knowledge-sharing platform to support stakeholders like urban planners, architects, decision-makers, and policymakers in the extraction of UHIMSs, and in a wide scope, the expected benefit would be more sustainable more resilient design. In addition, this study serves as a foundation for the establishment of a dynamic computer-based decision support system (DSS) for selecting the most efficient UHIMSs

Memory-Aware Scheduling for Fixed Priority Hard Real-Time Computing Systems

As a major component of a computing system, memory has been a key performance and power consumption bottleneck in computer system design. While processor speeds have been kept rising dramatically, the overall computing performance improvement of the entire system is limited by how fast the memory can feed instructions/data to processing units (i.e. so-called memory wall problem). The increasing transistor density and surging access demands from a rapidly growing number of processing cores also significantly elevated the power consumption of the memory system. In addition, the interference of memory access from different applications and processing cores significantly degrade the computation predictability, which is essential to ensure timing specifications in real-time system design. The recent IC technologies (such as 3D-IC technology) and emerging data-intensive real-time applications (such as Virtual Reality/Augmented Reality, Artificial Intelligence, Internet of Things) further amplify these challenges. We believe that it is not simply desirable but necessary to adopt a joint CPU/Memory resource management framework to deal with these grave challenges. In this dissertation, we focus on studying how to schedule fixed-priority hard real-time tasks with memory impacts taken into considerations. We target on the fixed-priority real-time scheduling scheme since this is one of the most commonly used strategies for practical real-time applications. Specifically, we first develop an approach that takes into consideration not only the execution time variations with cache allocations but also the task period relationship, showing a significant improvement in the feasibility of the system. We further study the problem of how to guarantee timing constraints for hard real-time systems under CPU and memory thermal constraints. We first study the problem under an architecture model with a single core and its main memory individually packaged. We develop a thermal model that can capture the thermal interaction between the processor and memory, and incorporate the periodic resource sever model into our scheduling framework to guarantee both the timing and thermal constraints. We further extend our research to the multi-core architectures with processing cores and memory devices integrated into a single 3D platform. To our best knowledge, this is the first research that can guarantee hard deadline constraints for real-time tasks under temperature constraints for both processing cores and memory devices. Extensive simulation results demonstrate that our proposed scheduling can improve significantly the feasibility of hard real-time systems under thermal constraints

Optimising a defence-aware threat modelling diagram incorporating a defence-in-depth approach for the internet-of-things

Modern technology has proliferated into just about every aspect of life while improving the quality of life. For instance, IoT technology has significantly improved over traditional systems, providing easy life, time-saving, financial saving, and security aspects. However, security weaknesses associated with IoT technology can pose a significant threat to the human factor. For instance, smart doorbells can make household life easier, save time, save money, and provide surveillance security. Nevertheless, the security weaknesses in smart doorbells could be exposed to a criminal and pose a danger to the life and money of the household. In addition, IoT technology is constantly advancing and expanding and rapidly becoming ubiquitous in modern society. In that case, increased usage and technological advancement create security weaknesses that attract cybercriminals looking to satisfy their agendas. Perfect security solutions do not exist in the real world because modern systems are continuously improving, and intruders frequently attempt various techniques to discover security flaws and bypass existing security control in modern systems. In that case, threat modelling is a great starting point in understanding the threat landscape of the system and its weaknesses. Therefore, the threat modelling field in computer science was significantly improved by implementing various frameworks to identify threats and address them to mitigate them. However, most mature threat modelling frameworks are implemented for traditional IT systems that only consider software-related weaknesses and do not address the physical attributes. This approach may not be practical for IoT technology because it inherits software and physical security weaknesses. However, scholars employed mature threat modelling frameworks such as STRIDE on IoT technology because mature frameworks still include security concepts that are significant for modern technology. Therefore, mature frameworks cannot be ignored but are not efficient in addressing the threat associated with modern systems. As a solution, this research study aims to extract the significant security concept of matured threat modelling frameworks and utilise them to implement robust IoT threat modelling frameworks. This study selected fifteen threat modelling frameworks from among researchers and the defence-in-depth security concept to extract threat modelling techniques. Subsequently, this research study conducted three independent reviews to discover valuable threat modelling concepts and their usefulness for IoT technology. The first study deduced that integration of threat modelling approach software-centric, asset-centric, attacker-centric and data-centric with defence-in-depth is valuable and delivers distinct benefits. As a result, PASTA and TRIKE demonstrated four threat modelling approaches based on a classification scheme. The second study deduced the features of a threat modelling framework that achieves a high satisfaction level toward defence-in-depth security architecture. Under evaluation criteria, the PASTA framework scored the highest satisfaction value. Finally, the third study deduced IoT systematic threat modelling techniques based on recent research studies. As a result, the STRIDE framework was identified as the most popular framework, and other frameworks demonstrated effective capabilities valuable to IoT technology. Respectively, this study introduced Defence-aware Threat Modelling (DATM), an IoT threat modelling framework based on the findings of threat modelling and defence-in-depth security concepts. The steps involved with the DATM framework are further described with figures for better understatement. Subsequently, a smart doorbell case study is considered for threat modelling using the DATM framework for validation. Furthermore, the outcome of the case study was further assessed with the findings of three research studies and validated the DATM framework. Moreover, the outcome of this thesis is helpful for researchers who want to conduct threat modelling in IoT environments and design a novel threat modelling framework suitable for IoT technology

Cloudarmor: Supporting Reputation-Based Trust Management for Cloud Services

Cloud services have become predominant in the current technological era. For the rich set of features provided by cloud services, consumers want to access the services while protecting their privacy. In this kind of environment, protection of cloud services will become a significant problem. So, research has started for a system, which lets the users access cloud services without losing the privacy of their data. Trust management and identity model makes sense in this case. The identity model maintains the authentication and authorization of the components involved in the system and trust-based model provides us with a dynamic way of identifying issues and attacks with the system and take appropriate actions. Further, a trust management-based system provides us with a new set of challenges such as reputation-based attacks, availability of components, and misleading trust feedbacks. Collusion attacks and Sybil attacks form a significant part of these challenges. This paper aims to solve the above problems in a trust management-based model by introducing a credibility model on top of a new trust management model, which addresses these use-cases, and also provides reliability and availability

Net.Sense

Net.sense will server as a proof-of-concept of a new type of network management system, using biological models and statistical principles to address scalability, predictability, and reliability issues associated with managing the highly complex computer systems that we as a society have come to depend on

Reconfigurability in space systems : architecting framework and case studies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.Includes bibliographical references (p. 247-257).Reconfigurability in engineered systems is of increasing interest particularly in Aerospace Systems since it allows for resource efficiency, evolvability, and enhanced survivability. Although it is often regarded as a desirable quality for a system, it has traditionally been difficult to quantitatively analyze its effects on various system properties in the early design stage. In order to allow for gaining an in-depth understanding of the various aspects of reconfigurability and its relationship with a system's architecture, a framework encompassing a set of definitions, metrics, and methods has been proposed. Two different modeling schemes, based on Markov models and controls theory, are first developed to show how the states and time aspects of reconfigurable systems can be naturally modeled and studied. An analytical model for quantifying the effect of reconfigurability on mission logistics, specifically spare parts demands, is formulated and it is shown through one specific example that reconfigurable parts can allow for 33-50% mass reduction. The system availability, however, becomes very sensitive to the reliability of the parts. Two case studies are then used for detailed illustration of the application of the developed framework.(cont.) In the first case study, the effect of reconfigurability on a fleet of planetary surface vehicles for a surface exploration mission are analyzed. It is found that a fleet of reconfigurable vehicles can allow for a mass savings of up to 27% and their expected transport capability degradation is almost three times lower as compared to a fleet of non-reconfigurable vehicles. In the second case-study, the reconfiguration of low earth-orbit communication satellite constellations is considered for evolving to higher capacity levels. It is found that reconfiguring a previously deployed constellation can be a viable option only for certain capacity levels and multi-payload launch capability scenarios. In addition to the high level 'ility' perspectives, a lower level design assessment is also carried out through a survey of 33 representative reconfigurable systems. It is found that on average, for commercial items the cost of reconfigurability is 35%, and the average useful state occupancy time is always at least 10 times the reconfiguration time of the system. Based on the illustrative results of the case studies, and generalization of empirical data, a few principles and guidelines for design for reconfigurability are proposed.by Afreen Siddiqi.Ph.D