Smart Resource Research Articles

Smart City: Concept, Models, Technologies, Standardization

The digital transformation problems of modern urban economy are considered. Their relevance for Ukrainian cities is caused by the fact that there are already a significant number of "smart cities" in the world, which are comfortable for their residents and for the management of urban services. The outlined problem for Ukraine is that a complex scenario of intellectualization and digital transformation of Ukrainian cities has not been formed yet. Unresolved problems and challenges that hinder the digital transformation of Ukrainian cities, namely the lack of municipal information networks, are described. Areas of further research are outlined, in particular, the statistical study of "smart cities", which is based on the collection and application of large data for this purpose, as well as the implementation of foreign experience in the Ukrainian realities of the economy.
 The digital transformation of cities is reviewed as a change of existing business models of urban services, the creation of smart mobility, smart resource consumption. An infographic unity of resources, services and management systems should be created in order to coordinate the actions of related structures and services in case of emergencies and unforeseen situations. This involves increasing technological literacy for different segments of the urban population. Three models of "smart cities" are proposed, the successful operation of each depends on investment, their rational management, as well as improving the level of digital skills of the population. The manufacturability of urban infrastructure should be based on megatrends in the field of information technology, namely: mobility, social communications, cloud technologies, big data and predictive analytics, machine learning and artificial intelligence, cybersecurity technology, the Internet of Things. These technologies are end-to-end for the whole set of technological solutions developed for "smart" cities. The scenario of development of "smart city" from the technological point of view is described; its basic components are: smart physical infrastructure; smart digital infrastructure; digital platforms; integrated digital platforms.
 The idea of building a digital duplicate, which is an accurate reflection of the real city in digital reality - the information comes to it from various sensors, monitoring systems and resource counters. The received experience of functioning can be translated into reality if it is successful, or to refuse it. All this is done at minimal cost, time savings and without harm to the real city.
 It is concluded that: information and communication technologies in the field of housing and communal services ensure the reliability and security of urban systems and resource efficiency; the formation of "smart cities" in Ukraine is limited by the lack of technical base for the creation of information technology platforms; a roadmap for the digital transformation of the national economy has not been developed.

Toward Enabled Industrial Verticals in 5G: A Survey on MEC-Based Approaches to Provisioning and Flexibility

The increasing number of heterogeneous devices connected to the Internet, together with tight 5G requirements have generated new challenges for designing network infrastructures. Industrial verticals such as automotive, smart city and eHealthcare (among others) need secure, low latency and reliable communications. To meet these stringent requirements, computing resources have to be moved closer to the user, from the core to the edge of the network. In this context, ETSI standardized Multi-Access Edge Computing (MEC). However, due to the cost of resources, MEC provisioning has to be carefully designed and evaluated. This survey firstly overviews standards, with particular emphasis on 5G and virtualization of network functions, then it addresses flexibility of MEC smart resource deployment and its migration capabilities. This survey explores how the MEC is used and how it will enable industrial verticals.

Planning mm-Wave Access Networks Under Obstacle Blockages: A Reliability-Aware Approach

Millimeter-wave (mm-wave) technologies are the main driver to deliver the multiple-Gbps promise in next-generation wireless access networks. However, the GHz-bandwidth potential must coexist with a harsh propagation environment. While strong attenuations can be compensated by directional antenna arrays, the severe impact of obstacle blockages can only be mitigated by smart resource allocation techniques. Multi-connectivity, as multiple mm-wave links from a mobile device to different base stations, is one of them. However, the higher reliability provided by several access alternatives can be fully exploited only if uncorrelated link statuses are guaranteed. Therefore, spatial diversity must be enforced. Moreover, since interposing obstacles can block a link, short access links allow reducing the link unavailability probability. Smart base-station selections can be made once the network is deployed, however, our results show that much better results are achievable if spatial diversity and link-length aspects are directly included in the network planning phase. In this article, we propose an mm-wave access network planning framework that considers base-station spatial diversity, link lengths, and achievable user throughput, according to channel conditions and network congestion. The comparison against traditional k-coverage approaches shows that our approach can obtain much better access reliability, thus providing higher robustness to random obstacles and self-blockage phenomena.

An Examination of Security and Privacy Challenges in Internet of Things

The Internet of Things (IoT) has been growing to market from the past several years with great potential. Many several devices have been now available in the market based on IoT, which enables it to connect with your smart phones or with any other kind of smart resources, and then that device is ready to perform smart work via the Internet. With the help of IoT, we are now able to make our devices connect with the internet and then can be operated from anywhere from the geo location as well as it can store and retrieve a large amount of data for better communication between the end-user and the device. IoT also has a wide range of applications that are being used on many platforms. However, this great technology also has to face many problems and among all the problems the main issue arises with its security aspects. The major concern on using IoT security is the hacker wants to enter into the large network system using a particular device as all the devices are connected over the network. Not only this, many other security threats and malware are also a major concern in IoT. So taking these security aspects as a major concern this research paper reviews several security issues and challenges that occur in IoT. As there in every field when it comes to cyber security for any kind of data, we need to follow CIA Security Triangle i.e., Confidentiality, Integrity, and Availability of data. CIA security triangle is the most important concept in terms of security and also must be taken into consideration in the IoT domain. Therefore, considering all these facts and reviewing some of the latest documents as well as researches in the field of IoT, this paper has been based on all the facts related to IoT security issues and its desirable solution which is needed to be done and should follow the security triangle to an extent.

Quantitative Mitigation Analysis: An ecosystem valuation tool to facilitate planning, restoration and mitigation

Globally, human development has proceeded at a rapid pace for the past several decades for both terrestrial and aquatic/marine environments. Project developers, government decision-makers and the public have had little data regarding the relative values of natural resources, or losses thereof, to facilitate project – and corresponding natural resource takings/ecosystem degradation – decision-making, resulting in intrinsic, but poorly quantified, environmental degradation. Accordingly, we have found that an effective strategy for communicating the value of ecosystems and related natural resources to facilitate smart resource management is to monetize the replacement value of resource losses from development. A number of tools have been developed for monetizing resource value, including quantitative mitigation analysis to address compensating for ecosystem and related natural resource losses due to human development. Quantitative Mitigation Analysis is a methodology developed to assist project developers and regulatory agencies alike with developing or evaluating cost-effective, defensible, quantitatively based compensatory mitigation strategies for developments that result in the taking of, or diminution in quality to, habitats and related natural resources. Quantitative Mitigation Analysis quantifies loss of ecological function from proposed developments and determines the amount of mitigation required as compensation. This paper introduces and describes Quantitative Mitigation Analysis and presents a case example that demonstrates how Quantitative Mitigation Analysis may be applied to construction projects resulting in substantive habitat destruction for the benefit of project developers and the regulatory community alike.

Incorporating natural habitats into coastal risk assessment frameworks

The coastal risk assessment (CRA) has important implications for policy development, resilience enhancement, and risk reduction to reduce the magnitude and likelihood of future losses to coastal hazards. However, few if any existing in-practice CRA approaches account for the effects of coastal natural habitats (CNHs), which shield communities from natural hazards and support resilience enhancement in coastal regions. Here, we use a coupled human-nature system-based CRA framework to provide evidence on the influence of CNHs on coastal storm-risk levels and spatial distributions. We calculate a risk index for each coastal county along the U.S. Atlantic coast and employ different spatial assessment approaches to systematically analyse the risk. This index incorporates several bio-geo-physical variables (e.g., geomorphology, natural habitats, coastal relief, and historical data on sea level trends, wind, and wave) and data on socio-ecological systems. The index is calculated under two CNH scenarios (i.e., without- and with-habitat) and is further used for mapping the at-risk population. We find that the without-habitat scenario overestimates the population in the highest risk category by 10 % and the number of counties by as much as 40 % as compared to the with-habitat scenario—mostly in the Gulf region. Also, the without-habitat scenario miscalculates the spatial distribution of the risk (e.g., over/under-estimate the relative risk for Florida/New York). These findings highlight the role of CNHs to provide defensive services and the importance of incorporating CNHs into the risk assessment process. While the CNHs inclusive risk results are important for coastal risk-reduction through prioritization and smart resource allocation, the well evident influence of CNHs on risk level and its distribution is also supportive for conservationists to stress the policies relevant to the protection and restoration of coastal natural systems owing to their multiple services.

Research on topology identification technology of distribution station area based on distribution Transformer supervisory Terminal Unit

This paper proposes a topology identification idea based on the physical equipment and information fusion of the distribution network, which fully combines existing distribution automation master stations, intelligent distribution transformer terminals, smart meter equipment and information data resources, and uses carrier communication technology to reflect the topological relationship of the distribution station area, carry out research on key technologies of distribution network topology identification, in order to realize the comprehensive integration identification of the distribution station-linetransformer-household relationship and the distribution network topology structure, and improve data penetration between different systems ability to provide basic support for intelligent and lean operation and maintenance of the distribution network.

A Review on Green Caching Strategies for Next Generation Communication Networks

In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching.

A Deep Learning Approach for Mobility-Aware and Energy-Efficient Resource Allocation in MEC

Mobile Edge Computing (MEC) has emerged as an alternative to cloud computing to meet the latency and Quality-of-Service (QoS) requirements of mobile devices. In this paper, we address the problem of server resource allocation in MEC. Due to the dynamic load conditions on MEC servers, their resources need to be used intelligently to meet the QoS requirements of the users and to minimize server energy consumption. We present a novel resource allocation algorithm, called Power Migration Expand ( PowMigExpand ). Our algorithm assigns user requests to the optimal server and allocates optimal amount of resources to User Equipment (UE) based on our comprehensive utility function. PowMigExpand also migrates UE requests to new servers, when needed due to the mobility of users. We also present a low cost Energy Efficient Smart Allocator (EESA) algorithm that uses deep learning for energy efficient allocation of requests to optimal servers. The proposed algorithms consider varying load of incoming requests and their heterogeneous nature, energy efficient activation of servers, and Virtual Machine (VM) migration for smart resource allocation and, thus, is the first comprehensive approach to address the complex and multidimensional resource allocation problem using deep learning. We compare our proposed algorithms with other resource allocation approaches and show that our approach can handle the dynamic load conditions better. The proposed algorithms improve the service rate and the overall utility with minimum energy consumption. On average, it reduces 26% energy consumption of MESs and improves the service rate by 23%, compared with other algorithms. We also get more than 70% accuracy for EESA in allocating the resources of multiple servers to multiple users.

Context Aware Control Systems: An Engineering Applications Perspective

Cyber-physical systems revolve around context awareness, empowering objective-oriented services, products and operations based on real data. Self-aware and self-control systems are core elements in the Industry 4.0 framework towards self-sustainable adaptive manufacturing and personalized services. This development is witnessed by the context-aware pervasive assistance to users and machines in decisions making process for optimizing product performance and economic yield. While integration of the virtual and the physical world entails smart sensors communication and complex data analytics, it relies on artificial intelligence tools to manage process operations. The objective of the article is to create awareness that systems & control community must address theoretical and practical aspects from a larger perspective. Context aware control is emerging as a natural solution to maximize the use of available sensing instrumentation and the relatively low cost data logging, i.e. an important source for extracting information, interpreting and using context information and adapt its functionality to the current context of use. This article presents a concise overview of applications where context aware systems and control methodologies are relevant in the seven societal challenges acknowledged by European policy-makers: Digital Society; Food; Health and Well-Being; Smart Resource Management; Urban Planning, Mobility Dynamics and Logistics; New Energy Demand and Delivery; and Society.

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities.

Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. Smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). Smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2–4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices.

Artificial-Intelligence-Enabled Intelligent 6G Networks

With the rapid development of smart terminals and infrastructures, as well as diversified applications (e.g., virtual and augmented reality, remote surgery and holographic projection) with colorful requirements, current networks (e.g., 4G and upcoming 5G networks) may not be able to completely meet quickly rising traffic demands. Accordingly, efforts from both industry and academia have already been put to the research on 6G networks. Recently, artificial intelligence (AI) has been utilized as a new paradigm for the design and optimization of 6G networks with a high level of intelligence. Therefore, this article proposes an AI-enabled intelligent architecture for 6G networks to realize knowledge discovery, smart resource management, automatic network adjustment and intelligent service provisioning, where the architecture is divided into four layers: intelligent sensing layer, data mining and analytics layer, intelligent control layer and smart application layer. We then review and discuss the applications of AI techniques for 6G networks and elaborate how to employ the AI techniques to efficiently and effectively optimize the network performance, including AI-empowered mobile edge computing, intelligent mobility and handover management, and smart spectrum management. Moreover, we highlight important future research directions and potential solutions for AI-enabled intelligent 6G networks, including computation efficiency, algorithms robustness, hardware development and energy management.

A Bio-Inspired Solution to Cluster-Based Distributed Spectrum Allocation in High-Density Cognitive Internet of Things

With the emergence of Internet of Things (IoT), where any device is able to connect to the Internet and monitor/control physical elements, several applications were made possible, such as smart cities, smart health care, and smart transportation. The wide range of the requirements of these applications drives traditional IoT to cognitive IoT (CIoT) that supports smart resource allocation, automatic network operation and intelligent service provisioning. To enable CIoT, there is a need for flexible and reliable wireless communication. In this paper, we propose to combine cognitive radio (CR) with a biological mechanism called reaction–diffusion to provide efficient spectrum allocation for CIoT. We first formulate the quantization of qualitative connectivity-flexibility tradeoff problem to determine the optimal cluster size (i.e., number of cluster members) that maximizes clustered throughput but minimizes communication delay. Then, we propose a bio-inspired algorithm which is used by CIoT devices to form cluster distributedly. We compute the optimal values of the algorithm’s parameters (e.g., contention window) of the proposed algorithm to increase the network’s adaption to different scenarios (e.g., spectrum homogeneity and heterogeneity) and to decrease convergence time, communication overhead, and computation complexity. We conduct a theoretical analysis to validate the correctness and effectiveness of proposed bio-inspired algorithm. Simulation results show that the proposed algorithm can achieve excellent clustering performance in different scenarios.

Application of Smart Waste Management Strategies for Sustainable Waste Management

India is moving towards development of smart cities which requires a marked improvement in Municipal Solid Waste Management (MSWM) to provide a clean and aesthetically appealing environment specifically in urban agglomerations. Presently India is producing around 65 million tones of municipal solid waste annually and 80% of which is dumped simply on the open ground. Even after the Solid waste management rules 2016 comes into effect there is no marked improvement in the waste management. The use of technologies like Internet of Things (IoT) and adopting a policy of smart waste – smart resources it is possible to create more robust Sustainable solid waste management systems. IoT is a concept that connects numerous and various physical objects to the internet with the help of sensors and other wireless technologies, conceptually the process of connecting different types of devices extracting the data from them to perform an action in the context of data read. With Swatch Bharath, Clean India mission and the development of Smart cities projects the government of India is offering and encouraging a phenomenal change in waste management policies and action plans with an objective to make the waste management technically feasible, environmentally and financially sustainable. In the present study an assessment of existing waste management scenario was carried out for the semi urban location, Annamalai Nagar Special town Panchayat of Cuddalore District in Tamilnadu state. IoT based waste management has been proposed, the ill effects of the present waste management practices and likely benefits of the application of technology enhanced IoT based waste management have been compared for the real time waste management system.

Production service system enabled by cloud-based smart resource hierarchy for a highly dynamic synchronized production process

The rapidly changing market demands entail a modern production system to cope with ever more diversified production orders. Not only the parameters and flow of the production process, sometimes the production resources and the corresponding application systems which make production decision and control even need to be reconfigurable. Due to the inability to provide dynamically reconfigurable manufacturing resources, systems and application systems, enterprises have to sacrifice profits to narrow their business scope or take risks to purchase a large number of production resources. In any case, it has brought operational burden to enterprises. This paper systematically analyses the production management requirements of a large-scale production system in terms of both hardware (production equipment) and software (application system) which is oriented to dynamic production demands, and then proposes a production service system enabled by cloud-based smart resource hierarchy (PnSS-CSRH). The platform is based on an open resource management system and inherits the general cloud structure and the AUTOM framework. PnSS-CSRH provides industrial users with integrated and synchronization services for the software and hardware resources involved in the production process in the PnSS mode. Using the integrated service mode, PnSS-CSRH not only helps resource providers to increase the frequency of resource leases, provides customers with targeted and systemic hardware and software overall solutions, and increases the platform usage rate, which brings more benefits to the stakeholders of PnSS-CSRH. At last, the PnSS-CSRH is used to provide services to the case company to validate the effectiveness.

Intelligent Radio for Next Generation Wireless Communications: An Overview

This article discusses various issues on intelligent radio (IR) from a perspective of intelligent UE and intelligent BS. Unlike a traditional UE, an intelligent UE can automatically access channel resources, cooperate with other UEs, and manage interferences. To implement such an intelligent UE, innovative techniques should be used, such as smart resource sensing and grant-free transmission. The core of IR lies in the development of thinking hardware, which can collect/process vital information of the environment and manage its resources optimally to support ultra-broadband communications. In particular, an integrated radar-communication unit is one of the most critical environment sensors in an intelligent UE, which helps it to acquire accurate location and mobility information of its neighbors for cooperation and interference avoidance. The traditional physical layer designs (such as beamforming and MIMO) should be revolutionized for the development of IR. ML and other AI algorithms play an important role in both BS and UEs. The communication protocols should be re-designed as well. The IR can offer a very high spectrum efficiency and power efficiency and is one of the most important research topics for future-generation wireless communications.

RESOLVING PRIVACY CONFLICT FOR MAINTAINING PRIVACY POLICIES IN ONLINE SOCIAL NETWORKS

In recent years, the use of online social networks (OSNs) such as Facebook, Twitter etc has tremendous increased. Users see these OSNs as a useful tool to find friends and interact with them. Moreover, OSNs allow their users to share photos, videos, and express their thoughts, views and feelings. However, users are usually concerned about their privacy when using OSNs. These OSNs not only offer smart resources for virtual social interfaces and sharing of data but also improve a number of security and privacy issues. While OSNs allow a single user to manage access to her/his data, those currently do not provide any mechanism to apply privacy concerns over data associated with multiple users, remaining privacy harms largely unresolved and leading to the potential confession of information that at least one user planned to keep private. This is because the unrestricted image of a subject can be affected by photos or comments posted on a social network. In this way, recent studies shows that users are demanding better mechanisms to protect their privacy. For this concern, we provide a systematic mechanism to identify and resolve privacy conflicts in online social networks (OSNs). The first computational tool to resolve conflicts for multiparty privacy management in social media. This makes it enable to adapt different situations by modelling the concessions that users make to reach a solution to the conflicts. Our conflict resolution specifies a trade-off between privacy protection and data sharing by computing privacy risk and sharing loss.

Challenges facing management practice in the light of Industry 4.0: The example of Poland

The article outlines selected challenges brought by Industry 4.0 as well as consequences for Polish businesses in the modern process of their management. The concept is based on a close connection between physical objects and information network. Sophisticated networks of businesses are being created, connected with smart resources communicating via the Internet. This means cooperation within implemented cyber-physical systems affecting a company's environment, its production model, value-added chain of business processes and organisational structure.

Risk assessment for the sustainability of coastal communities: A preliminary study

With communities increasingly concentrated in coastal regions globally, governments and stakeholders call for cohesive risk assessments for future sustainability in the wake of natural hazards. This can only be achieved through risk-based decision-making and smart resources treatment. To provide a basis for such actions, we here propose a risk assessment (RA) framework focusing on the risk-resilience-sustainability nexus. In contrast to focusing on the traditional RA approach, we propose an integrative approach based on hazard, vulnerability, and resilience covering the full spectrum of RA for effective risk reduction. We further explain how the proposed framework can simultaneously provide useful input for resilience management in parallel to achieving certain Sustainable Development Goals (SDGs). We apply this framework for typhoon risk assessment (represented by a Typhoon Risk Index—TRI) of coastal counties of mainland China. Different TRIs e.g. total population, elderly population, non-adult population, and economic status are calculated for each coastal county to supplement multi-objective empirical measures for risk reduction. The RA results show a large spatial heterogeneity in typhoon risk with an increase in the risk from north to south along the coast of mainland China. The comparative results from this study are relevant to the prioritization of different regions for immediate or gradual actions, wise decision-making, and risk reduction through proper treatment of resources-related policy implications. The evaluation of the SDGs achievement status reveals that the overall performance of coastal provinces in mainland China is higher to achieve SDGs 3 and 15 followed by 13 and 8. The study shows that while Guangdong province is in the highest risk category, its achievement status for SDG-13 (climate actions, strengthening resilience) is the lowest relative to other provinces, which is critical. This study represents a major scientific contribution to mainland China's coastal risk management and calls for aligning risk-informed planning and sustainability frameworks.

Strategic Resource Allocation in Project Management: A Data-Driven Framework

Effective project management relies on smart resource allocation strategies that navigate the complexities, in project dynamics. However, it is important to consider factors when choosing projects for a portfolio and allocating resources to that portfolio. In this paper, we present a data-driven framework for strategic resource allocation in project management. By using the Fuzzy TOPSIS method this framework combines evaluations into a model improving decision-making accuracy. Our study identifies ten factors that contribute to project complexity and transforms opinions into fuzzy numbers to evaluate project performance. When we applied this framework to five projects, we gained insights into how they align with established criteria resulting in nuanced rankings based on calculated closeness coefficients. This research lays the foundation for resource allocation strategies by advocating for the integration of dynamic data sources and advanced analytical techniques. The goal is to enhance adaptability and facilitate implementation, within project management paradigms.