Resource Providers Research Articles

Utility Optimization for Multi-User Task Offloading in Mobile Ad Hoc Cloud: A Stochastic Game Approach

Offloading tasks to the mobile ad hoc cloud (MAHC) can improve the utility of mobile devices in scenarios without infrastructure. However, when multiple resource demanders (RDs) offload tasks to multiple resource providers (RPs) in the MAHC with task random generation, how to optimize the utility of RDs and the service quality of the MAHC is an issue worth researching. To this end, we investigate this issue from the stochastic game perspective. Firstly, we combine the obtained time, energy, and monetary revenue as the utility of each RD and construct the utility improvement of each RD as a static non-cooperative game. Secondly, according to the randomness of RD’s task generation, we transform the single-shot non-cooperative game into a stochastic game in an infinite time horizon to obtain the long-term utility. Thirdly, to reduce the computational complexity for achieving Nash equilibrium, we propose an action reduction alternate backward iteration algorithm according to the games characteristics and prove its convergence. Finally, we compare the utility obtained from the static game with the stochastic game, the numerical results indicating that the utility of each RD can be effectively improved by utilizing the stochastic game.

РОЛЬ ДЕРЖАВИ У ФОРМУВАННІ ТА РЕАЛІЗАЦІЇ ЗОВНІШНЬОТОРГОВЕЛЬНОЇ ПОЛІТИКИ УКРАЇНИ В УМОВАХ ЄВРОПЕЙСЬКОЇ ІНТЕГРАЦІЇ

The objective of the paper is to reveal the role of the state in the formation and implementation of Ukraine's foreign trade policy in the conditions of the European integration. At present development of world trade is under the impact of the active participation of the states in the trade flows formations through the use of the mechanism of state regulation. This makes it possible to combine national and international interests, which do not always coincide. Ukraine's participation in the processes of neoliberal globalization turned it into a raw material appendage of developed countries, as a result of which Ukraine lost a significant part of its potential. The current deterioration of Ukraine's economic condition makes it difficult to solve the problem of adaptation to the social standards of the EU, and, accordingly, the accession to it, therefore the issue of the role of the state in the formation and implementation of foreign trade policy in the conditions of European integration becomes important and requires detailed research. The state creates the necessary legal framework, which includes measures to define private property rights and guarantee compliance with contracts. Government also sets the “rules of the game” by regulating the relationship between businesses, resource providers and consumers. Based on legislation, the state acts as an arbiter in the field of foreign economic relations. The most important tool for achieving the goal should be the improvement of the mechanism of regulation of foreign economic activity in the direction of the optimal combination of the openness of the national economy with the risks of economic development in the conditions of globalization of the world economy and acceleration of accession to the EU

Multi-objective flexibility disaggregation to distributed energy management systems

Flexibility from stationary batteries and electric vehicles allow home energy management systems to optimally consume local photovoltaic generation. The aggregated flexibility potential of a set of energy management systems can further contribute to a common objective, e.g., peak shaving at the transformer station. This paper formalizes the (non-convex) goals of involved stakeholders when disaggregating a flexibility request to a pool of energy management systems as multi-objective problem. The proposed genetic algorithm optimizes for the resource aggregator ( minimizing cost and maximizing delivery probability ), the grid operator ( minimizing grid losses ), the resource provider ( maximizing autarky and self-consumption ), and a fairness provider ( maximizing fairness among participants ). A disaggregation schedule that satisfies the objectives of all stakeholders can be chosen a posteriori from the Pareto-optimal solution set, which is demonstrated with a case study on the IEEE 906 low voltage test feeder.

An intelligence energy consumption model based on BP neural network in mobile edge computing

Establishing an accurate edge server power model is helpful for resource providers to predict and optimize power consumption within edge data centers. Considering the fact that the accuracy of the previous energy consumption model is easily affected by the workload types, this paper develops an edge server power model based on BP (back propagation) neural network and feature selection, which is denoted by DSBF. For different task types, DSBF leverages “principal component analysis (PCA)” to analyze the contribution of each energy consumption parameter and selects “representative parameter”, and then builds a power model based on BP neural network. In contrast to other power models, DSBF can effectively handle the variable workload. To measure the effectiveness of the DSBF model, a series of experiments were conducted. The results suggest that compared with other energy consumption models, DSBF can better adapt to the changing workload and has advantages in predicting the accuracy of the energy consumption model.

Evaluating Ventures Fast and Slow: Sensemaking, Intuition, and Deliberation in Entrepreneurial Resource Provision Decisions

We examine the decision process of individuals evaluating whether to support an entrepreneurial endeavor. Such decisions are made by individuals under conditions of ambiguity and equivocality. Therefore, it is nearly impossible for resource providers to adopt a purely rational evaluative process in assessing a venture. Building on insights from sensemaking and social and cognitive psychology, we elaborate a theoretical model combining sensemaking, intuition, and deliberation to account for how entrepreneurial support decisions are made. The model reflects individual and social factors that impact this decision process and provides a basis for understanding entrepreneurial support decisions across diverse actors and contexts.

The role of prototype fidelity in technology crowdfunding

The presentation of a prototype is pervasive when technology entrepreneurs pitch to potential resource providers. Yet, we know little about how the fidelity of a prototype—the degree to which it approximates the final product—can affect funding decisions. We study the relationship between prototype fidelity and resource acquisition of nascent technology ventures in online crowdfunding. Based on the community logic under which crowdfunding operates and the diverse motivations of funders to participate, we develop the seemingly counterintuitive idea that moderate prototype fidelity is more effective in gaining support from funders than high prototype fidelity. Across our three empirical studies, we find support for the hypothesis that prototype fidelity has an inverted U-shaped relationship with crowdfunding performance. This relationship is moderated by the materiality of the offered rewards and the quality of the prototype presentation delivered through the online interface.

Exploring accommodations along the education to employment pathway for deaf and hard of hearing healthcare professionals.

BackgroundDeaf and hard of hearing (DHH) people are an underserved population and underrepresented among healthcare professionals. A major barrier to success for DHH healthcare professionals is obtaining effective accommodations during education and employment. Our objective: describe DHH individuals’ experiences with accommodations in healthcare education.MethodsWe used an online survey and multipronged snowball sampling to recruit participants who identify as DHH and who had applied to a U.S. health professional school (regardless of acceptance status). One hundred forty-eight individuals representing multiple professions responded; 51 had completed their training. Over 80% had been accepted to, were currently enrolled, or had completed health professions schools or residency programs, and/or were employed. The survey included questions addressing experiences applying to health professions programs and employment; satisfaction with accommodations in school and training; having worked with a disability resource professional (DRP); and depression screening.ResultsUse and type of accommodation varied widely. While in school, respondents reported spending a mean of 2.1 h weekly managing their accommodations. Only 50% were highly satisfied with the accommodations provided by their programs. Use of disability resource providers (DRPs) for accommodations was highest during school (56%) and less frequent during post-graduate training (20%) and employment (14%). Respondents who transitioned directly from school to employment (versus via additional training) were more satisfied with their accommodations during school and were more likely to find employment (p = 0.02). Seventeen respondents screened positive for risk of depression; a positive screen was statistically associated with lower school accommodation satisfaction.ConclusionsDHH people study and practice across many health professions. While respondents were mostly successful in entering health professions programs, accommodation experiences and satisfaction varied. Satisfaction with accommodations was related to successful employment and wellness. Low satisfaction was associated with higher likelihood of depression symptoms. To increase representation in the workforce, healthcare professional schools, training programs, and employers should enhance support for the learning and working climates for people with disabilities.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12909-022-03403-w.

Creating the model of balanced business development based on ecosystem approach

The object of research is the process of creating effective relationships between the participants of the economic system, which is based on the need to ensure its balanced development in an unstable environment. One of the most problematic places is that at present the main criterion for the effectiveness of the model for organizing relationships between participants is the economic result, other aspects of the rational creation of an ecosystem are not considered, namely: innovative, environmental, social. The study proved that considering a systematic approach allows making effective management decisions at the level of a business ecosystem, considering the results obtained by all its agents. The basis of the modelof balanced business development model is the transition to a circular economy, which allows reducing resource consumption, reducing the negative impact on the environment, and complying with relevant socio-economic standards. On the example of an agricultural complex, a model of an agribusiness ecosystem was created, including participants and internal relationships between them. The agents of the internal environment include resource (service) providers, agricultural manufacturers and customers (buyers), detailing their roles in this system. A methodical approach to assessing the effectiveness of management decisions based on a multi-criteria assessment in four areas is proposed: economic, environmental, social, and innovative. For implementation, one should choose a solution that gives the maximum value of the integral indicator at the system level, considering the participation of each of its agents. The proposed solutions will contribute to more sustainable production and consumption patterns, which will provide opportunities for developed and developing countries to achieve economic growth and sustainable development.

Time series sentiment analysis (SA) of relief operations using social media (SM) platform for efficient resource management

The ease of access to the internet has sparked a worldwide interest in SM in recent years. The possibilities for the use of SM as a potential source in improving the management of disasters are increasing. Although there is an existing research ongoing with the analysis of the usage of SM during disasters, but none of the works have exploited the use of explainable artificial intelligence (XAI) for the validation of the transparency of the ML models. The contribution of this research is two-fold: Firstly, ML based time series analysis for relief operations using social media information with situational information gathered using Twitter from the users and resource providers and secondly, XAI has been used to increase the transparency and understand-ability of model decisions. For the case study, public dataset from Nepal, Italy earthquakes, COVID-19 dataset along with originally collected Twitter dataset has been considered. The performance of the extreme gradient boosting (xgboost) model is relatively superior than other techniques with 10-fold training mean accuracy of 87.17%. Thus, the experiments conclude the possibility of automation for the time series analysis for optimal relief operation management to serve the victims in the most efficient way and to control legal and administration implications.

Proxy Re-Encryption Scheme for Decentralized Storage Networks

Storage is a promising application for permission-less blockchains. Before blockchain, cloud storage was hosted by a trusted service provider. The centralized system controls the permission of the data access. In web3, users own their data. Data must be encrypted in a permission-less decentralized storage network, and the permission control should be pure cryptographic. Proxy re-encryption (PRE) is ideal for cryptographic access control, which allows a proxy to transfer Alice’s ciphertext to Bob with Alice’s authorization. The encrypted data are stored in several copies for redundancy in a permission-less decentralized storage network. The redundancy suffers from the outsourcing attack. The malicious resource provider may fetch the content from others and respond to the verifiers. This harms data integrity security. Thus, proof-of-replication (PoRep) must be applied to convince the user that the storage provider is using dedicated storage. PoRep is an expensive operation that encodes the original content into a replication. Existing PRE schemes cannot satisfy PoRep, as the cryptographic permission granting generates an extra ciphertext. A new ciphertext would result in several expensive replication operations. We searched most of the PRE schemes for the combination of the cryptographic methods to avoid transforming the ciphertext. Therefore, we propose a new PRE scheme. The proposed scheme does not require the proxy to transfer the ciphertext into a new one. It reduces the computation and operation time when allowing a new user to access a file. Furthermore, the PRE scheme is CCA (chosen-ciphertext attack) security and only needs one key pair.

Dynamic scheduling of heterogeneous resources across mobile edge-cloud continuum using fruit fly-based simulated annealing optimization scheme

Achieving sustainable profit advantage, cost reduction and resource utilization are always a bottleneck for resource providers, especially when trying to meet the computing needs of resource hungry applications in mobile edge-cloud (MEC) continuum. Recent research uses metaheuristic techniques to allocate resources to large-scale applications in MECs. However, some challenges attributed to the metaheuristic techniques include entrapment at the local optima caused by premature convergence and imbalance between the local and global searches. These may affect resource allocation in MECs if continually implemented. To address these concerns and ensure efficient resource allocation in MECs, we propose a fruit fly-based simulated annealing optimization scheme (FSAOS) to serve as a potential solution. In the proposed scheme, the simulated annealing is incorporated to balance between the global and local search and to overcome its premature convergence. We also introduce a trade-off factor to allow application owners to select the best service quality that will minimize their execution cost. Implementation of the FSAOS is carried out on EdgeCloudSim Simulator tool. Simulation results show that the FSAOS can schedule resources effectively based on tasks requirement by returning minimum makespan and execution costs, and achieve better resource utilization compared to the conventional fruit fly optimization algorithm and particle swarm optimization. To further unveil how efficient the FSAOSs, a statistical analysis based on 95% confidential interval is carried out. Numerical results show that FSAOS outperforms the benchmark schemes by achieving higher confidence level. This is an indication that the proposed FSAOS can provide efficient resource allocation in MECs while meeting customers’ aspirations as well as that of the resource providers.

Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems.

Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve themselves of the load of dealing with redundant data contents. This must be protected to prevent the theft of personal belongings, and privacy must be improved as well. Different research projects have been suggested to ensure the safe management of the information included within the data content. The security of current research projects, on the contrary, still needs improvement. As a result, this method has been suggested to address the security concerns associated with cloud computing. The primary goal of this study effort is to offer a safe environment for cloud users while also increasing the profit of cloud resource providers by managing and securely delivering data contents to the cloud users. The bulk of sectors, including business, finance, military, and healthcare industry, do not store data in cloud-based storage systems. This technique is used to attract these kinds of customers. Increasing public acceptance, medical researchers are drawn to cloud computing because it allows them to store their study material in a centralized location and distribute and access it in a more flexible manner. They were collected from numerous individuals who were being evaluated for medical care at the time. Scalable and enhanced key aggregate cryptosystem is a protected data protection method that provides highly effective security in the healthcare industry. When parties interested in a dispute disagree on the outflow of sensitive information, this technique manages the disputes and ensures the data security deployment of a cloud-based intelligent health monitoring system for the parties involved. The encrypted data structure of medical and healthcare prescriptions is recorded as they move through the hands of patients and healthcare facilities, according to the technique recommended. The double encryption approach is used in order to raise the overall degree of security. An encryption class is created by referring to the Ciphertext ID during the encryption procedure. The keyholder is a master secret key that facilitates in the recovery of the secret keys of various monsters and creatures by acting as a conduit between them. It is transferred and stored as a single aggregate for the benefit of the patient or customer in order to make decryption more convenient and efficient. A safe connection between cloud-based intelligent health monitoring systems and healthcare organizations and their patients may be established via the use of a key aggregation cryptosystem and a double encryption approach, according to the researchers. Because of this, when compared to earlier techniques, the findings reveal that the research methodology provides high levels of security in terms of confidentiality and integrity, in addition to excellent scalability.

Organization of lifelong education of library staff in the electronic environment

The object of the report is to present a complex approach to lifelong professional education of library specialists in the digital environment, used in the Far Eastern State Scientific Library, to disclose the factors influencing quantitative and qualitative indicators in this sphere, to identify problematic and positive aspects based on the results of activities for the period of 2017–2021. The main attention is paid to the system of lifelong education of the staff of public libraries in the Khabarovsk Territory, closely related to the activities of the Center for Professional Development on the basis of the Far Eastern State Scientific Library, founded in 2002 with the support of the State Public Scientific and Technological Library of the Siberian Branch of the Russian Academy of Sciences and received the first license in the Far East to conduct educational activities on the basis of the library institution in 2004. Licensed programs of upgrading skills of library specialists of the region, short-term training in the framework of non-formal education, information and methodological support of educational activities (generation of information resources in modern formats in modern formats on current areas of library activity, development of network educational projects aimed at improving professional level of staff of the Far Eastern State Scientific Library and municipalities of the Khabarovsk Territory, support of professional skills competitions, analysis of the libraries activities) are examined. In the context of the digital space formation, the efforts of the Far Eastern State Library are aimed at interacting with partner libraries, providers of information resources, updating pedagogical tools with an emphasis on a competencybased approach, expanding the list of educational programs, introducing distance learning on additional professional programs, and providing open access to digitized educational resources.

Library Patrons’ Personal Data as Regards to Access to Licensed Resources

The article deals with some issues of personal data processing and management in Russian libraries interactions with licensed resources providers. The author analyzes international practice on the libraries’ way to establishing main principles of personal data privacy and security: minimal data transfer and informed patron’s agreement on personal data processing. List of principles set up by “NISO consensus principles on users’ digital privacy in library, publisher, and software-provider systems” are analyzed as well as American Library Association documents. Specific problems of personal data transfer from Russian electronic library systems providers to libraries are analyzed and some solutions are suggested.

Regulating Journalism in the Digital Age

The research examined national and international legislation on activity of online news and the role of artificial intelligence in this sphere. Authors analyzed both international acts and recommendations, EU’s, India’s, Nepal’s, UAE’s, Kazakhstan’s and UK’s laws and ECHR’s decisions. The core concepts are liberal (European) and strict (Eastern). The European approach to mass media involves self-regulation and some basic state restrictions, whereas the Eastern system focuses on developing an allowed-content standards and controlling state bodies. The authors concluded that such a classification is quite vague since many countries have some features of both approaches, so that co-regulation arises. The authors underlined trends in formulating the concept and its regulatory aspects. Due to legal uncertainty and linguistic diversity of definitions, online media may include social network accounts, providers of audiovisual media services, websites (both electronic versions of printed publications and separate publishing houses) and other Internet resources. All of them must abide by the decisions of the Press Councils and the Ombudsmen, obtain licenses and follow the rules of prohibited content, developing its own system of tracking and rapid response (including via artificial intelligence).

A meta-analysis of cross-country context effects on the link between green product strategy and financial performance

PurposeDecades of research offer mixed results regarding the relationship between green product strategies and corporate financial performance. On the one hand, many scholars put forward green product strategies as a source of competitive advantage and in turn enhance financial performance. On the other hand, some studies suggest the opposite – that green product strategies may encounter managerial difficulties or are too costly, consequently leading to meager, if any, financial gain. This study explores cross-country contextual differences as a contingency to resolve this inconsistency. Thus, the research question is, “Do stakeholders of a country affect the link between green product strategies and financial performance?”Design/methodology/approachUsing a meta-analytic approach, the authors examine three country-level contingencies related to stakeholders: the impact of regulatory (stringency of environmental regulators), economic (consumer economic wealth) and political conditions (democratic vs. authoritarian governments) of a country in which the effects of a green product strategy on financial performance may vary.FindingsConsistent with our predictions, the meta-analysis of 26 studies published over a 20-year period reveals that green products positively relate to financial performance in countries with lax environmental regulation, low consumer economic status and authoritarian regimes.Originality/valueThe authors applied both (natural) resource-based and resource dependence theories by focusing on the interactions between firms' internal resources/capabilities and the external resources that firms can access. By doing so, the study adds to our understanding of stakeholders as resource providers to enhance financial benefits of green product strategies and provide insight into key boundary conditions of the link.

DIGITAL BUSINESS MODEL TYPES: UNDERSTANDING THEIR MECHANISMS AS RECIPES TO COMMERCIALISE DIGITAL TECHNOLOGIES

The increasingly digital business landscape has created manifold novel opportunities as well as threats to traditional business models. In consequence, a broad variety of digital business models emerged. Powerful tools and managerial guidance on how to shape digital strategies in this volatile and uncertain terrain are sought-after, but remain rare. Building on an analysis of the world’s top-1.000 venture funded technology startups over the last decade, we identify 49 novel business model types that describe firms as vendors of digitally enabled products and services, as providers of resources and capabilities for digital business, and as facilitators of intermediation. Furthermore, we identify the novelties of these digital business models types in their components, i.e., value proposition as well as their value creation, delivery, and capture processes. The result is a recipe collection of novel mechanisms to guide and inspire other firms when commercialising digital technologies in their business models.

Game Strategy Selection of Multiple Participants in Cloud Manufacturing Alliance

Introducing the cloud platform operator (CPO) to manage all kinds of manufacturing services on the cloud service platform, the game strategy selection of the multiple participants in the cloud manufacturing alliance is one of current research hotspots of the cloud manufacturing mode. Based on the game theory, this article elaborates the multi-participants business collaboration process and proposes the game strategy selection framework of the multiple participants in the cloud manufacturing alliance. From the perspectives of the manufacturing resource demander (MRD), the manufacturing resource provider (MRP), and the CPO, the game types are analyzed, the benefit functions are established, the existences of game equilibria are proved, and their corresponding constraint conditions are obtained. Integrating the dominant game strategies of the multiple participants, the dominant combination strategies of the above three game equilibria are proposed and the intersection conditions of Nash equilibrium from the mixed perspective are obtained. A set of experimental data from the practical case is given to prove that the solution space of Nash equilibrium from the mixed perspective is not empty. This research provides the theoretical basis for the landing application of the cloud manufacturing mode and the technical support for the development of the cloud manufacturing service platform. It has the important academic value and the broad application prospects.

Interrelationship of Food Wastage and Sustainable Development: A Review

This paper aims to examine the interrelationship of food consumption and designing a sustainable community. Japan has achieved its economic vestige through healthy economic development and technological opportunity, resource utilization, and the well-being of the community and citizens. Related to creating a sustainable community, it requires a coordinated joined approach involving a wide range of resources and stakeholders. To attain zero food waste community, resource mobilization is needed that promotes sustainable food consumption. Resource mobilization is the process of getting resources from resource providers, using different mechanisms, to implement the organization's work for achieving the pre-determined organizational goals. Technology is much needed to come up with efficient mechanization and technologies in preventing, reducing, and reutilizing food wastes. During the design process, it is essential to understand that having the same level of understanding should be established, in terms of common current issues.

ECMS: An Edge Intelligent Energy Efficient Model in Mobile Edge Computing

With the increasing popularity of mobile edge computing (MEC) for processing intensive and delay sensitive IoT applications, the problem of high energy consumption of MEC has become a significant concern. Energy consumption prediction and monitoring of edge servers are crucial for reducing MEC’s carbon footprint in accordance with green computing and sustainable development. However, predicting energy consumption of edge servers is a nontrivial problem due to the fluctuation and variation of different loads. To address this problem, we propose ECMS, a new edge intelligent energy modeling approach that jointly adopts Elman Neural Network (ENN) and feature selection to optimize the consumption of energy on edge servers. ECMS considers 29 parameters relevant to edge server energy consumption and uses the ENN to develop an energy consumption model. Unlike other energy consumption models, ECMS can successfully deal with load fluctuation and various sorts of tasks, such as CPU-intensive, online transaction-intensive, and I/O-intensive. We have validated ECMS through extensive experiments and compared its performance in terms of accuracy and training time to several baseline approaches. The experimental results show the superiority of ECMS to the baseline models. We believe that the proposed model can be used by the MEC resource providers to forecast and optimize energy use.