Application of the New Resource Approach to the Study of the Parameters of the Industrialization Economy

The processes of industrialization, reindustrialization and new industrialization differ not only in the content and mechanisms of implementation, but also in the set of resources required for their application. New industrialization as a process of quantitative and qualitative changes in the economy is based on a complex of resources. These resources are necessary, on the one hand, for the modernization of traditional industries, and on the other hand, for the formation of promising economic activities and industries. Keeping a balance between the resources used to achieve the goals of modernization and innovative development in order to achieve the goals of modernization and innovative development is one of the tasks of a methodological nature and requires the development of appropriate theoretical approaches and models. At the same time, the second most important task is the application of such theories and concepts that will provide a solution to the problems associated with the identification, assessment and description of the parametric characteristics and functions of resources in the system of industrial development of the domestic economy. To solve these problems, the article highlights the features of new industrialization; its differences from such phenomena as industrialization, deindustrialization and reindustrialization. It is substantiated that the use of the resource concept as a methodological basis for new industrialization will make it possible to determine the following: to draw up a typology of the resources of new industrialization; identify criteria for strategic and complementary resources of new industrialization; to identify the subjects of relations in the resource allocation system, as well as their specific functions. The article concludes that modernization processes are provided mainly by massive resources and complementary capabilities and competencies, while the processes of innovative and technological development within the framework of the new industrialization of the economy presuppose the presence of strategic, unique resources and competencies.

Web-Based DSS for Resource Allocation in Higher Education

The allocation of scarce resources is a complex higher education decision problem, especially when it comes to budget constraints. Therefore, the authors propose a multicriteria web-based decision support system for resource allocation in higher education organizations. To do so, they define an MCDA/M resource allocation model, based on a project portfolio selection problem to set the percentage of the total budget that every alternative should receive. For the web-based DSS, they develop a database model to store and retrieve data, define the user's interface, and they use a web platform to transform the prototype into a web-based system. Also, they run an empirical analysis with an end-user to test the DSS. They show that the system can provide a clear vision of how the resource allocation system works; the mechanism as a whole becomes more transparent to those involved, enabling them to make efficient and reasonable decisions.

Enhancement in resource allocation system for cloud environment using modified grey wolf technique

<p class="normal">Cloud computing is an advanced technology which provides services with the help of internet. These services work under the rule of pay and gain. The services consist of hardware and software used in different fields of life. Due to growth of cloud computing the number of users are increased and their demand for better services also increased with the passage of time. Cloud computing faces different issues. One of them is resource scheduling. In this paper a new technique is used for improvement of scheduling in cloud computing. The improvement took place in GWO algorithm. Two main sections of this algorithm are modified, which are local search section and fitness function value. The above proposed technique is used to improve three main parameters of scheduling that are energy consumption, throughput and average network executation time in VM for cloud computing. The techniques results are compared with ABC algorithm and GWO algorithm. The results show that proposed algorithm improves in the three main parameters of scheduling for cloud computing.</p>

A Hybrid Grey Wolf Optimizer and Artificial Bee Colony Algorithm Used for Improvement in Resource Allocation System for Cloud Technology

<p class="0abstract">Cloud computing is the next generation of technology which provide different service with the rule of pay and gain with the help of internet. These services consist of hardware and software used in different field of life. Due the growth of user in cloud environment the number of access and share system of technology increases which causes different issue and resource allocation system is one of them. In this paper for improvement in resource allocation system in VM a hybrid algorithm used because in some situation VM become underloaded and overloaded in cloud data centre due to lack of proper load balancing technique system. Therefore a hybrid technique used for improvement in VM allocation system. The hybrid technique consist of GWO and ABC algorithm three main section of GWO technique improve first improvment occur at local search section in this section ABC algorithm local search technique used second improvement occur at fitness function along with the energy parameter. The above proposed technique used to improve four main parameter of scheduling which are energy consumption, throughput network stability and average network executation time in resource allocation system in VM for cloud computing. The proposed technique result are compare with ABC algorithm , GWO algorithm, RAA algorithm based on those result the proposed algorithm improve 1.25 % accuracy and efficiency for resource allocation system in VM for cloud computing.</p>