Energy efficient resource allocation based on virtual network embedding for IoT data generation

An expansion of services and unprecedented traffic growth is anticipated in future networks, aligned with the adoption of the long-awaited Fifth Generation (5G) of mobile communications. To support this demand, without exposing mobile operators to the pressure of CAPEX and OPEX, 5G uses new frequency bands, and adopts promising trends, including: densification, softwarization, and autonomous management. While the first technology is proposed to handle the traffic growth requirements, the softwarization and autonomous management are expected to play, in synergy, to ensure the desired trade-off between reducing the CAPEX and OPEX, while guaranteeing the quality of service (QoS). Softwarization is expected to transform the network design, from one size fits all, to more demand oriented adaptive resource allocation. In this work, we focus on this point, by discussing how these technologies act in synergy towards enabling RAN sharing. Particularly, we focus on how they fit into the issue of energy efficient Multi-Operator Resource Allocation (MO-RA). After a survey and classification of schemes leveraging this synergy for distinct resource allocation (RA) objectives, we present a detailed survey and qualitative classification of RA schemes with respect to energy efficiency. This work presents an innovative survey, since it concentrates on multiple operators, and the enabling of Mobile Virtual Network Operators (MVNOs), which will come into play with the complete virtualization of mobile networks. Based on the deep literature analysis of the different operations that can bring energy savings to MO-RA, we conclude the work with listing open challenges and future research directions.

Long‐Term Evolution–unlicensed (LTE‐U) has recently attracted worldwide interest to meet the explosion in cellular traffic data. By using carrier aggregation, licensed and unlicensed bands are integrated to enhance transmission capacity while maintaining reliable and predictable performance. As there may exist other conventional unlicensed band users, such as WiFi users, LTE‐U users have to share the same unlicensed bands with them. Thus, an optimized resource allocation scheme to ensure the fairness between LTE‐U users and conventional unlicensed band users is critical for the deployment of LTE‐U networks. In this paper, we investigate an energy efficient resource allocation problem in LTE‐U coexisting with other wireless networks, which aims at guaranteeing fairness among the users of different radio access networks. We formulate the problem as a multiobjective optimization problem and propose a semidistributed matching framework with a partial information‐based algorithm to solve it. We demonstrate our contributions with simulations in which various network densities and traffic load levels are considered.

In the face of increasingly growing health demands and the impact of various public health emergencies, it is of great significance to study the regional differences in the allocation efficiency of the rural public health resources and its improvement mechanism. In this paper, the game competition relationship is included in the evaluation model, and the game cross-efficiency model is used to measure the allocation efficiency of the rural public health resources in 31 provinces of China from 2008 to 2017. Then, the Theil index model and the Gini index model are applied in exploring the regional differences in the allocation efficiency of rural public health resources and its sources. Finally, the bootstrap truncated regression model is used to analyze the influencing factors of the allocation efficiency of the rural public health resources in China. The results show that, first, the total allocation efficiency level of the rural public health resources in China from 2008 to 2017 is relatively low, and it presents a U-shaped trend, first falling and then rising. Second, the changing trend of the allocation efficiency of the rural public health resources in the eastern, central, and western regions of China is similar to that in the nationwide region, and it shows a gradient trend that “the allocation efficiency in the eastern region is high, the allocation efficiency in the western region is low, and the allocation efficiency in the Central region is at the medium level”. However, the gap among the three regions is continually narrowing. Third, the calculation results of the Theil index and the Gini index show that intra-regional differences are the major source of the regional differences in the allocation efficiency of the rural public health resources in China, and the inter-regional differences demonstrate an expansion trend. Finally, the improvement of the education level and the social support level will generally improve the allocation efficiency of the rural public health resources in China and its three regions. The increased governmental financial support and urbanization level will reduce the allocation efficiency of the rural public health resources in China and its three regions. The economic development level, the living conditions and the population density are the important influencing factors of the allocation efficiency differences of the rural public health resources in the three regions. Therefore, on the basis of ensuring the increase of the total supply of the rural public health resources, more attention should be paid to the improvement of the allocation efficiency. Moreover, on the basis of continually narrowing the inter-regional differences among the eastern, central, and western regions, more attention should be paid to the intra-regional differences of the allocation efficiency of the rural public health resources among the different provinces. The various economic and social policies should be constantly optimized to jointly improve the allocation efficiency of the rural public health resources.

Cloud computing is one among the emerging platforms in business, IT enterprise and mobile computing applications. Resources like Software, CPU, Memory and I/O devices etc. are utilized and charged as per the usage, instead of buying it. A Proper and efficient resource allocation in this dynamic cloud environment becomes the challenging task due to drastic increment in cloud usage. Various promising technologies have been developed to improve the efficiency of resource allocation process. But still there is some incompetency in terms of task scheduling and power consumption, when the system gets overloaded. So an energy efficient task scheduling algorithm is required to improve the efficiency of resource allocation process. In this paper an improved task scheduling and an optimal power minimization approach is proposed for efficient dynamic resource allocation process. Using prediction mechanism and dynamic resource table updating algorithm, efficiency of resource allocation in terms of task completion and response time is achieved. This framework brings an efficient result in terms of power reduction since it reduces the power consumption in data centers. The proposed approach gives accurate values for updating resource table. An efficient resource allocation is achieved by an improved task scheduling technique and reduced power consumption approach. The Simulation result gives 8% better results when comparing to other existing methods.

BackgroundWith the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation.MethodsThe data used in this study were derived from the “China Statistical Yearbook” and the “China Civil Affairs Statistical Yearbook” for the period of 2010–2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020.ResultsThe equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation.ConclusionWith the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

Multi-objective optimization oriented policy for performance and energy efficient resource allocation in Cloud environment

ABSTRACTIn this article, we analyzed the impact mechanism of Internet finance on the efficiency of regional financial resource allocation. A data envelopment analysis–Malmquist model is used to measure the efficiency of financial resource allocation in 30 provinces in China, and the impact of Internet finance on the efficiency of regional financial resource allocation is tested using a spatial Durbin model. The results show clear spatial agglomeration and spillover effects in the efficiency of regional financial resource allocation. In addition, developing Internet finance can promote the efficiency and technological progress of regional financial resource allocation and can enhance efficiency and technological progress in the allocation of financial resources in adjacent regions. However, it can hurt the technical efficiency of regional financial resource allocation.

Increasing the efficiency of resource allocation is the basis and guarantee for boosting high-quality economic development. Based on the panel data of Chinese industrial enterprises and cities from 2008 to 2013, this paper studies the influence of infrastructure construction demand shocks represented by local government debt expansion on the efficiency of sectoral resource allocation from the perspective of sectoral linkage. According to the empirical findings, local government debt significantly reduces the resource allocation efficiency of manufacturing sector that is highly related to infrastructure construction. This conclusion is still tenable after the robustness test using the simulated local government debt as an instrumental variable. Further mechanism tests show that there are two reasons for the decline of the efficiency of resource allocation in manufacturing sector that is highly related to infrastructure construction. First, more product demands and investments brought by the expansion of local government debt flow to less productive enterprises in the sector. Second, resource misallocation reduces the probability of high-productivity enterprises entering the market and low-productivity enterprises exiting the market, and the effect is more prominent in cities with high dependence on state-owned enterprises and high pressure on officials to be promoted. According to this study, the performance management of local government debt should be further strengthened, and particular attention should be paid to the influence of local government debt on enterprise investment and financing crowding out and resource misallocation.

In 5G mobile technology, the expansion of Internet of Things (IoT) has created a huge need for a wide variety of latency, dependability, and energy efficiency requirements, etc… Spectrum efficiency (SE) of such large scale network needs to be improved with an economical power consumption. The non-orthogonal multiple access (NOMA) technique is utilized to enhance system efficiency (SE) by merging several users in the same frequency. An energy efficient (EE) resource allocation (RA) problem has been formulated for NOMA based heterogeneous IoT networks. Using the examining technique of Cognitive Radio (CR) Network, a stepwise RA scheme is assigned for IoT Users (IoTUs) and Mobile Users (MUs) with the mutual interference management. Later, to find a solution quickly and flawlessly, a deep recurrent neural network (RNN) based mechanism has been proposed. Furthermore, to systemize the approach of heterogeneous users, a rate and precedence demands based scheduling method has been implemented. Extensive results demonstrate that the deep learning based framework performs better than traditional RA methods in terms of computational complexity. On comparing with the prevailing OFDMA technique, the NOMA system with the imperfect SIC provides an acceptable performance on the EE at the cost of low EE and high power consumption.

Balancing energy efficiency and throughput fairness in IEEE 802.11 WLANs

The medical and health resources in the Yangtze River Delta region are abundant, occupying a significant position in China's medical and health system with wide service coverage. The efficient allocation of medical and health resources in this region is a key issue affecting the high-quality development of medical and health services. Existing research on the representative region of the Yangtze River Delta Urban Agglomeration remains relatively limited, with insufficient analysis of the efficiency of medical and health resource allocation in the area, as well as a lack of in-depth exploration into its influencing factors and barriers. This study employs the undesirable output super-efficiency SBM model to calculate the static super-efficiency values of medical and health resource allocation in 41 cities of the Yangtze River Delta urban agglomeration from 2015 to 2020. The Malmquist index is utilized to analyze the changes in dynamic efficiency, and the panel Tobit regression model is utilized to analyze the influencing factors of comprehensive efficiency of medical and health resource allocation in the Yangtze River Delta urban agglomeration. The study highlights that the Yangtze River Delta urban agglomeration confronts multiple systemic challenges, such as pronounced disparities in healthcare resource allocation, uneven dissemination of medical technological innovations, insufficiently effective policy implementation, severe pandemic-induced impacts, enduring gaps in urban-rural healthcare resources, and financial accessibility barriers in low-efficiency cities. By integrating empirical evidence from existing studies and performing comparative case analyses, this research puts forward actionable recommendations. These strategies are designed to improve the equity and efficiency of medical and health resource allocation within the region, while offering transferable insights for other regions facing similar institutional and operational challenges.

Network virtualization has evoked interest among researchers as a promising solution for developing flexible and manageable architectures for future Internet. One of the major challenges in network virtualization is the efficient allocation of substrate resources to the Virtual Networks (VNs) - a problem known as Virtual Network Embedding (VNE). Most of the past research on VNE has been focused on algorithms to allocate resources to VNs. The problem of reconfiguration, however, is relatively less explored. In this paper, we propose a simulated annealing algorithm for reconfiguring the VNs in order to balance the load across the substrate network, thereby reducing the peak node and link load on the substrate network. Through extensive simulations we evaluate the proposed reconfiguration algorithm and show that after reconfiguration there is a 20% reduction in maximum link load and 5% reduction in maximum node load. The average link load is reduced by 50% and the fraction of links having a load above 50% is reduced from 66% to 14%. We also show that periodic reconfiguration leads to a significant improvement in the acceptance ratio of VN requests.

Efficient allocation of achievable virtual resources to the diverse users is a key challenging issue in a controlled and collaborative cloud environment. As well, balancing the load among the resources and mapping these virtual resources to the physical machines is even bigger challenge of present distributed computing arena. Numerous approaches were introduced by different researchers including Genetic Algorithm for dealing with these challenges, but their scope was limited to certain specific performance elements. Hence, there is a need of optimizing the existing research implementations for efficient allocation of virtualized resources in cloud computing environment. Usually, in a typical distributed computing environment like cloud computing, allocation of virtual resource and balancing of workload among them is realized by means of virtual machines live migration. This article introduces an optimization of existing Genetic algorithm (GA) that mainly intended for VM resource provisioning and load balancing. The proposed OGA_EAVRC considers Population size, Fitness function, Mutation probability, and success rate of resource for optimizing the performance through efficient resource allocation. Key objective of this work is to utilize each physical resource effectively and allocated them to end users efficiently. For studying the operational performance of OGA_EAVRC, an event based CloudSim was chosen. Simulation results states that the proposed OGA_EAVRC can efficiently allocates the workload among virtualized resource by reducing VM's migration among the physical machines.

Digital consumption, driven by the widespread application of information technology, has led to more efficient resource allocation and industrial structure optimization. This promotes green transformation and has a positive impact on carbon productivity. This research examined 275 cities across China, employing a difference-in-differences approach alongside the national information consumption pilot policy to carry out a quasi-natural experiment. The study found that the information consumption pilot policy enhances carbon productivity at the 1% significance level. After controlling for other variables, the regions affected by the information consumption policy saw an increase in carbon productivity that was 0.233 higher than in the regions that were not affected. This growth reflects the positive impact of the information consumption pilot policy or measures on carbon productivity. Meanwhile, the increase in technological resources and the transformation of the industrial framework encouraged by the policy indirectly promote the development of carbon productivity. The information consumption pilot policy promotes technological innovation and increases resource density, leading to more efficient technology application and resource allocation. It also drives industrial structure optimization, particularly accelerating the development of low-carbon industries, thereby effectively enhancing carbon productivity. This study provides theoretical and empirical references for the promotion of carbon productivity through digital consumption.

Aiming at the virtual network embedding problem under dynamic service request, Service Request Aware-based Dynamic Virtual Network Embedding (SRAD) algorithm is proposed. We first present virtual network embedding model, and then define virtual network construction cost according to the dynamic characteristic of service request. Our goal is to find the optimal reconfiguration policies by awaring service request type and changing trends, which can minimize the overall construction cost using substrate resource. Experimental results show that the proposed algorithm satisfies the service request, achieves higher success ratio and gains higher revenue/cost ratio for substrate network comparing with the existing algorithms.