Literature Review on the Impact of Blockchain Technology on Resource Allocation Efficiency

With the rapid development of Internet technology,the importance of blockchain technology has become increasingly prominent.Faced with this situation,extensive research has been carried out at home and abroad.Through the analysis of relevant literature on blockchain in recent years,it is found that there are many research results of blockchain technology in medical care,finance,education,etc.,but its application in the field of resource allocation efficiency is rare.From the existing studies on the influencing factors of resource allocation efficiency in China,it is found that there are significant differences in resource allocation efficiency between China and some developed countries or between various provinces and cities of China.

Energy Efficient Resource Allocation in Timesharing Multiuser Systems with Hybrid Energy Harvesting Transmitter

An energy effi cient resource allocation scheme in timesharing multiuser system with a hybrid energy harvesting transmitter is studied in this paper. Specially, the operation energy of system is supplied by constant energy and energy harvesting, which harvests energy from external environment. Our goal is to maximize the energy effi ciency of timesharing multiuser systems by considering jointly allocation of transmission time and power control in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Then, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy efficient resource allocation scheme has a better performance than the scheme which decomposes optimization problem into two parts(power allocation, time allocation) to solve iteratively.

Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing

In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.

Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system resources.It is also referred to as a system that will let the consumers utilize computational resources like databases,servers,storage,and intelligence over the Internet.In a cloud network,load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency.It is also known as a server pool or server farm.When a single node is overwhelmed,balancing the workload is needed to manage unpredictable workflows.The load balancer sends the load to another free node in this case.We focus on the Balancing of workflows with the proposed approach,and we present a novel method to balance the load that manages the dynamic scheduling process.One of the preexisting load balancing techniques is considered,however it is somewhat modified to fit the scenario at hand.Depending on the experimentation’s findings,it is concluded that this suggested approach improves load balancing consistency,response time,and throughput by 6%.

Can the low-carbon city pilot policy promote the upgrading of high-carbon emitting enterprises? Evidence from China

As a crucial environmental reform system to realize“carbon peaking”and“carbon neutrality”,the pilot policy of low-carbon cities(LCCs)puts pressure and challenges on high-carbon emitting enterprises(HCEEs)while providing opportunities for these firms to take the path of independent transformation.Employing the data of Chinese listed enterprises from 2006 to 2016 and adopting a difference-in-differences(DID)model,we evaluated the impact of LCC construction on the upgrading of HCEEs and its mechanisms.The results indicate that LCC construction enhances the upgrading of HCEEs in the pilot cities.The conclusions remain stable after a series of robustness tests.The mechanism analysis reveals that LCC construction triggers the upgrading of HCEEs by promoting resource allocation efficiency,R&D investment,and green technology innovation.The heterogeneity results indicate that this positive effect is more pronounced for HCEEs in regions with more stringent environmental law enforcement.This study also observes that the upgrading impact is more promi‐nent for state-owned enterprises,enterprises with higher bargaining power,and enterprises whose managers have a long-term vision.The above results provide directions for upgrading HCEEs and replicable evidence for cities in developing economies to fulfill the win-win target of environmental protection and economic transfor‐mation.

The Core Driver of China＇s Economic Growth： An Analysis Based on Cross- Region Spillover Effects of Factors

China＇s recent economic slowdown has provoked academic discussion on what the core driver should be to ensure sustainable and healthy economic growth. To answer this question, it is essential to analyze the resources allocation efficiency. Using the newly-developed spatial panel data model, this paper studies not only the direct efject of resources allocation on local economies, but also the spillover effects on the economies in other regions. We are then able to assess the actual effects of resource factors on China＇s economic growth, including labor force, fixed-asset investment （FAI） and technical progress. The conclusions are.＂ 1） during the past 13 years, the labor force has had an insignificant effect on all the three industries; 2） FAI has produced a prominent positive direct effect on secondary industry, but accompanied with even severer negative spillover effects which outweigh the positive ones; however, FAI has had significant direct and total effect on the tertiary industry,＂ 3） technical progress has significant effects on all the three industries. Therefore, the labor force is not the core driver of China＇s economic growth, and the demographic dividend is an invalid explanation for China＇s economic growth. Instead, fixed-asset investment remains the powerhouse of China＇s economic growth, not in the secondary industry but in the tertiary industry. All in all, technical progress is the core driver for healthy economic growth as well as the inevitable path to industrial upgrading in China.

Performance evaluation of a WDM/OCDM based hybrid optical switch utilizing efficient resource allocation

A hybrid optical switch （HOS） with physical layer of wavelength division multiplexing and optical code division multiplexing （WDM/OCDM） scheme is proposed. An additional feature to the HOS than optical cross connect （OXC） is that the controller can process requests for both circuit establishment and burst scheduling. In our study, the measurement criteria of HOS are the blocking probability, probability of error, and probability of outage. To simplify the analysis, no distinction is made between a circuit in progress and a burst in progress. Moreover, a minimum fit （MinF） resource allocation strategy is applied in order to increase the bandwidth efficiency and control the multiplexing interference of the OCDM. A 2D Markov model for the HOS is presented using the MinF strategy. Numerical results reveal that the code parameters and the resource allocation strategy greatly affect the performance. Certain periority can be achieved by assigning shorter codes to high periority users and longer codes to low periority users. Also, the probability of error and outage are reduced bv aonling the MinF strategy.