# 5G Edge Network of Collaborative Computing Task-Scheduling Algorithm with Cloud Edge

Authors: Weixin Sui; Yimin Zhou; Sizheng Zhu; Ye Xu; Shanshan Wang; Dan Wang
Journal: Mobile Information Systems
 (2022)

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## Abstract

In the new era, the arrival of 5G has added a lot of fun and beauty to our lives, allowing us to enjoy the happiness brought by the network even more. The 5th Generation mobile technology (5G for short) is a new generation of broadband mobile communication technology with features such as higher speed, lower latency, and massive connectivity. Moreover, this is a network infrastructure that, in fact, realizes the interconnections among humans, computer machines, and sensors/things, i.e., Internet of things. The world can now be characterized as a whole global village. The 5 G, mobile edge computing networks, and cloud-edge collaborative computing allow us to communicate and share information on the cloud networks, allowing us to better understand the global village. Based on cloud-edge collaborative computing for 5G edge networks, this study builds a task scheduling algorithm, which will help us to check network defects and make better use of the 5G technology to serve customers. Experimental results demonstrate the extra efficiency of the proposed algorithm over the closest rivals.


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## Body

## 1. Introduction

Entering a new era, the emergence and use of the 5G communication technology have brought us convenience in all aspects. Moreover, this allows us to enjoy the various network conveniences brought by the 5G, especially the network progress brought about by the combination of 5G and mobile edge computing. Such a combination has enabled us to see the progress of the country and development. The 5G is a communication technology further developed on the basis of 2G, 3G, and 4G. The International Telecommunication Union (ITU) has specified that there are three key 5G application scenarios. First application scenario is improved mobile broadband (eMBB). Second application scenario is ultra-high reliability and low-latency communication (uRLLC), and finally, the third scenario is Massive Machine-Type Communication (MMTC) (mMTC). In 5 G, the Enhanced Mobile Broadband (eMBB) is utilized to sort the issues faced while handling the increasingly mobile Internet traffic. For this purpose, customers are offered with a more extreme application experience. In 5 G, uRLLC, on the contrary, is mostly used for industrial control applications, telemedicine applications, and autonomous driving applications. The use of uRLLC ensures to meet the application needs of vertical industries with extremely high dependability and reliability requirements [1]. Moreover, in 5G, Massive Machine-Type Communication (mMTC) is primarily geared at sensing and data acquisition applications including smart cities, smart homes, and environmental monitoring.As a new type of mobile communication network, 5G must not only address people-to-people communication issues and give users with more immersive and extreme business experiences such as augmented reality, virtual reality, and ultra-high-definition (3D) video but also address people-to-things issues. Furthermore, this addresses the issue of communication between things/people and things/sensors, as well as the requirements of new Internet of Things (IoTs) applications such mobile medical care, Internet of Vehicles (IoVs), smart homes, industrial control, and environmental monitoring. 5G will eventually cover different industries and fields of the economy and society and will soon become a major new infrastructure enabling the economy and society's digital, networked, and intelligent transformation [2]. Faced with the network's necessities in today's society, every country in the globe has committed a significant amount of labor and material resources in the network. After all, we live in an Internet era, and the Internet is now inextricably linked to our daily lives. The importance of the Internet has never been underestimated by anyone. Internet businesses, in particular, are truly heading down the Internet era's path. The importance of 5G communication technology in the face of today's established Internet of Things (IoTs) and networks cannot be overstated.The major goal of this study is to design and propose a task scheduling algorithm based on the 5G edge network and cloud-edge coordinated computing, as well as undertake research to make the 5G era capable of bringing us a better life [3]. Our experimental results show that the suggested scheduling method is superior when acceptable assumptions and assessment measures are used.In this study, based on cloud-edge collaborative computing for 5G edge networks, we build a task scheduling algorithm, which will help us to check network defects and make better use of 5G to serve us. The scheduling algorithm can be implemented in an integrated platform of the IoT, cloud, and MEC. The major contributions of the research conducted in this study are as follows.(i)
We propose a scheduling framework for the MEC-Cloud collaboration(ii)
A four-layer system architecture is proposed for the edge-cloud-network(iii)
A task-scheduling algorithm is suggested which helps in checking network defects and make better use of the 5G technology.The rest of the study is organized as follows. In Section2, we discuss the 5G communication technology in details. Moreover, key enabling technologies and the applications of the mobile edge computing platform are briefly discussed. The construction and design of the cloud-edge collaborative computing using a task scheduling algorithm based on the 5G edge network are proposed in Section 3. Experimental results and analysis are depicted using Section 4. Finally, Section 5 concludes this study along with several directions for future research.


## 2. The 5G Communication Technology

The advantages of 5G communication technology are reflected in our lives. 5G mobile communication is based on the 5G network era. The so-called 5G refers to the fifth-generation mobile phone mobile communication standard, which mainly brings us the fifth-generation mobile communication. My country started 5G technology research and development in January 2016; the 5G frequency band was officially designated in November 2017; in 2018, the three major operators confirmed 5G precommercial use in 2019 and 5G commercial use in 2020. 5G mobile phones were launched in China in August 2019. Huawei's advantages in applying 5G networks all demonstrate our country's support and emphasis on 5G communication technology. The key technology of 5G has certain advantages because its communication system has more powerful functions; especially when compared with previous generations of communication technologies, it will be found that the transmission efficiency of 5G communication technology has been significantly improved, and the delay in addition the 5G capacity has also been increased to a certain extent [1,4].The first advantage is that the experience rate is high. It is a consensus in the industry that the ship speed rate of 5G communication technology has been significantly improved, in which the transmission rate per second can reach the rate of 1G, thereby improving the user experience. Especially, in the real network environment, a good increase in the transmission rate can give users a better sense of experience. The second advantage is the high connection density. Another advantage of 5G communication technology is that it can maximize the number of online devices. Traditional communication technology cannot ensure that too many devices per unit area are online, but 5G technology solves this problem and can achieve more than 100 devices per square kilometer. Online devices are online at the same time. The third advantage is that the latency is relatively low. In the traditional communication technology, the delay problem has always been the main problem restricting the transmission [5, 6]. A short delay can ensure good communication of the communication content and avoid transmission accidents. 5G technology minimizes the latency to 1 millisecond, thus achieving lower latency.The fourth advantage is better mobility. In the traditional communication technology, a certain amount of signal loss will occur during the moving process, which affects the transmission quality. However, 5G technology can also stabilize the signals of both the sender and the receiver during the movement, so it can better realize the transmission of information on the move. And the moving speed of the sender and receiver can reach up to 500 km/h. Mobility of the users will also be supported by the 5G technology that will help to migrate running services.


### 2.1. Key Enabling Technologies for 5G Mobile Communication

#### 2.1.1. A High-Frequency Transmission Technology

At present, the spectrum resources of mobile communication technology have become very crowded. The reason for such a situation is mainly due to the influence of too many frequency bands, and most of them are concentrated in 3 GHz, but there are many resources available in the high-frequency band. This part of the resources can effectively alleviate the shortage of resources, and the data can be transmitted faster [2, 7]. Therefore, this technology is critical to the 5G mobile communication technology.


#### 2.1.2. Direct Communication Technology

Direct connection between different devices can be transformed from a dream to a reality with the application of 5G mobile communication technologies. As a result, it will be able to reduce device energy consumption and service delays, improve the role of spectrum resources, and dramatically improve the efficiency and quality of 5G communication. On the one hand, the use of direct communication technology can boost system capacity, while on the other hand, it can expand network coverage [3, 8]. However, there are also many shortcomings related to this technology. For example, the energy efficiency is where direct communication technology needs to improve.


#### 2.1.3. Device-to-Device (D2D) Technology

D2D (Device-to-Device) communication is a relatively recent technology. The system is in charge of it, and each terminal can connect with one another directly by repurposing cell resources. Improving the spectral efficiency of the cellular communication system while lowering the terminal's transmission power is tremendously useful. Inadequate spectrum resources in the communication system are a concern. Because direct communication is performed when the distance is short and the channel quality is high, D2D supports a more flexible connection method and network architecture, which promotes a significant improvement in link flexibility and network reliability [3]. At present, D2D is mainly broadcast, multicast, and unicast technology solutions. In the future, enhancement technologies including D2D relay technology, multiantenna technology, and joint coding technology will be vigorously developed.


#### 2.1.4. New Network Architecture Technologies

At this stage, the LTE access network mainly uses a flat network architecture, which reduces the system delay and maximizes the control of maintenance and network construction costs. In today's era, when people are constantly requesting network changes, new network architecture technologies in 5G mobile communications have been formed, which in turn satisfies the business needs that may arise in the future [9]. Among them, the low-cost high-speed optical transmission network is used, and the wireless tie signal is transmitted between centralized remote antennas and central nodes, which can cover more than 100 base station service areas and a coverage area of more than 100 km2.


#### 2.1.5. Multicarrier Technology Based on Filter Bank

In the 5G system, the multicarrier technology based on the filter bank is a crucial content, which can efficiently deal with the phenomenon of multipath fading in the 5G system and spectral efficiency [4]. Among them, FBMC is one of the indispensable methods in the multicarrier scheme of the 5G system, and it is also indispensable for the efficient utilization of the 5G system.


#### 2.1.6. Massive MIMO Technologies

At this stage, multiantenna technology has played an important role in promoting the transmission rate and spectral efficiency of the communication systems. Furthermore, it has been widely used in many wireless communication systems. This should be noted that MIMO has the characteristics of large scale networks. At this time, the base station needs to be equipped with a large number of antennas, and these antennas are centrally configured on one base station [10]. As such, the use of massive MIMO technology has broadened, and with the help of existing information, it is possible to grasp the close relationship between the number of antennas and the magnitude of spectral efficiency.


### 2.2. Applications of Mobile Edge Computing

The mobile edge computing (MEC) is a brand-new distributed computing approach based on mobile communication networks. Certain network services and network functions are segregated from the core network and realised through the cloud service environment created on the radio access network (RAN) side, for example, cost savings, lower latency and round-trip times, optimized traffic, enhanced physical security, and cache efficiency.In fact, the MEC is ubiquitous in our lives; we just do not notice it. MEC has certain computing power and can provide low-latency services and support mobility [5, 6]. And, MEC can continuously manage and control the information in end users [7]. In terms of server distribution, MEC servers are mainly deployed in base stations near the network edge of terminal equipment. More and more emerging mobile applications will benefit from MEC by offloading tasks from end devices to edge servers for execution [8]. In addition, the MEC supports 3G, 4G, and 5G, wired network, and WiFi wireless scenarios, and its main applications include (i) computing offloading, (ii) content caching, (iii) service content optimization, and (iv) collaborative computing [9,10]. In the meanwhile, the MEC can benefit industrial, entertainment, personal computing, and other applications that require processing and storage [10, 11]. Figure 1 depicts the MEC framework's eight most common application scenarios.Figure 1
Eight application scenarios of the MEC.


## 2.1. Key Enabling Technologies for 5G Mobile Communication

### 2.1.1. A High-Frequency Transmission Technology

At present, the spectrum resources of mobile communication technology have become very crowded. The reason for such a situation is mainly due to the influence of too many frequency bands, and most of them are concentrated in 3 GHz, but there are many resources available in the high-frequency band. This part of the resources can effectively alleviate the shortage of resources, and the data can be transmitted faster [2, 7]. Therefore, this technology is critical to the 5G mobile communication technology.


### 2.1.2. Direct Communication Technology

Direct connection between different devices can be transformed from a dream to a reality with the application of 5G mobile communication technologies. As a result, it will be able to reduce device energy consumption and service delays, improve the role of spectrum resources, and dramatically improve the efficiency and quality of 5G communication. On the one hand, the use of direct communication technology can boost system capacity, while on the other hand, it can expand network coverage [3, 8]. However, there are also many shortcomings related to this technology. For example, the energy efficiency is where direct communication technology needs to improve.


### 2.1.3. Device-to-Device (D2D) Technology

D2D (Device-to-Device) communication is a relatively recent technology. The system is in charge of it, and each terminal can connect with one another directly by repurposing cell resources. Improving the spectral efficiency of the cellular communication system while lowering the terminal's transmission power is tremendously useful. Inadequate spectrum resources in the communication system are a concern. Because direct communication is performed when the distance is short and the channel quality is high, D2D supports a more flexible connection method and network architecture, which promotes a significant improvement in link flexibility and network reliability [3]. At present, D2D is mainly broadcast, multicast, and unicast technology solutions. In the future, enhancement technologies including D2D relay technology, multiantenna technology, and joint coding technology will be vigorously developed.


### 2.1.4. New Network Architecture Technologies

At this stage, the LTE access network mainly uses a flat network architecture, which reduces the system delay and maximizes the control of maintenance and network construction costs. In today's era, when people are constantly requesting network changes, new network architecture technologies in 5G mobile communications have been formed, which in turn satisfies the business needs that may arise in the future [9]. Among them, the low-cost high-speed optical transmission network is used, and the wireless tie signal is transmitted between centralized remote antennas and central nodes, which can cover more than 100 base station service areas and a coverage area of more than 100 km2.


### 2.1.5. Multicarrier Technology Based on Filter Bank

In the 5G system, the multicarrier technology based on the filter bank is a crucial content, which can efficiently deal with the phenomenon of multipath fading in the 5G system and spectral efficiency [4]. Among them, FBMC is one of the indispensable methods in the multicarrier scheme of the 5G system, and it is also indispensable for the efficient utilization of the 5G system.


### 2.1.6. Massive MIMO Technologies

At this stage, multiantenna technology has played an important role in promoting the transmission rate and spectral efficiency of the communication systems. Furthermore, it has been widely used in many wireless communication systems. This should be noted that MIMO has the characteristics of large scale networks. At this time, the base station needs to be equipped with a large number of antennas, and these antennas are centrally configured on one base station [10]. As such, the use of massive MIMO technology has broadened, and with the help of existing information, it is possible to grasp the close relationship between the number of antennas and the magnitude of spectral efficiency.


## 2.1.1. A High-Frequency Transmission Technology

At present, the spectrum resources of mobile communication technology have become very crowded. The reason for such a situation is mainly due to the influence of too many frequency bands, and most of them are concentrated in 3 GHz, but there are many resources available in the high-frequency band. This part of the resources can effectively alleviate the shortage of resources, and the data can be transmitted faster [2, 7]. Therefore, this technology is critical to the 5G mobile communication technology.


## 2.1.2. Direct Communication Technology

Direct connection between different devices can be transformed from a dream to a reality with the application of 5G mobile communication technologies. As a result, it will be able to reduce device energy consumption and service delays, improve the role of spectrum resources, and dramatically improve the efficiency and quality of 5G communication. On the one hand, the use of direct communication technology can boost system capacity, while on the other hand, it can expand network coverage [3, 8]. However, there are also many shortcomings related to this technology. For example, the energy efficiency is where direct communication technology needs to improve.


## 2.1.3. Device-to-Device (D2D) Technology

D2D (Device-to-Device) communication is a relatively recent technology. The system is in charge of it, and each terminal can connect with one another directly by repurposing cell resources. Improving the spectral efficiency of the cellular communication system while lowering the terminal's transmission power is tremendously useful. Inadequate spectrum resources in the communication system are a concern. Because direct communication is performed when the distance is short and the channel quality is high, D2D supports a more flexible connection method and network architecture, which promotes a significant improvement in link flexibility and network reliability [3]. At present, D2D is mainly broadcast, multicast, and unicast technology solutions. In the future, enhancement technologies including D2D relay technology, multiantenna technology, and joint coding technology will be vigorously developed.


## 2.1.4. New Network Architecture Technologies

At this stage, the LTE access network mainly uses a flat network architecture, which reduces the system delay and maximizes the control of maintenance and network construction costs. In today's era, when people are constantly requesting network changes, new network architecture technologies in 5G mobile communications have been formed, which in turn satisfies the business needs that may arise in the future [9]. Among them, the low-cost high-speed optical transmission network is used, and the wireless tie signal is transmitted between centralized remote antennas and central nodes, which can cover more than 100 base station service areas and a coverage area of more than 100 km2.


## 2.1.5. Multicarrier Technology Based on Filter Bank

In the 5G system, the multicarrier technology based on the filter bank is a crucial content, which can efficiently deal with the phenomenon of multipath fading in the 5G system and spectral efficiency [4]. Among them, FBMC is one of the indispensable methods in the multicarrier scheme of the 5G system, and it is also indispensable for the efficient utilization of the 5G system.


## 2.1.6. Massive MIMO Technologies

At this stage, multiantenna technology has played an important role in promoting the transmission rate and spectral efficiency of the communication systems. Furthermore, it has been widely used in many wireless communication systems. This should be noted that MIMO has the characteristics of large scale networks. At this time, the base station needs to be equipped with a large number of antennas, and these antennas are centrally configured on one base station [10]. As such, the use of massive MIMO technology has broadened, and with the help of existing information, it is possible to grasp the close relationship between the number of antennas and the magnitude of spectral efficiency.


## 2.2. Applications of Mobile Edge Computing

The mobile edge computing (MEC) is a brand-new distributed computing approach based on mobile communication networks. Certain network services and network functions are segregated from the core network and realised through the cloud service environment created on the radio access network (RAN) side, for example, cost savings, lower latency and round-trip times, optimized traffic, enhanced physical security, and cache efficiency.In fact, the MEC is ubiquitous in our lives; we just do not notice it. MEC has certain computing power and can provide low-latency services and support mobility [5, 6]. And, MEC can continuously manage and control the information in end users [7]. In terms of server distribution, MEC servers are mainly deployed in base stations near the network edge of terminal equipment. More and more emerging mobile applications will benefit from MEC by offloading tasks from end devices to edge servers for execution [8]. In addition, the MEC supports 3G, 4G, and 5G, wired network, and WiFi wireless scenarios, and its main applications include (i) computing offloading, (ii) content caching, (iii) service content optimization, and (iv) collaborative computing [9,10]. In the meanwhile, the MEC can benefit industrial, entertainment, personal computing, and other applications that require processing and storage [10, 11]. Figure 1 depicts the MEC framework's eight most common application scenarios.Figure 1
Eight application scenarios of the MEC.


## 3. Construction of the Cloud-Edge Collaborative Computing Task-Scheduling Algorithm Based on the 5G Edge Network

### 3.1. The Basic Framework of the MEC

From a broad perspective, MEC consists of three parts: network layer, host layer, and system layer. The Mp, Mn, and Mx interfaces are important foundations for effective interaction between different modules and are the application, management, and external objects of MEC and body-related interface type [12]. The basic framework of the proposed MEC is shown in Figure 2. From a macroperspective, different functional entities under the MEC framework are divided into three different levels, i e., (i) the mobile edge system level, (ii) the mobile edge host level, and (iii) the mobile edge network level.Figure 2
Basic architecture of the MEC.


### 3.2. Cloud-Edge Collaborative Computing Task Scheduling of Edge Computing

The model of “providing edge intelligent services near the data source and cooperating with cloud servers” is called “cloud-edge collaboration.” In the report “Nine Application Scenarios of Cloud Computing and Edge Computing Collaboration” led by the China Academy of Information and Communications Technology, there is a paragraph about “cloud-edge collaboration”: “Edge computing is an extension of the concept of cloud computing, and the two are dependent on each other and operate collaboratively. And cloud-side collaboration will become the mainstream model in the future.” It can be seen that the role of cloud-side collaboration is huge and indispensable. At the same time, edge computing and cloud-edge collaboration and 5G are inseparable from task scheduling [13]. Task scheduling is a critical component of implementing edge computing. It becomes a chaos without it. A good scheduling method can make maximum use of the device's computational and storage resources, reducing data transmission and increasing application execution performance, and improving service effects for users with limited resources [14]. As can be seen, task scheduling is equally critical and must be carefully planned and implemented.Figure3 depicts the basic task-scheduling architecture scenario for cloud-edge collaborative computing in a 5G edge network. N mutually independent jobs are distributed over M edge nodes with varying computing capabilities, and N is typically more than M. Each edge node's computational resources are vastly varied, and job N's requirements will manifest in a variety of ways. To accomplish optimal task allocation, a matching relationship between tasks and edge nodes is constructed based on the optimization aim to be attained [15]. In order to simplify the scheduling of tasks, the following assumptions are made: (i) by default, each task is independent, and there is no dependency between tasks; (ii) the requirements of each task are clearly known; (iii) there is no interruption in the execution of each task implement. The basic structure of the 5G networking is shown in Figure 4. After receiving the instruction to obtain the basic attribute parameters of the site to be tested, the intelligent terminal obtains the basic attribute parameters of the site to be tested and the test case from the server through the network [16].Figure 3
Basic task scheduling architecture for cloud-side collaborative computing in 5G edge networks.Figure 4
Basic structure of 5G networking.


## 3.1. The Basic Framework of the MEC

From a broad perspective, MEC consists of three parts: network layer, host layer, and system layer. The Mp, Mn, and Mx interfaces are important foundations for effective interaction between different modules and are the application, management, and external objects of MEC and body-related interface type [12]. The basic framework of the proposed MEC is shown in Figure 2. From a macroperspective, different functional entities under the MEC framework are divided into three different levels, i e., (i) the mobile edge system level, (ii) the mobile edge host level, and (iii) the mobile edge network level.Figure 2
Basic architecture of the MEC.


## 3.2. Cloud-Edge Collaborative Computing Task Scheduling of Edge Computing

The model of “providing edge intelligent services near the data source and cooperating with cloud servers” is called “cloud-edge collaboration.” In the report “Nine Application Scenarios of Cloud Computing and Edge Computing Collaboration” led by the China Academy of Information and Communications Technology, there is a paragraph about “cloud-edge collaboration”: “Edge computing is an extension of the concept of cloud computing, and the two are dependent on each other and operate collaboratively. And cloud-side collaboration will become the mainstream model in the future.” It can be seen that the role of cloud-side collaboration is huge and indispensable. At the same time, edge computing and cloud-edge collaboration and 5G are inseparable from task scheduling [13]. Task scheduling is a critical component of implementing edge computing. It becomes a chaos without it. A good scheduling method can make maximum use of the device's computational and storage resources, reducing data transmission and increasing application execution performance, and improving service effects for users with limited resources [14]. As can be seen, task scheduling is equally critical and must be carefully planned and implemented.Figure3 depicts the basic task-scheduling architecture scenario for cloud-edge collaborative computing in a 5G edge network. N mutually independent jobs are distributed over M edge nodes with varying computing capabilities, and N is typically more than M. Each edge node's computational resources are vastly varied, and job N's requirements will manifest in a variety of ways. To accomplish optimal task allocation, a matching relationship between tasks and edge nodes is constructed based on the optimization aim to be attained [15]. In order to simplify the scheduling of tasks, the following assumptions are made: (i) by default, each task is independent, and there is no dependency between tasks; (ii) the requirements of each task are clearly known; (iii) there is no interruption in the execution of each task implement. The basic structure of the 5G networking is shown in Figure 4. After receiving the instruction to obtain the basic attribute parameters of the site to be tested, the intelligent terminal obtains the basic attribute parameters of the site to be tested and the test case from the server through the network [16].Figure 3
Basic task scheduling architecture for cloud-side collaborative computing in 5G edge networks.Figure 4
Basic structure of 5G networking.


## 4. Experiment and Application Analysis

We all know that welding is an important production process in the equipment manufacturing industry. The quality of welding greatly affects the manufacturing cost, performance, service life, and operational safety of the product. At present, the welding quality management of manufacturing enterprises mainly relies on manual implementation, and it is impossible to comprehensively and effectively monitor, record, and trace the welding process. At the same time, in the new era, facing the difficulty of increasing the supervision of the welding process, with the development of the Internet of Things and 5G communication technology, the digital welding monitoring system can greatly improve the existing welding quality management and provide welding operators with many convenient [17, 18].In this study, the cloud-edge collaborative computing task scheduling algorithm for 5G edge network is used to effectively monitor all the processes of the welding process. In the design idea of the intelligent welding factory, the system is divided into four layers, namely, (i) acquisition layer, (ii) transmission layer, (iii) storage layer, and (iv) application layer. The system architecture of the proposed scheduling framework is shown in Figure5.Figure 5
System architecture of the proposed layered framework.The test work under the environment of an automatic welding workshop is used, and the Fronius TPS5000 MIG/MAG welding machine is used, and all welds adopt the pulse welding process. Run the monitoring software, input the necessary weld information, and real-time display and automatically record the welding condition of each weld during the test. The terminal software simulates different numbers of client programs for data transmission with the host computer via 5G and CPE and tests the packet loss rate of the algorithm system. This should be noted that the communication protocol is TCP/IP, in our simulations, and the distance between the simulated client and the server is 260–310m [19].The results show that the proposed algorithm and MEC system can ensure that the packet loss rate is 0 when 5G and CPE are used as the medium for data transmission. Moreover, this indicates that the algorithm and MEC system can well ensure the integrity of data transmission and good error-free performance, the cloud of 5G edge network. The integration of edge collaborative computing task-scheduling algorithm and welding monitoring equipment is conducive to improving the data transmission efficiency of online monitoring of the welding process, thereby improving the real-time performance of process monitoring and reducing welding costs [20]. It can be seen that the cloud-edge collaborative computing task-scheduling algorithm for 5G edge networks is valuable, and it also shows that the task scheduling under the cloud-edge collaborative computing of 5G networks combined with mobile edge computing can better serve enterprises.Experimental results in terms of delay and drop ratio for different communication technologies, i.e., CPE and 5G, are shown in Table1. The metric delay is measured in seconds and basically characterizes the service response time, i.e., when tasks are scheduled and a response is noted from the MEC server. Similarly, the drop ratio is measured in percentage and characterizes the total number of packets that were dropped due to lower communication capacity, i.e., tasks not assigned to MEC servers in our case. From the following results, we can observe that using 5G is more beneficial in all cases than using the CPE as the underground communication technology [21]. The results in terms of delay and packet drop ratio are shown in Figure 6. The other competing methods are round Robin and first fit scheduling techniques. The round Robin techniques assign tasks in a round Robin fashion while the FF technique puts tasks where it is possible. We can observe that the proposed scheduling algorithm has the lowest delay and also has the minimum dropout ratio.Table 1
Experimental results in terms of delay and drop ratio for different communication technologies, i.e., CPE and 5G.
Delay (s)Drop ratio (%)CPERR4522.09FF4132.41Proposed3941.935GRR392.781.93FF387.421.94Proposed365.681.86Figure 6
Results in terms of delay and packet drop ratio.


## 5. Conclusions and Future Work

In the new era, the characteristics of 5G's wide coverage, large connection, low cost, and low energy consumption has the demand for utilizing our network. Today, when the Internet of Things and the network are so developed, the emergence and development of 5G give us a closer understanding of the world. Moreover, it shortens the time to understand it and can provide benefits to our life and work. All walks of life are also inseparable from the network. The 5 G edge network combined with the cloud-edge collaborative computing will provide enterprises with better network advantages. With the addition of task-scheduling algorithms, enterprises can better control their own internal and external information. Experiments’ outcomes also show that there is value in use, and it can better contribute to the development of the country so that the network can better serve the society and the world.In the future, we will add additional metrics to study the validity of our scheduling approach. Similarly, prediction techniques can be integrated into the scheduling problem in order to optimize various objectives of the MEC platform such as energy consumption, response time, performance, and execution times. We will also develop approximate algorithm to solve the NP hard problem of task scheduling, where majority of the online problems are solved using heuristics [20]. Albeit, heuristics are fast enough to reach a solution but cannot provide an optimal or approximate solutions. We will also think over the implementation of the algorithm in a real MEC environment rather than in a simulation study.



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*Source: 4592790-2022-05-23.xml*