Upload Bandwidth Research Articles

User And Bandwidth Management Using Mikrotik Hotspot At State Vocational School 5 Waingapu

The use of the internet in schools is very helpful for teachers, staff and students, the internet is an important need for most adult people, they even regard the internet as a basic daily need that must be met, such as at SMK Negeri 5 Waingapu. The use of the internet in schools is very helpful for teachers, staff and students. State Vocational High School 5 Waingapu uses an internet service provider (ISP) sourced from KOMINFO Bakti as internet access with a total bandwidth of 2 Mbps with an average user of 15 clients. The distance to access the internet network on WIFi is 20 meters, but there is still no good management of network usage so that when accessing the internet, many users (clients) often experience interference. One form of utilizing wireless technology is a hotspot. The development method used in this research is to develop a hotspot network at SMK Negeri 5 Waingapu using the Network Development Life Cycle (NDLC) model which is used as the overall development method in developing or designing computer network systems. By implementing bandwidth management using a hotspot router proxy at SMK Negeri 5 Waingapu and testing it using a speedtest before implementation, namely a download speed of 4.55 and an upload speed of 1.09. And after the implementation of bandwidth management for teacher user hotspots, namely for download bandwidth of 0.95 Mbps and upload bandwidth of 0.21 Mbps, then for hotspot user principals download bandwidth is 0.94 Mbps and upload bandwidth is 0.94 Mbps and hotspot user download bandwidth for students is 0.73 Mbps and upload of 0.94 Mbps.

4G LTE Network Quality and TCP/IP Performance of Telkomsel Provider in the Lolong Belanti Area

Lolong Belanti is one of the sub-districts in North Padang District, Padang City, West Sumatra Province. In Lolong Belanti cellular telecommunications is growing very rapidly and has become an important need for the community. Therefore, research needs to be done so that it can be a reference for providers to improve the quality and quantity of 4G LTE networks in Lolong Belanti. The measurement results on weekdays obtained the percentage of good to excellent 4G network categories have a percentage value of RSRP 99.04%, SINR 12.14% and Throughput 98.51% and the average value of download bandwidth 28.26 Mbps, upload bandwidth 23.92 Mbps, throughput 1,282,003 kbps, packet loss 0.103%, delay 5.92 ms and jitter 5.97%. While on holidays, the percentage of 4G network categories is good to very good having a percentage value of 97.91% RSRP, 12.28 SINR and 98.51% Throughput and has an average value of 13.68 Mbps download bandwidth, 17.94 Mbps upload bandwidth, 647.688 kbps Throughput, 0.26% packet loss, 17.428 ms dellay and 17.566 ms jitter. The quality of Telkomsel's 4G LTE network provider in Lolong Belanti Village on holidays is better than on weekdays. And the comparison of TCP/IP performance for Bandwidth Download, Bandwidth Upload, Throughput and Packet Loss is superior on weekdays compared to holidays, and for Delay and Jitter is better on holidays than on weekdays.

Lane-Level Map Generation and Management Framework Using Connected Car Data

This study proposes a lane-level map generation and management framework using connected sensor data to reduce the manpower and time required for producing and updating high-definition (HD) maps. Unlike previous studies that relied on the onboard processing capabilities of vehicles to collect map-constructing elements, this study offloads computing for map generation to the cloud, assigning vehicles solely the role of transmitting sensor data. For efficient data collection, we divide the space into a grid format to define it as a partial map and establish the state of each map and its transition conditions. Lastly, tailored to the characteristics of the road elements composing the map, we propose an automated map generation technique and method for selectively collecting data. The map generation method was tested using data collected from actual vehicles. By transmitting images with an average size of 350 KB, implementation was feasible even with the current 5G upload bandwidth. By utilizing 12,545 elements, we were able to achieve a position accuracy and regression RMSE of less than 0.25 m, obtaining 651 map elements to construct the map. We anticipate that this study will help reduce the manpower and time needed for deploying and updating HD maps.

The correlation between broadband prices and the digital divide: A survey of Taiwan’s north coast

This study highlights the importance of differentiating between urban and rural areas when exploring broadband issues that matter to consumers and statistically sampling accordingly. To test the effectiveness of rural broadband programmes in improving internet usage, this study is based on a selection of five geographically adjacent administrative districts with varying population densities.During a survey using the double-bounded dichotomous choice model to measure people’s WTP, two research hypotheses were tested and verified through regression analysis. The results showed that consumers living in rural areas are significantly less willing to pay for broadband than those living in urban areas, which contradicts the findings of the study by Worden and Hambly (2022) conducted in Canada.Additionally, the significant t value test results found in this study showed that consumers are willing to pay more for download bandwidth than for upload bandwidth for every dollar spent. This result indicates that consumers have a clear preference for one over the other and highlights significant differences in their choices.In particular, the results of the willingness-to-pay survey revealed that the incumbent operator yield opposite results in the regression coefficients for their willingness to pay for each unit of download bandwidth and upload bandwidth. This result may be due to differences in the design of internet products offered by the two operators.Given the inevitable reality that income generated by service operators in rural areas is lower than that in urban areas, there is a need to study price differentials between urban and rural areas in order to promote greater use of broadband internet in rural areas in the context of the adoption of a single price throughout the region.

VeriDedup: A Verifiable Cloud Data Deduplication Scheme With Integrity and Duplication Proof

Data deduplication is a technique to eliminate duplicate data in order to save storage space and enlarge upload bandwidth, which has been applied by cloud storage systems. However, a cloud storage provider (CSP) may tamper user data or cheat users to pay unused storage for duplicate data that are only stored once. Although previous solutions adopt message-locked encryption along with Proof of Retrievability (PoR) to check the integrity of deduplicated encrypted data, they ignore proving the correctness of duplication check during data upload and require the same file to be derived into same verification tags, which suffers from brute-force attacks and restricts users from flexibly creating their own individual verification tags. In this paper, we propose a verifiable deduplication scheme called VeriDedup to address the above problems. It can guarantee the correctness of duplication check and support flexible tag generation for integrity check over encrypted data deduplication in an integrative way. Concretely, we propose a novel Tag-flexible Deduplication-supported Integrity Check Protocol (TDICP) based on Private Information Retrieval (PIR) by introducing a novel verification tag called <inline-formula><tex-math notation="LaTeX">${note\ set}$</tex-math></inline-formula> , which allows multiple users holding the same file to generate their individual verification tags and still supports tag deduplication at the CSP. Furthermore, we make the first attempt to guarantee the correctness of data duplication check by introducing a novel User Determined Duplication Check Protocol (UDDCP) based on Private Set Intersection (PSI), which can resist a CSP from providing a fake duplication check result to users. Security analysis shows the correctness and soundness of our scheme. Simulation studies based on real data show the efficacy and efficiency of our proposed scheme and its significant advantages over prior arts.

Time-Critical Data Dissemination Under Flash Crowd Traffic

How to rapidly disseminate a large-sized file to many recipients in flash crowd arrival patterns is a fundamental challenge in many applications, such as distributing multimedia content. To tackle this challenge, we present the Bee, which is a time-critical peer-to-peer data dissemination system aiming at minimizing the maximum dissemination time for all peers to obtain the complete file in flash crowd arrival patterns. Bee is a decentralized system that organizes peers into a randomized mesh-based overlay, and each peer only works with local knowledge. We introduce the slowest peer first strategy to boost the speed of dissemination and present a topology adaptation algorithm that adapts the number of connections based on upload bandwidth capacity of a peer. Bee is designed to support network heterogeneity and deals with the flash crowd arrival pattern without sacrificing the dissemination speed. We also show the lower bound analysis of the data dissemination problem, and present the experimental results to demonstrate that the performance of Bee can roughly approximate the lower bound of the data dissemination problem under flash crowd traffic.

BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference.

Edge-cloud collaborative inference can significantly reduce the delay of a deep neural network (DNN) by dividing the network between mobile edge and cloud. However, the in-layer data size of DNN is usually larger than the original data, so the communication time to send intermediate data to the cloud will also increase end-to-end latency. To cope with these challenges, this paper proposes a novel convolutional neural network structure—BBNet—that accelerates collaborative inference from two levels: (1) through channel-pruning: reducing the number of calculations and parameters of the original network; (2) through compressing the feature map at the split point to further reduce the size of the data transmitted. In addition, This paper implemented the BBNet structure based on NVIDIA Nano and the server. Compared with the original network, BBNet’s FLOPs and parameter achieve up to 5.67× and 11.57× on the compression rate, respectively. In the best case, the feature compression layer can reach a bit-compression rate of 512×. Compared with the better bandwidth conditions, BBNet has a more obvious inference delay when the network conditions are poor. For example, when the upload bandwidth is only 20 kb/s, the end-to-end latency of BBNet is increased by 38.89× compared with the cloud-only approach.

Analisis Rekomendasi Penggunaan Provider Telekomunikasi Seluler Berdasarkan Pengukuran Bandwdith pada Masa Pandemi

This study aims to provide recommendations for the use of cellular telecommunications providers for use in online learning during a pandemic. This study used an experimental study in which the researcher collected data manually by comparing the download and upload bandwidth usage of each available cellular telecommunications provider in the Mamuju district. This research was conducted during the COVID-19 pandemic to impact the teaching and learning process, which must do online or remotely, which certainly requires good internet connectivity. This research uses quantitative methods and comparative analysis by collecting data download bandwidth and upload bandwidth using NetLimiter from three cellular telecommunications providers, namely Telkomsel, XL, and Indosat in Mamuju district. Then the data is processed by calculating the bandwidth. The results of data analysis obtained are Telkomsel with a download bandwidth of 0.0136 MBps, upload 0.0147 MBps, XL download bandwidth 0.0116 MBps, upload 0.0129 MBps, Indosat download bandwidth 0.0066 MBps, upload 0.0162 MBps. The results of this study show that among the three providers, Telkomsel is superior in the use of download bandwidth with a size of 0.0136 MBps. In contrast, for upload bandwidth usage, it is recommended to use Indosat with a size of 0.0162 MBps. Still, an overall analysis of the provider, Telkomsel is a recommended provider for using video conferencing applications due to gaps Between the download bandwidth usage with a size of 0.0136 MBps and upload with a size of 0.0147 MBps is not too significant and more stable than other providers. Suggestions for further research are re-measurement by looking at the distribution factor or the number of BTS in the area

RETRACTED: Research on the strategy of mobile short video in product sales based on 5G network and embedded system

Mobile short video-based product sales sharing sites like YouTube and Tudor have many established user content for creating and distributing shares. The increasing number of mobile devices for product sales leads to the upcoming new 5G technology roadmap for embedded systems and 5G network connectivity. As these are the main sources of 5G information and online activities for consumers, mobile phone short films are rapidly being replaced by embedded systems. As the demand for more embedded system devices and applications continues to grow, supported bandwidth is also essential to meet this growing connection demand. The existing system does not allocate the product sales data upload bandwidth size. The system proposed here focuses on user upload bandwidth allocation, one of the basic resources of a short video sharing system with product details. Its allocation upload bandwidth Recurrent Neural Network (RNN) algorithm is proposed in a centralized or decentralized way and evaluated for balancing widely used strategies (equal allocation) and a mobile short video. Embedded systems are responsible for running professional product sales and control applications consistently and predictably. Development while using the microprocessor is also important. It increases the need to process product sales to handle the bandwidth, latency requirements, product sales data and data generated from multiple connected devices. It's a big challenge for the industry to data and data capabilities.

A Pose Estimation-Based Fall Detection Methodology Using Artificial Intelligence Edge Computing

As the population worldwide continues to age and the percentage of elderly people continues to increase, falls have been become the second leading cause of death from accidental or unintentional injuries. Although many imaging sensing devices have been used to detect falls for elderly people, most involve using the Internet to transfer images taken by a camera to a large back-end server, which performs the necessary calculations; however, algorithm limitations and computational complexity may cause bottlenecks in image outflow, and the image transfer can result in privacy problems. To address these problems, in this paper, an artificial intelligence (AI) fall detection method is proposed that operates using an edge computing architecture, called the pose estimation-based fall detection methodology (PEFDM), which is based on a human body posture recognition technique. The proposed PEFDM can effectively reduce the computational load, runs smoothly on mainstream edge computing systems and possesses artificial intelligence computing capabilities. By using edge computing, the privacy and upload bandwidth issues caused by image outflow can be eliminated. Experiments with real humans show that the PEFDM can detect falls for elderly people with a recognition accuracy of up to 98.1%.

ERRANT: Realistic emulation of radio access networks

Mobile devices drastically changed how people use the Internet. We use smartphones to access a heterogeneous catalog of web services such as news, social networks, audio/video streaming. Differently from wired connections, mobile networks do not offer the same kind of performance stability yet. Thus, service providers have to handle different network scenarios, e.g., 3G or 4G, while promising good end-users’ quality of experience (QoE). To ensure that QoE is adequate, it is necessary to thoroughly test applications with a wide range of possible network conditions. For this, network emulation is of vital importance as it allows a tester to run experiments with a wide range of network conditions. However, when it comes to mobile networks, the variety of technical characteristics, coupled with the opaque network configurations, makes realistic emulation a challenging task. Most of the freely available emulation tools rely on a simple emulation, offering limited variability performances for each network condition.In this paper, we propose ERRANT, EmulatoR of Radio Access NeTworks, an open-source tool that emulates mobile networks with a high level of realism, following a data-driven approach. We use a large-scale dataset composed of 100 k speed test measurements collected from 4 network operators in 2 countries. We create 32 different network profiles based on different countries, operators, radio access technologies, and signal qualities. For each profile, we obtain both typical behavior and variability for latency, download and upload bandwidth. We use the profiles to create models by means of the Kernel Density Estimation. Then, ERRANT employs the tc-netem Linux tool and the models for emulation. In this way, ERRANT offers realistic network emulation, in which both typical behavior and network variability are accurately recreated.We validate ERRANT models with an independent dataset of HTTP downloads performed on the same mobile networks as of the profiles. Results show the effectiveness of ERRANT in the emulation of real mobile networks in terms of average behavior and obtained variability. We also show the limitations of a simple emulation, and of other freeware approaches versus ERRANT. Finally, we show two practical use cases to demonstrate the benefits of a dynamic emulation in understanding the performance of web browsing and video streaming. To run new measurement campaigns and create new models, we provide guidelines along with the required open-source code.

An intelligent peer-to-peer streaming model for minimizing flash crown

Peer-to-peer streaming systems (P2PSS) have become well deployed over the Internet in recent times due to its robustness, scalability, distributive nature and cost effectiveness. It is not un-common that peers arrive on the system in large numbers at a particular time in order to retrieve multimedia files. The large spike in the number of peers arriving at a time can be referred to as flash crowd. Several methods have been proposed, models have been designed aiming at providing solution to the problem. This paper attempts to alleviate flash crowd that may occur in the system using a fuzzy logic control system. Inputs were created and fuzzified, rules were developed and then the outputs were defuzzified. Analysis of the results derived from the MATLAB simulation reveal that under a flash crowd scenario, our fuzzy logic controller functions appropriately by the detecting flash crowd when it is about to occur and then necessary actions are taken. Also, with the fuzzy logic control system peer access in and out of the system is successfully controlled. The system allows for new peers to connect more with high bandwidth peers aiming at making the upload rate of each parent proportional to its upload bandwidth thereby utilizing the limited bandwidth resources of the entire P2P system more effectively.Keywords: Peer-to-peer networks, video streaming and flash crowdVol. 26, No. 1, June, 2019

SecP2PVoD: a secure peer-to-peer video-on-demand system against pollution attack and untrusted service provider

The Peer-to-Peer video-on-demand (P2P-VoD) streaming has become widespread in recent years. Unlike the traditional client-server model based video-streaming, the P2P-VoD leverages the peer’s capacity of upload bandwidth for the delivery of video contents in a distributed network. The P2P environment is susceptible to various security threats, in which the pollution attack is one of the potentially destructive threats. Moreover, video streaming is prone to other security challenges, such as authenticity, confidentiality, authorization, and integrity. There have been discussed four possible protection to the pollution attack: blacklisting, hash verification, traffic encryption, and chunk signing. In this paper, we present escrow-free identity-based signcryption (EF-IDSC) scheme for secure data transmission scheme in P2P-VoD streaming with an untrusted service provider. The proposed system enables a peer to establish a session key with other peer using the asymmetric key algorithm. The security analysis shows that the proposed P2P-VoS system prevents pollution attacks under well-known random oracle model and achieves privacy, confidentiality, and subscriber authentication simultaneously. The experimental evaluation shows that the proposed scheme has better computation and communication costs as compared to the related schemes.

FLHyO: fuzzy logic based hybrid overlay for P2P live video streaming

In recent times, enormous growth has been observed in the field of media streaming and real-time communication using peer-to-peer (P2P) network. The popularity of P2P network for live streaming can be credited to its fundamental characteristics such as a decentralized model, low complexity and scalability. Some of the key factors that affect the performance of P2P live streaming are overlay, scheduling schemes and selfish peer. Many structured and unstructured P2P overlay construction techniques have been introduced till now. But both type of overlays have proven to be inadequate in fulfilling the requirements of today’s streaming systems. Generally, the peers in a P2P network are heterogeneous, isolated and mobile in nature. It is difficult to construct an overlay in such a way that resource utilization along with other QoS parameters in the network is maximal. So in this paper, we propose a novel Fuzzy Logic based Hybrid Overlay (FLHyO). FLHyO uses the fuzzy system for determining the priority of each peer during overlay creation. Some of the other factors considered by FLHyO for overlay creation are geographical location, upload bandwidth, age and utilization of a peer. A comparative analysis of FLHyO with some of the landmark overlay approaches verifies that our proposed approach provides better quality of service (QoS) in the network and also improves the video quality at receiver side.

Multi-Party WebRTC Services Using Delay and Bandwidth Aware SDN-Assisted IP Multicasting of Scalable Video Over 5G Networks

At present, multi-party WebRTC videoconferencing between peers with heterogenous network resources and terminals is enabled over the best-effort Internet using a central selective forwarding unit (SFU), where each peer sends a scalable encoded video stream to the SFU. This connection model avoids the upload bandwidth bottleneck associated with mesh connections; however, it increases peer delay and overall network load (resource consumption) in addition to requiring investment in servers since all video traffic must go through SFU servers. To this effect, we propose a new multi-party WebRTC service model over future 5G networks, where a video service provider (VSP) collaborates with a network service providers (NSP) to offer an NSP-managed service to stream scalable video layers using software-defined networking (SDN)-assisted Internet protocol (IP) multicasting between peers using NSP infrastructure. In the proposed service model, each peer sends a scalable coded video upstream, which is selectively duplicated and forwarded as layer streams at SDN switches in the network, instead of at a central SFU, in a multi-party WebRTC session managed by multicast trees maintained by the SDN controller. Experimental results show that the proposed SDN-assisted IP multicast service architecture is more efficient than the SFU model in terms of end-to-end service delay and overall network resource consumption, while avoiding peer upload bandwidth bottleneck and distributing traffic more evenly across the network. The proposed architecture enables efficient provisioning of premium managed WebRTC services over bandwidth-reserved SDN slices to provide videoconferencing experience with guaranteed video quality over 5G networks.

Cooperative Cache Transfer-based On-demand Network Coded Broadcast in Vehicular Networks

Real-time traffic updates, safety and comfort driving, infotainment, and so on, are some envisioned applications in vehicular networks. Unlike traditional broadcast, network-coding-assisted broadcast can satisfy multiple vehicles with different data items in a coded form. However, server side encoding requires the prior knowledge about vehicles’ cache information for the successful decoding at the vehicles’ sides. The explicit cache upload from vehicles to Road Side Unit (RSU) wastes upload bandwidth. In multi-RSU vehicular networks, we propose a Cooperative Cache Transfer-based On-demand Network Coded Broadcast called CCTCB. In the proposed CCTCB approach, vehicles do not need to upload their cache information to the server, rather the RSU server learns the vehicles’ cache intrinsically. We derive a probabilistic model to analyze the coding opportunity in the proposed cooperative cache transfer mechanism incorporating vehicle mobility. The comprehensive simulation results validate the superiority of the proposed approach.

Content Harvest Network: Optimizing First Mile for Crowdsourced Live Streaming

Crowdsourced live streaming (CLS), such as Twitch.tv and Inke.tv, has emerged as an important multimedia application in recent years. Video delivery in such CLS service involves two steps: 1) video uploading-video streaming (i.e., a live channel) generated from a broadcaster is uploaded to the server, which we call the “first mile” network and 2) video distribution-the video streaming is then delivered to viewers in the channel. Today's CLS services usually use conventional content delivery network solutions to address the video distribution problem, while little attention has been paid to improve the video uploading quality. Our measurement study shows that the first mile network causes 17% viewer rebuffers, and some viewers quit the channel once encountering rebuffer. In this paper, we propose a content harvest network (CHN) architecture to address the uploading problem in the CLS service. Specifically, the CHN architecture employs edge devices in the network as relays to receive the streaming uploaded by broadcasters and then forward to the central servers. On one hand, we need to reduce the latency since it is live streaming; on the other hand, we must provide sustainable upload bandwidth. It is challenging to achieve both at the same time, especially in such high dynamic system as CLS. In order to provide global optimal and real-time assignment, we propose a hybrid solution, i.e., centralized and distributed assignment. Specifically, we formulate the centralized relay assignment problem as an optimization problem to achieve both low latency and sustainable bandwidth. To cope with the frequent channel establishments, we use a multi-armed bandit method to characterize the time-variant network condition. Experiment results on a large-scale trace provided by Inke.tv show that our solution can reduce the overall viewer cost by 40% compared to state-of-the-art solutions. The viewers' rebuffer can also be reduced by 50%.

Energy efficient technique for P2P multisource video streaming in mobile ad hoc networks to improve QoE

This paper proposes a novel Quality of experience based Energy Efficient method (QEE) to distribute Peer-to-Peer (P2P) video in a mobile ad hoc network. P2P video distribution is first formulated as a resource allocation problem with the aim of maximizing the end user’s quality of experience. We studied the resource allocation problem as a linear optimization problem to provide efficient utilization of upload bandwidth and energy at each mobile node. Furthermore, scalable video coding is used, that helps maximizing the quality of experience by distributing the layered video over multiple sources using multiple paths to minimize the power consumption and the upload bandwidth at each node. The simulation results show that in the case of 10% uploader nodes in the network, and at the nodes velocity of 1 m/s; QEE method consumes 5 to 25% less power, as compared to existing methods such as; EVAN (Energy aware video streaming in wireless ad hoc network), WCNC (Assessing best strategy for adaptive streaming in mobile ad hoc network), QNE (QoE based non Energy Efficient) and NQNE (Non QoE based Non Energy Efficient). This is because the load is efficiently distributed across multiple sources in the network. Furthermore, the result also shows that for the case of 10% uploader nodes in the network QEE method achieves 10% higher Mean Opinion Score (MOS) among nodes as compared to EVAN and QNE methods as it considers path utility for streaming the video using multiple sources over multiple paths. We have also evaluated the performance of QEE under network churn and flash crown scenarios; the result shows that QEE maintains a reasonable quality under such situations.

Collaborative Caching in P2P Streaming Networks

With the development of the Internet, the Internet applications represented by Peer-to-Peer (P2P) streaming systems bring more and more communication overhead. In order to alleviate communication pressure of the Internet, and improve the user’s access experience, we aim at taking full advantage of peer upload bandwidth contributions with a cache on each peer. While, the size of such a cache on each peer is limited, it is necessary to design the cache replacement strategy in such P2P Systems. In this paper, we implemented a collaborative caching mechanism for P2P streaming networks. Firstly, we designed some measurement experiments for the existing large-scale P2P streaming systems to find some features and problems. Then, we proposed the collaborative caching strategy based on the chunk value and requesting distribution factor to address the existing problems. Our goal is to keep those chunks with high requesting frequency and farther away from the current peer in order to achieve higher cache hit rate and load balancing. Compare to the measured P2P streaming systems, the simulation results show that the proposed method has better performance on multiple metrics such as cache hits, system load and peer collaboration.

Utility maximization for bandwidth allocation in peer-to-peer file-sharing networks

<p style='text-indent:20px;'>Peer-to-peer (P2P) networks have been commonly applied into many applications such as distributed storage, cloud computing and social networking. In P2P networks fairness fosters an incentive so as to encourage peers to offer resources (e.g, upload bandwidth) to the networks. In this paper, we consider fair bandwidth allocation of access links in P2P file-sharing networks and develop a coupled network-wide utility maximization model which aims at achieving several kinds of fairness among requesting peers. We provide a meaningful interpretation of the problem of maximizing social welfare and its sub-problems from an economic point of view. The coupled optimization problem is difficult to resolve in a distributed way because of its non-strict convexity and non-separation. We apply a modified successive approximation method to investigate the coupled problem and propose a distributed bandwidth allocation scheme to solve the approximation problems. Then, we investigate the convergence of the scheme by mathematical analysis and evaluate the performance through numerical examples, which validate that the scheme can achieve the global optimum within reasonable iterations.