Network Service Model Research Articles

On-Demand Coordinated Spectrum and Resource Provisioning Under an Open C-RAN Architecture for Dense Small Cell Networks

Mobile networks have seen more than a thousand times traffic increases in the past decade. Network operators face an ever increasing demand and cost to deploy denser networks in order to maintain the quality of services. In view of this paradigm shift, an open cloud radio access network (C-RAN) service model is studied in this work. Integrating the cross-layer functions of spectrum resource sharing, channel and power allocation, and interference management in a C-RAN architecture, we explore the feasibility of providing a scalable yet efficient broadband wireless service with dense small cell networks (DSN). The proposed methods and architecture can be applied to DSN that support the functions of (further enhanced) inter-cell interference cancelation (feICIC/ICIC) techniques of 3GPP standard, and have the potential to provide a cost-effective solution for high-quality DSN. Simulation results across an area of 100 km <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> show that the proposed scheme can offer an aggregate downlink throughput of 21 Gbps over a maximum channel bandwidth of 20 MHz, which is 5 times the throughput with a typical ICIC method. Moreover, the service satisfaction degree can reach 85% under the proposed C-RAN architecture, making it a promising and cost-effective solution for future broadband wireless services.

A task scheduling algorithm with deadline constraints for distributed clouds in smart cities.

Computing technologies and 5G are helpful for the development of smart cities. Cloud computing has become an essential smart city technology. With artificial intelligence technologies, it can be used to integrate data from various devices, such as sensors and cameras, over the network in a smart city for management of the infrastructure and processing of Internet of Things (IoT) data. Cloud computing platforms provide services to users. Task scheduling in the cloud environment is an important technology to shorten computing time and reduce user cost, and thus has many important applications. Recently, a hierarchical distributed cloud service network model for the smart city has been proposed where distributed (micro) clouds, and core clouds are considered to achieve a better network architecture. Task scheduling in the model has attracted many researchers. In this article, we study a task scheduling problem with deadline constraints in the distributed cloud model and aim to reduce the communication network's data load and provide low-latency services from the cloud server in the local area, hence promoting the efficiency of cloud computing services for local users. To solve the task scheduling problem efficiently, we present an efficient local search algorithm to solve the problem. In the algorithm, a greedy search strategy is proposed to improve the current solutions iteratively. Moreover, randomized methods are used in selecting tasks and virtual machines for reassigning tasks. We carried out extensive computational experiments to evaluate the performance of our algorithm and compared experimental results with Swarm-based approaches, such as GA and PSO. The comparative results show that the proposed local search algorithm performs better than the comparative algorithms on the task scheduling problem.

An advanced intermodal service network model for a practical transition to synchromodal transport in the US Freight System: A case study

• Provide managerial insights for synchromodal freight transportation network designs in long haul transportation. • Present routing models based on MIP for a free mode choice network with different intermodal terminal schedules and delays. • Develop a genetic algorithm to solve the model for an advanced intermodal service network design. Free mode choice, termed “synchromodality,” is an extension of intermodal service network design and is still in the early stages of modeling development. European countries have already started moving toward realizing this innovative transportation system. However, advancement in global transport with longer distances is rare and needs more infrastructural preparation and studies to clarify the steps for such a transition. In this paper, an advanced intermodal service network model (AI-SNM) is proposed to support the development of synchromodal transportation systems. This mixed-integer programming (MIP) model finds the optimal path between O/D pairs while considering horizontal integration of variant transport modes in a supply chain network along with resource constraints and time windows. It minimizes the total transportation cost, transshipment cost, and tardiness with a penalty for delays at intermodal terminals and overdue costs at the destination that accounts for the opening and closing times of the terminals. In order to solve the model for large problem instances, an efficient multiobjective genetic algorithm using a novel coding approach is developed. The algorithm is tested on two US-based case studies, showing the capability of the model to provide cost- and time-saving advantages in long-haul freight. The results of this study can be applied to long-distance global transportation with similar geography and scale.

Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network.

In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks was used as a research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The current research status of wide-field bionic compound-eye target recognition and detection was analyzed, and improvement directions were proposed. The surface microlens array arrangement was designed, and the spaced surface bionic compound eye design principle cloud service network model was established for the adopted spaced-type circumferential hierarchical microlens array arrangement. In order to realize the target localization of the compound eye system, the content of each step of the localization scheme was discussed in detail. The distribution of virtual spherical targets was designed by using the subdivision of the positive icosahedron to ensure the uniformity of the targets. The spot image was pre-processed to achieve spot segmentation. The energy symmetry-based spot center localization algorithm was explored and its localization effect was verified. A suitable spatial interpolation method was selected to establish the mapping relationship between target angle and spot coordinates. An experimental platform of wide-field bionic compound eye target recognition and detection system was acquired. A super-resolution reconstruction algorithm combining pixel rearrangement and an improved iterative inverse projection method was used for image processing. The model was trained and evaluated in terms of detection accuracy, leakage rate, time overhead, and other evaluation indexes, and the test results showed that the cloud service network-based wide-field bionic compound eye target recognition and detection performs well in terms of detection accuracy and leakage rate. Compared with the traditional algorithm, the correct rate of the algorithm was increased by 21.72%. Through the research of this paper, the wide-field bionic compound eye target recognition and detection and cloud service network were organically provide more technical support for the design of wide-field bionic compound eye target recognition and detection system.

Dynamic Allocation of Medical Resources During the Outbreak of Epidemics

During the outbreak of epidemics such as coronavirus disease (COVID-19), the local hospitals often withstand a sharp increase of patient influx, which renders the healthcare system on the verge of collapse. To alleviate the situation, the effective allocation of scarce medical resources during the pandemic plays a vital role. The essence of the healthcare system in time of emergency is to stay functional, and to be able to diagnose and hospitalize as many patients as possible. Fangcang shelter hospital, as a novel way to temporarily increase the capacity of the local healthcare system, is proven to be effective against the COVID-19 pandemic. To improve the performance of the healthcare system with Fangcang, many practical factors need to be taken into account, such as the patient deterioration during waiting to be admitted, the referral mechanism according to the severity of the patients, and the selective admission regulations. To address the high volatility and time-varying feature of the COVID-19, a multistage and multi-type medical service network model is established, and a dynamic allocation strategy of the medical resources at each stage is proposed based on a stochastic optimization problem, which is then solved via the fluid queueing approximation. Combined with the real data collected from Wuhan, it is revealed that the proposed algorithm could help with the allocation of medical resources during the outbreak of epidemics. Even with limited medical resources available, the method could still maintain a guaranteed service level while keeping the healthcare system operational. Furthermore, the simulation analysis validates that our method can effectively allocate medical resources at each stage, so as to stabilize the system performance and fulfill the medical demand for multiple types of patients. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —To fend off the outbreak of epidemics, the lessons have to be learned from the past. The successful control of the spread of COVID-19 in Wuhan (China) is a classical example of applying modern medical practices and management tools. In the present article, the treating procedure of COVID-19 in Wuhan is modeled as a multistage decision problem, which includes the screening with nucleic acid testing, the further testing, the treatment of patients with mild/severe symptoms, or even critical patients. The introduction of Fangcang shelter hospital is crucial for winning the battle against COVID-19. The current study attempts to determine the timing of introducing the Fangcang shelter hospital during the outbreak of a major epidemic, and helps allocate the medical resources needed to contain the spread of the virus. It is discovered that the actual number of beds in the Fangcang shelter hospital is far more than what is necessary, and it would be better to have built the Fangcang some time in advance. In the meantime, the number of designated hospitals for COVID-19 is in line with the results obtained via the optimal staffing strategy proposed here, but it is also noticeable that these hospitals should be released of duty sooner to fight against not only COVID-19 but also other diseases in reality.

Integrated Service Delivery in Fetal Alcohol Spectrum Disorder (FASD): A Review of the Alberta FASD Service Network Model

Integrated Service Delivery in Fetal Alcohol Spectrum Disorder (FASD): A Review of the Alberta FASD Service Network Model

Equilibrium in taxi and ride-sourcing service considering the use of e-hailing application

With the advent of e-hailing applications, ride-sourcing service has become popular and replaced a substantial portion of taxi services. It is crucial to study the impact of different management strategies and regulation policies on taxi and ride-sourcing market performance. We build a taxi network service model involving taxi and ride-sourcing service to study the effect of pricing strategies, fleet size regulation, and customer-driver meeting ways on the equilibrium and the market performance. We prove that there is a solution for the network model and propose a solution algorithm based on the fixed-point iteration method. Numerical experiments are performed to analyze the market performance of taxi and ride-sourcing services under different fleet sizes and pricing strategies. This study provides valuable references for designing policies and measures to regulate taxi and ride-sourcing.

Improved Incentive Pricing Wireless Multi-service Single Link with Bandwidth Attribute

Several objectives that service providers have to achieve are to determine the increase or decrease in the price change due to the change in service quality and the amount of service quality value. Multi-service wireless Internet pricing schemes that apply the quality of the bandwidth advantage are designed to take into account the need of ISPs to provide high-quality services to users and increase their revenue, considering the limited bandwidth of the resources. The modified model is an improvement of the original model by adding variables and parameters to the multiple service network model by specifying the base price for QoS (alpha) and premium quality (β) as variables, parameters, and service class load factor, Pregnancy basis factor and differentiation factor. The models are solved by the program Lingo 18.0 to get the best solution. The results prove that the modified model is the best and yields the best profit for the service provider when the cost of all changes in quality of service is increased and the variable α and β is set as constant or variable.

Management of industrial communications slices: Towards the Application Driven Networking concept

To address the performance problems that many business critical applications are experiencing, network vendors and Network Service Providers (NSP) are reconsidering the integration of some form of application awareness in the way their networks forward user traffic. Their ultimate goal is to devise new network service models that are dedicated and customized to applications while efficiently using network resources. Even if this approach is not new and has been already followed with a mitigated success two decades ago, the emergence of software-Defined networking and network virtualization coupled with DPI (Deep Packet Inspection) pave the way for the investigation of new approaches/solutions towards application aware/driven networks. This is exactly the motivations of this work whose objective is to propose an Application Driven Network (ADN) that provides services to a specific type of applications, i.e. Dynamic Data Distribution Service (DDS) based applications. Considered as one of the leading connectivity standard for industrial IoT communications, focusing on DDS allows a fine-grained description of applications’ traffic and needs. With this information as input, the proposed ADN is able to provision network services that stick to application needs while using network resources efficiently. This paper sketches the general architecture of such ADN by describing its main components, their requirements as well as their algorithms. This solution has been implemented, prototyped and applied to a DDS based distributed interactive simulation application.

The optimized selection strategy of crowdsourcing members in cloud-based design and manufacturing platform

Crowdsourcing services and cloud-based design and manufacturing platforms have been combined into an emerging network service model. Due to the diversity and differences of crowdsourcing members in the platform, member optimized selection process is uncertain and discrete, and it is difficult to find the most satisfying solution. In view of this, this article proposed an optimized selection strategy of crowdsourcing members to help users select reasonable crowdsourcing members to form the cooperative team with the most satisfaction. The research steps in this article are as follows. The first step is to analyze the characteristics of crowdsourcing services and crowdsourcing members in the cloud-based design and manufacturing platform. In the second step, according to the characteristics of crowdsourcing members, the evaluation index and target variables of members in the optimized process are proposed, the optimized selection system is established, and the calculation based on each target variable is given. In the third step, the decision-making model is established based on the optimized selection index system. The model decomposes the task-oriented global optimized selection indexes for crowdsourcing members into subtask-oriented local optimized selection indexes, and the gray relational analysis method is used to solve the model. Finally, the effectiveness of the proposed method is verified by taking the crowdsourcing member optimized selection process in the medical product research and development task as an example.

Resource optimization scheduling and allocation for hierarchical distributed cloud service system in smart city

With the support of 5G system, the hierarchical distributed cloud service network model (HDCSN) is proposed. The model consists of three levels: Access Cloud + Distributed Micro Cloud + Core Cloud, which meets the basic requirements of IMT-2020 (5G) and 3GPP for network system architecture. On the basis of access cloud, the distributed micro-cloud system of Smart City is deployed to migrate the service capabilities of the remote core cloud server to the local area. Users can obtain high-quality low-latency application services from the micro-cloud server in the local area. A resource description model based on resource graph and hierarchical resource vector is established, which enriches the Smart City service mode of IaaS cloud platform and provides a structural basis for optimal scheduling of cluster resources. A multi-node system resource graph scheduling and allocation algorithm VCE-PSO based on particle swarm optimization is proposed to optimize the response speed and resource efficiency of multi-node collaborative scheduling. The example shows that the above key technologies significantly improve 5G. The scheduling optimization and utilization efficiency of various resources in the hierarchical distributed cloud service for the Smart City effectively reduces the response time of the tenant resource request and optimizes the performance of system resource scheduling on the cloud platform.

IMPROVEMENT OF PASSENGER SERVICE PROCESSES OF DEPARTING FLIGHT BASED ON PROJECT MANAGEMENT METHODS

The article considers the formalization of the service technology of departing passengers into network model, which is a good basis for improving the service technology, monitoring the performance that determines the process duration and service optimization in cost and resources. The article shows the formalization result of the service technology of departing passengers into network model; the critical path is found, and the duration of service is determined. In order to find the critical path of the network graph it is recommended to apply the Dijkstra algorithm. It allows us to identify all critical paths from the initial vertex to the final one if there are several. Improving the service process is possible by reducing the performance duration on the critical path and upgrading the service technology. When servicing the departing passengers, there may be factors that lead to the flight departure delay due to the fault of the passenger transportation organization. While analyzing the service for departing passengers, additional work to eliminate the flight delay factors is considered. The service network model is shown in case of untimely removal of the baggage, belonged to the passenger who has not arrived for the flight; the service duration has been determined and critical path activities requiring special attention have been identified. The results analysis provides a list of critical path activities for several reasons of departure violation. It is concluded that it is necessary to reduce the performance duration of critical path graph to ensure the departure of a scheduled flight. Optimization of network model involves consideration of several possible service technologies of departing flight, taking into account the additional work to eliminate the factors leading to the flight delay from the airport and then creation of such service technology which would provide the minimum expenses at given service process duration.

Constraint-aware software-defined network for routing real-time multimedia

Traditional Ethernet-based IP networks do not have the capability to provide the Quality of Service (QoS) required for professional real-time multimedia applications. This is because they operate on a best-effort network service model that does not provide service guarantee. Network operators and service providers require a novel network architecture to efficiently handle the increasing demands of this changing network domain. Software-Defined Networking has emerged as an effective network architecture that decouples the control plane and data plane, which makes it capable of handling the dynamic nature of future network functions and intelligent applications while reducing cost through simplified hardware, software, and management. This paper presents an SDN architecture for real-time low latency applications that offer adaptive path provisioning based on the calculated end-to-end delay, available bandwidth, and traditional shortest path first algorithm. The SDN architecture utilises the Ryu OpenFlow application programming interface (API) to perform real-time monitoring to collect network statistics and computes the appropriate paths by using this information. The experiment to ascertain the feasibility and evaluate the effectiveness of this approach is carried out in an emulated network environment using Mininet.

Evaluation of network service model based on network convergence

Technologies such as Bluetooth, RFID, WiFi, 4G, and the Internet of things are mutually converged with ADSL and fiber to the home network. Users can get information in the forms of word, voice, images, etc. through ubiquitous networks including the fixed telephone, the mobile telephone, the television, the computer, and diversified informational zed terminal equipment. Ubiquity informatization may be the trend of future network development, which is the development direction of the ubiquitous intelligent comprehensive network information society. Its physical representation is the appearance of ubiquitous network or the named universal network. It represents the ubiquitous prosperity that all people, all organizations, and industries can get benefits from the ubiquity informatization. This article studies the internal and external structures of network service model and introduces technology dynamics, demand dynamics, competition, and security as adjustment variables. Then, the evaluation model of network service based on network convergence is proposed and tested. The test results prove the validity of the evaluation model.

The Modeling and Analysis of the Extensible Network Service Model

With the increasing number of new application requirements in network, the capability of providing services in traditional network is being challenged constantly. The network service model, which is the core of the network architecture, directly determines the capability of providing network services. However, there lacks the explicit service model about the research of the next generation network architectures. We propose the extensible network service model (ENSM). In this paper, the basic principle of the ENSM is summarized. Then the mathematical modeling of the ENSM is provided and, based on the mathematical modeling, we analyze the functional description and the performance calculation for composite services when a service composition instance is implemented. Finally, through the experimental modeling and the simulation, the performances of the ENSM are compared with those of the traditional network when providing the same service. The experimental results show that the services can be customized or composed flxibly without sacrificing the performances in the extensible network service model. It can also be seen that the model can implement service extension better and the model idea is correct.

Web services recommendation leveraging semantic similarity computing

With the popularity of Web services adopted for supporting domain applications, recommending and composing appropriate services with respect to user requirements is a challenge. This paper proposes a dynamic programming and variable length genetic algorithm for the recommendation and composition of Web services. Generally, starting and ending services are determined leveraging the constructed service network model. Based on which, services are selected and composed, such that these services should be more appropriate on satisfying users' requirements. Experimental evaluation result shows that our technique is effective and can improve the accuracy of service recommendation.

Web Services Recommendation Leveraging Semantic Similarity Computing

With the popularity of Web services adopted for supporting domain applications, recommending and composing appropriate services with respect to user requirements is a challenge. This paper proposes a dynamic programming and variable length genetic algorithm for the recommendation and composition of Web services. Generally, starting and ending services are determined leveraging the constructed service network model. Based on which, services are selected and composed, such that these services should be more appropriate on satisfying users’ requirements. Experimental evaluation result shows that our technique is effective and can improve the accuracy of service recommendation.

Implementation of young children English education system by AR type based on P2P network service model

Recently, as the Internet service technology has been activated and popularized, digital contents industry is increasingly attracting attention as a promising industry. Digital content is a material or information that appears with the development of information and communication technology. It is represented by a sign character, voice, sound, image and video. This digital content industry has been applied to various disciplines. P2P service model is being used as a new business model in the field of digital contents industry. P2P service model is the most important factor in constructing a collaboration system between users. In other words, as more users collaborate, such as sharing content, contributing computing resources, etc., the network becomes rich in data. In addition, smooth traffic processing can be ensured through contribution of computing power. Conversely, as collaboration between users decreases, the resources of the P2P system become exhausted, which can lead to system collapse. Therefore, this paper developed a system for creative English education for young children. To this end, we designed and developed an English education system that can generate interest by applying augmented reality(AR) and implemented which is based on the P2P network service model. Finally, we provide virtual multimedia education contents using augmented reality and build a system environment applying P2P network service model method. Based on this, we implemented the functions such as learning process, progress check, result feedback between instructor and learner in real time.

Properties of healthcare teaming networks as a function of network construction algorithms.

Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106–108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.

Service Provision in the Framework of Industry 4.0

The purpose of this paper is to analyze the relevance of the industrial service industry in the framework of the project: “Industry 4.0”. In an increasing number of cases, the progress of the project is unsatisfactory and takes on a crisis-like character. Previous research in the context of the concept “Industry 4.0” focus on production environments. By conducting expert interviews, the relevance of services for the future project is examined. The result of the study is the identification of relevant business services, and an assessment of the applicability of scientific approaches to service-networks for the project “Industry 4.0”. The current state of research in the field of Industry 4.0 and service network is used as a basis for this study. The added value of this study is to create a model to assess the service sector by bringing together different scientific approaches so as to meet the necessary interdisciplinary requirement. The decision model allows the service industry to apply the evaluation model for the own business view and strategy. The added value of the evaluation model is the application of service network models in the concept “Industry 4.0” and the completion of the theoretical and practical implementation dimension in the concept.