Showing papers on "Differentiated service published in 2019"

Service Function Chaining Use Cases in Mobile Networks

Abstract: This document provides some exemplary use cases for service function chaining in mobile service provider networks. The objective of this draft is not to cover all conceivable service chains in detail. Rather, the intention is to localize and explain the application domain of service chaining within mobile networks as far as it is required to complement the SFC problem statement and architecture framework of the working group. Service function chains typically reside in a LAN segment which links the mobile access network to the actual application platforms located in the carrier's datacenters or somewhere else in the Internet. Service function chains (SFC) ensure a fair distribution of network resources according to agreed service policies, enhance the performance of service delivery or take care of security and privacy. SFCs may also include Value Added Services (VAS). Commonly, SFCs are typical middle box based services. General considerations and specific use cases are presented in this document to demonstrate the different technical requirements of these goals for service function chaining in mobile service provider networks. The specification of service function chaining for mobile networks must take into account an interaction between service function chains and the 3GPP Policy and Charging Control (PCC) environment.

Differentiated Service/Data Migration for Edge Services Leveraging Container Characteristics

Abstract: The Multi-access Edge Computing (MEC) and Fog Computing paradigms are enabling the opportunity to have middleboxes either statically or dynamically deployed at network edges acting as local proxies with virtualized resources for supporting and enhancing service provisioning in edge localities. However, migration of edge-enabled services poses significant challenges in the edge computing environment. In this paper, we propose an edge computing platform architecture that supports service migration with different options of granularity (either entire service/data migration, or proactive application-aware data migration) across heterogeneous edge devices (either MEC-based servers or resource-poor Fog devices) that host virtualized resources (Docker Containers). The most innovative elements of the technical contribution of our work include i) the possibility to select either an application-agnostic or an application-aware approach, ii) the possibility to choose the appropriate application-aware approach (e.g., based on data access frequencies), iii) an automatic edge services placement support with the aim of finding a more effective placement with low energy consumption, and iv) the in-lab experimentation of the performance achieved over rapidly deployable environments with resource-limited edges such as Raspberry Pi devices.

Research to improve differentiated HIV service delivery interventions: Learning to learn as we do.

Abstract: In a Perspective, Elvin Geng and Charles Holmes discuss research on differentiated service delivery in HIV care.

Differentiated Latency in Data Center Networks with Erasure Coded Files Through Traffic Engineering

Abstract: This paper proposes an algorithm to minimize weighted service latency for different classes of tenants (or service classes) in a data center network where erasure-coded files are stored on distributed disks/racks and access requests are scattered across the network. Due to the limited bandwidth available at both top-of-the-rack and aggregation switches, and differentiated service requirements of the tenants, network bandwidth must be apportioned among different intra- and inter-rack data flows for different service classes in line with their traffic statistics. We formulate this problem as weighted queuing and employ a class of probabilistic request scheduling policies to derive a closed-form upper-bound of service latency for erasure-coded storage with arbitrary file access patterns and service time distributions. The result enables us to propose a joint weighted latency (over different service classes) optimization over three entangled “control knobs”: the bandwidth allocation at top-of-the-rack and aggregation switches for different service classes, dynamic scheduling of file requests, and the placement of encoded file chunks (i.e., data locality). The joint optimization is shown to be a mixed-integer problem. We develop an iterative algorithm which decouples and solves the joint optimization as 3 sub-problems, which are either convex or solvable via bipartite matching in polynomial time. The proposed algorithm is prototyped in an open-source, distributed file system, Tahoe, and evaluated on a cloud testbed with 16 separate physical hosts in an OpenStack cluster using Cisco switches. Experiments validate our theoretical latency analysis and show significant latency reduction for diverse file access patterns. The results provide valuable insights on designing low-latency data center networks with erasure coded storage.

Using Machine Learning to Provide Reliable Differentiated Services for IoT in SDN-Like Publish/Subscribe Middleware.

Abstract: At present, most publish/subscribe middlewares suppose that there are equal Quality of Service (QoS) requirements for all users. However, in many real-world Internet of Things (IoT) service scenarios, different users may have different delay requirements. How to provide reliable differentiated services has become an urgent problem. The rise of Software-Defined Networking (SDN) provides endless possibilities to improve the QoS of publish/subscribe middlewares due to its greater programmability. We can encode event topics and priorities into flow entries of SDN switches directly to meet customized requirements. In this paper, we first propose an SDN-like publish/subscribe middleware architecture and describe how to use this architecture and priority queues supported by OpenFlow switches to realize differentiated services. Then we present a machine learning method using the eXtreme Gradient Boosting (XGBoost) model to solve the difficult issue of getting the queuing delay of switches accurately. Finally, we propose a reliable differentiated services guarantee mechanism according to the queuing delay and the programmability of SDN to improve QoS, namely, a two-layer queue management mechanism. Experimental evaluations show that the delay predicted by the XGBoost method is closer to the real value; our mechanism can save end-to-end delay, reduce packet loss rate, and allocate bandwidth more reasonably.

Dynamic Load-Balancing Vertical Control for a Large-Scale Software-Defined Internet of Things

Abstract: As the global Internet of things (IoT) has grown in popularity with consumers and the business environment, network flow management has become an important topic to optimize the performance of the IoT. The rigid existing IoT architecture blocks current traffic management technology from providing a real differentiated service for the large-scale IoT. The software-defined IoT (SD-IoT), a new computing paradigm that separates the control plane and data plane and enables centralized logic control, offers a feasible method to address these limitations. In this paper, we investigate a vertical structure of the controller pool for the control plane of the SD-IoT; the controller pool includes the controllers (main controllers) of the main control layer and the controllers (basic controllers) of the basic control layer. We then propose a dynamic balancing algorithm of the main controllers based on an election mechanism and a dynamic load balancing algorithm of the basic controller based on the balanced delay model. The experimental results show that the dynamic balancing algorithm based on the election mechanism can ensure consistency of the messages between the main controllers, and the dynamic load balancing algorithm based on the balanced delay model can balance between these different workloads in the basic controllers.

Load-Balancing and QoS Based Dynamic Resource Allocation Method for Smart Gird Fiber-Wireless Networks

Abstract: Real-time network resource allocation based on virtualization technology is an important method to solve the solidification problem of Fiber-wireless (FiWi) access networks. To increase the resource utilization and meet the specific QoS requirements of smart gird communication services, a Load-balancing and QoS based dynamic resource allocation method (LbQ-DR) is proposed with three sub-mechanisms. A time-window based substrate network resource update mechanism is designed to describe the realtime resource consumption of substrate networks, which can balance the accuracy of resource status and the complexity of the allocation algorithm. A QoS-based Virtual network request (VNR) sorting mechanism is presented to precisely calculate the priority of VNRs and reasonably sort the incoming services. A load-balancing based resource allocation mechanism is designed to avoid unbalanced resource consumption. Especially, the channel interference is considered in the cost of embedding and a collision domain mechanism is introduced to decrease interference. Simulation results demonstrate that the proposed method can provide heterogeneous smart grid businesses with differentiated service, improve the utilization and economic benefits of the network and make the network more balanced.

RAN Slice Strategy Based on Deep Reinforcement Learning for Smart Grid

Abstract: As one of the important application scenarios of the Green Internet of Things (IoT), the development of smart grid is an important means to promote the energy system revolution. Future power grid will rely heavily on smart devices based on the IoT concept. As the 5G standard matures and is put into commercial use, the green interconnected 5G mobile network has shown great potential. With 5G network slicing technology, a wireless private network can be virtualized for each industry to better meet the requirements of smart grid security, reliability and flexibility. Considering the differentiated service characteristics of the smart grid and the challenges of flexibility and adaptability of the communication platform, this paper aims to solve the resource allocation problem of the radio access network (RAN) slice of smart grid. Since the type of service arrival of smart grid is unknown and lacks prior knowledge, deep reinforcement learning (DRL) is used to conduct this research. The mapping from the RAN slice resource management to DRL of the smart grid is analyzed at first, and then discussion from the elastic application and the real-time application is presented. Furthermore, a smart grid RAN slice allocation strategy based on DRL is proposed. Finally, simulation results prove that the proposed algorithm can satisfy the maximization of the resource allocation demand of the smart grid on the RAN side while reducing the cost.

Product Price, Quality and Service Decisions under Consumer Choice Models

Abstract: In this paper, we develop an integrated framework to study a firm's joint decisions on product price, quality and service duration in a variety of monopolistic and competitive scenarios. Product price, quality, and ancillary service (such as maintenance and factory warranty) are arguably among the most important factors consumers consider when making a purchase. Meanwhile, they are also seen as effective instruments for firms to achieve market segmentation. We consider a cost structure for the firm where the service cost depends on the product quality level. In particular, if quality is associated with product reliability (resp., complexity), the service cost would decrease (resp., increase) in the quality level. We adopt the widely used multinomial logit model and the nested logit model to study consumers' choice behavior, and employ mixed integer optimization and game theory to conduct analysis. We find that with multiple substitutable products being offered, it is sufficient for a firm to provide only two maximally differentiated service durations at optimality. The quality of each product should be set at a level such that the marginal utility to consumers equals the marginal cost to the firm, independent of the decisions on other products, whereas pricing decision should take into account all products. In addition, consumer surplus increases when the firm can make more decisions. Regardless of product substitution and market competition, the optimal quality level and service duration for each product can be determined independently of other products. Moreover, service differentiation can benefit consumers and improve the firm's profitability at the same time.

Steward: smart edge based joint QoE optimization for adaptive video streaming

Abstract: With the increase of HTTP-based adaptive video streaming over the Internet, multiple clients may compete for a shared bottleneck bandwidth, which brings some damage to the fairness and stability of Quality of Experience (QoE). This paper presents Steward, a system that enforces multi-client joint QoE optimization for bottleneck bandwidth sharing. Joint QoE optimization refers to improving QoE fairness among clients with various video devices and providing differentiated service for clients with different priorities. Steward deploys the adaptive bitrate (ABR) algorithm based on neural networks (NN) and reinforcement learning at the network edge. The ABR agent trains the NN model through experience and makes appropriate bitrate guidance for video chunks to be requested by clients sharing the same bottleneck bandwidth. We compare Steward with state-of-the-art algorithms under different network conditions. Compared with all considered algorithms and conditions, Steward reduces 30%~85% QoE unfairness under the premise of differentiated service.

Energy efficient service differentiated QoS aware routing in cluster-based wireless sensor network

Abstract: In today's technological era, WSNs has gained attention worldwide with its miniature size and low cost. Data transmission demands both energy and quality of service (QoS) to ensure efficient use of the sensors and adequate access to collecting information. Lot of research work in literature has been focused on QoS provisioning by differentiated service technique that differentiates and priorities different traffic classes to meet the user requirements. Our work toward scheduling based on packet type providing high priority to emergency data to facilitate reliable transmission of emergency data in critical situations. We proposed an approach for effective sensing by use of stochastic scheduling to increase the energy efficiency of sensor nodes for intracluster communication. The proposed technique in this work outperforms when compared with the existing protocol in the literature in terms of minimised energy consumption, delay and high throughput by offloading of the energy-intensive tasks.

Stochastic Profit Maximization of Service Provider in Millimeter-Wave High-Speed Railway Networks

Abstract: We study the problem of profit maximization for service providers using a newly emerged business model in millimeter-wave (mmWave) high-speed railway (HSR) networks. In such business model, a service provider purchases data transmission resource from a network operator with a low price. Then, mobile users only need to pay for requested services provided by the service provider. To optimize the profit of service provider, the profit analysis and optimization framework tailored toward the new business model and mmWave HSR networks is developed. This framework consists of three main components including admission control, transmission control, and resource purchasing control. To obtain optimal policies for these components, a stochastic profit optimization problem is formulated while taking into account differentiated service quality requirements, wireless transmission capacity, and network system stability. Then, the formulated problem is solved by using stochastic network optimization theory and stochastic profit maximization mechanism (SPMM) is established. An extensive performance evaluation of SPMM is conducted in order to demonstrate its superiority.

Voice interception method and system

Abstract: The invention discloses a voice interception method and system, and relates to the field of communication. According to the voice interception method and system in the invention, the voice interception system is deployed in a network; when a called user signs an intelligent voice interception service, an intelligent voice service platform judges whether a calling number is a harassment number or not; and, if the intelligent voice service platform judges that the calling number is the harassment number, a call is established with the calling number through an intelligent calling centre platform; and furthermore, an intelligent call is carried out. According to the voice interception method and system in the invention, intelligent interception and intelligent calling on a harassment call canbe realized through the intelligent interception system; the differentiated service quality of a communication service is improved; and thus, the user experience is improved.

Research on Construction Technology of Generalized Load Model Analysis Library for Space-Time Dimensions

Abstract: In the field of electric marketing, with the continuous deepening of the interactive use of intelligent power, users' willingness to autonomy, choice and participation is becoming more and more urgent, and users have gradually become an important subject of power system operation and interoperability. Different types of users present different characteristics for electricity demand, industrial users pay attention to energy efficiency services, power saving consultation, demand side response, distributed energy access, etc.; commercial users pay attention to integrated energy management, new energy power generation solutions, energy saving solutions Etc. Therefore, analyzing the user's electricity usage and mastering the user's electricity consumption characteristics based on electric big data is of great significance for improving the power supply service level, building the power enterprise brand, and practicing the Internet + marketing service. It is urgent to apply artificial intelligence and data analysis technology to the field of power load characteristic analysis, and to build a general-purpose load feature model library to provide shared and scalable model support for various business application scenarios. Application to household change relationship identification, serial household string identification, source network friendly interaction, precise load control, user differentiated service, time-of-use price design, user-level load forecasting, demand response potential assessment, power stealing identification, default power use Business scenarios such as energy saving, industrial production anomaly monitoring, and user portrait portrayal.

Two-Tier Sharing in Electric Vehicle Service Market

Abstract: Transportation sharing in goods (bike sharing), distinguished from service sharing (ride), has been one of the most active sectors of the sharing economy recently. Such a business model, facilitated by the mobile Internet and cloud computing platforms, seeks supplies in vehicles on demands at matched times and rental locations. The success has attracted more competitors into it, counter-effectively resulted in redundancies in total supplies, reducing social efficiency. In this work, we take electric car sharing as an example to propose a business solution to deal with such a dilemma. Our main idea is to set up a joint venture to provide shared electric cars for different competitors to operate on. These competitors provide their differentiated service for their customers through their own electric mobile Apps, while reducing the infrastructure cost through the joint venture. We study this business model as a two-stage Stackelberg game to analyze the optimal pricing and the sharing scheme of the leader (joint venture) and its followers (car sharing operators). Our model places the sharing of the electric vehicles in two tiers: One among the customers (to reduce the cost of time sharing) and the other among the operators (to reduce the cost of space sharing).

Multi-access Edge Computing in 5G Network Slicing: Opportunities and Challenges

Abstract: 5G is designed to be a multi-service network, capable of supporting diverse range of applications with distinct quality of service (QoS) requirements. Network slicing is one of the key technologies that will enable differentiated service provision on 5G networks, realized using multi-access edge computing (MEC), network function virtualization (NFV), and software-defined networking (SDN). It allows the network operators to build multiple virtual networks over a shared infrastructure, thereby providing network as a service for different service classes. MEC plays a key role in network-slicing based 5G architecture, as it can be used to support virtual network functions for core network (CN) and radio access network (RAN) for latency sensitive applications. Each MEC server can be considered as a pool of virtualized resources running on standard hardware infrastructure. Although network slicing is a promising technology, it still has many challenges that need to be addressed for effective service provisioning. In this work, we focus on challenges related to MEC for supporting network slicing for QoS provisioning in different 5G use cases, and discuss how operating system (OS) level optimizations can help to overcome them.

Problem Statement and Use Cases of Application-aware IPv6 Networking (APN6)

Abstract: Network operators are facing the challenge of providing better network services for users. As the ever developing 5G and industrial verticals evolve, more and more services that have diverse network requirements such as ultra-low latency and high reliability are emerging, and therefore differentiated service treatment is desired by users. However, network operators are typically unaware of which applications are traversing their network infrastructure, which means that only coarse-grained services can be provided to users. As a result, network operators are only evolving their infrastructure to be large but dumb pipes without corresponding revenue increases that might be enabled by differentiated service treatment. As network technologies evolve including deployments of IPv6 and SRv6, the programmability provided by IPv6 and SRv6 encapsulations can be augmented by conveying application related information into the network. Adding application knowledge to the network layer allows applications to specify finer granularity requirements to the network operator. This document analyzes the existing problems caused by lack of application awareness, and outlines various use cases that could benefit from an Application-aware IPv6 Networking (APN6) architecture.

Improving Quality of Service of Border Gateway Protocol Multiprotocol Label Switching Virtual Private Network of EthioTelecom Service Level Agreements

Abstract: The primary goals of Quality of Service (QoS) are managed bandwidth, controlled jitter, minimized latency, and improved packet loss characteristics to provide satisfactory services for users. Shaping network optimization is crucial for the service provider, too. To implement QoS mechanisms optimizing the current network physical and logical architectures is among the best practices. In this paper, an attempt has been made to investigate the end-to-end QoS parameters of multiprotocol border gateway protocol multiprotocol label switching virtual private network (MP-BGP MPLS VPN) EthioTelecom service level agreement (SLA) customers. That is done using differentiated service (DiffServ) model to manage end-to-end traffic delay, jitter, and packet losses. The traffics are classified and marked depending on their priorities. The proposed network architecture has used weighted fair queueing (WFQ) for congestion management and weighted random early detection (WRED) for congestion avoidance. The Huawei’s Enterprise Network Simulation Platform (eNSP) and Wireshark are used to design, demonstrate and evaluate the network architectures. When the results of the existing network are compared with the proposed network architecture its delay, jitter, packet loss and traffic utilization have shown improvements.

Fuzzy-logic-based data-differentiated service supported routing protocol for emergency communication networks in underground mines:

Abstract: Hybrid wireless mesh networks are suitable to construct emergency communication networks after disasters in underground mines. The routing decision in emergency scene is more difficult to give an a...

Method and device of enhanced distributed channel access (EDCA) mechanism-based differentiated service in internet of vehicles and equipment

Abstract: The embodiment of the invention provides a method and a device of enhanced distributed channel access (EDCA) mechanism-based differentiated service in an internet of vehicles and equipment. The methodincludes: receiving vehicle density which is of a current moment of a road and is sent by a roadside unit (RSU); when the vehicle density is less than or equal to a preset density threshold, determining first EDCA parameters and a first queue internal scheduling mechanism, and sending to-be-transmitted information according to the first EDCA parameters and the first queue internal scheduling mechanism; and when the vehicle density is greater than the preset density threshold, determining second EDCA parameters and a second queue internal scheduling mechanism, and sending the to-be-transmittedinformation according to the second EDCA parameters and the second queue internal scheduling mechanism. Through the method and the device of the EDCA mechanism-based differentiated service in the internet of the vehicles and the equipment provided by the embodiment of the invention, performance of information transmission in the internet of the vehicles can be improved.

Method and apparatus for obtaining service data

Abstract: A method for obtaining service data and an apparatus are used to implement obtaining of service data by a data analysis network element. In this method, the data analysis network element obtains service data from a service network element, so that the data analysis network element can perform big data analysis on the obtained service data, thereby implementing differentiated service assurance.

On-Demand Service Sharing with Collective Dynamic Pricing

Abstract: This paper designs a dynamic allocation and pricing mechanism for an on-demand platform that can provide individual or shared services. Time-sensitive customers arrive stochastically onto the platform with heterogenous willingness to pay. The mechanism optimizes at what time, to which customers and at what price to provide services. This environment creates inter-agent and inter-temporal dependencies. We decompose the platform's problem into a dynamic program, based on the novel notion of collective virtual value --- defined as the total surplus that the platform can extract from all customers. The optimal mechanism in this complex environment follows a simple, easily-implementable index rule: service is provided each time the collective virtual value exceeds a threshold, which decreases with the number of available suppliers. Service sharing thus leads to temporal discrimination: as opposed to the classical problem of dynamic pricing with commitment, customers may receive an immediate service or a delayed service --- based on their own willingness to pay and the system's dynamics. Ultimately, service sharing is not exclusively governed by cost-minimization and demand-supply management objectives, but also by discriminatory incentives: it provides an additional degree of freedom to offer differentiated service levels across heterogenous customers.

Service providing method, device and system based on user identity

Abstract: The present application discloses a service providing method based on user identity and a user registration method, as well as a device, a device, a system and a computer storage medium respectively corresponding to the two methods. The user identity-based service providing method comprises: receiving a first access request sent by a client, the first access request including a client identification and/or an access token; determining whether there is an unregistered user corresponding to the client identification or the access token; If so, providing a first personalized service for the non-registered user according to the historical behavior data of the non-registered user; Adopting the technical proposal of the application, the service provided for the user can be determined according to the identity of the user, and for the unregistered user of the system, the differentiated service can be provided for different unregistered users according to the respective historical behavior data of different unregistered users; Therefore, the data utilization efficiency of the system can be effectively improved and the user experience can be improved.

Design of Space Information Network Task Service Station

Abstract: For the spatial information network link load imbalance, the task of differentiated service quality requirements is difficult to meet. This paper proposes a spatial information network task service level agreement, which includes the quality of service requirements and priority avoidance strategies required by the task, and provides a basis for spatial information network resource allocation and task service quality requirements. On this basis, the space information network task service station is designed to perform edge calculation on the task flow that is about to enter the network side, identify and mark the service flow service level, and provide technical support for task-driven network-wide resource scheduling. The simulation results show that in the event of a conflict of task resources, the service station can maintain high task satisfaction while effectively balancing the link load, and has a significant improvement in link resource utilization.

Method and device for acquiring service data

Abstract: The invention discloses a method and a device for acquiring service data, which are used for acquiring the service data by a data analysis network element. According to the method, the data analysis network element acquires the service data from the service network element, so that the data analysis network element can perform big data analysis on the acquired service data, and differentiated service guarantee can be realized.

Pricing and Routing Mechanisms for Differentiated Services in an Electric Vehicle Public Charging Station Network

Abstract: We consider a Charging Network Operator (CNO) that owns a network of Electric Vehicle (EV) public charging stations and wishes to offer a menu of differentiated service options for access to its stations. This involves designing optimal pricing and routing schemes for the setting where users cannot directly choose which station they use. Instead, they choose their priority level and energy request amount from the differentiated service menu, and then the CNO directly assigns them to a station on their path. This allows higher priority users to experience lower wait times at stations, and allows the CNO to directly manage demand, exerting a higher level of control that can be used to manage the effect of EV on the grid and control station wait times. We consider the scenarios where the CNO is a social welfare-maximizing or a profit-maximizing entity, and in both cases, design pricing-routing policies that ensure users reveal their true parameters to the CNO.

Differentiated Service Mechanism According to Vehicle Environment in Vehicular Edge Network

Abstract: With the rapid development of communication technologies such as 5G, vehicular information and applications are exploding. Mobile edge computing (MEC) as a new technology can transfer the information more quickly and accurately. Providing differentiated services for the information can affect the performance of the applications. In this study, based on 802.11p EDCA protocol, we propose a new differentiated service scheme called DD-EDCA (Differentiating Density Enhanced Distributed Channel Access). Firstly, we use MEC Server to estimate the road density. Secondly, different solutions have been designed according to different vehicle density environment requirements. For example, the displacement trend is considered at a low density, and the multi-hop broadcast information is pre-processed at a high density. And the schemes for dynamically adjusting EDCA parameters are designed. Simulation results show that our method reduces latency and packet loss rate, and improves the throughput.