Earliest Deadline First Scheduling with Active Buffer Management for Real-Time Traffic in the Internet

We studied the problem of QoS guarantee for differentiated services. A two-level hierarchical scheduling framework was deployed to separate QoS metrics. Due to its desirable property of minimizing the maximum packet lateness, the Earliest Deadline First (EDF) scheduling was adopted to provide the in-class scheduling for the time-sensitive traffic. We employed an EDF scheduler combined with an active buffer management scheme (CHOKe) to improve the fairness of resource allocation and to maintain a good delay performance for real-time applications. Simulation results showed that the proposed scheme can achieve a better delay performance and make a more fair bandwidth allocation between the real-time TCP and UDP connections than the First Come First Served (FCFS) scheduling with the drop-tail buffer management which is commonly deployed in traditional IP routers.     

An Optimized Collaborative Scheduling Algorithm for Prioritized Tasks with Shared Resources in Mobile-Edge and Cloud Computing Systems

Mobile edge computing (MEC) is a promising technology that has the potential to meet the latency requirements of next-generation mobile networks. Since MEC servers have limited resources, an orchestrator utilizes a scheduling algorithm to decide where and when each task should execute so that the quality of service (QoS) of each task is achieved. The scheduling algorithm should use the least possible resources required to meet the service demands. In this paper, we develop a two-level cooperative scheduling algorithm with a centralized orchestrator layer. The first scheduling level is used to schedule tasks locally on MEC servers. In contrast, the second level resides at the orchestrator and assigns tasks to a neighboring base station or the cloud. The tasks serve in accordance with their priority, which is determined by the latency and required throughput. We also present a resource optimization algorithm for determining resource distribution in the system in order to ensure satisfactory service availability at the minimum cost. The resource optimization algorithm contains two variations that can be employed depending on the traffic model. One variant is used when the traffic is uniformly distributed, and the other is used when the traffic load is unbalanced among base stations. Numerical results show that the cooperative model of task scheduling outperforms the non-cooperative model. Furthermore, the results show that the suggested scheduling algorithm performs better than other well-known scheduling algorithms, such as shortest job first scheduling and earliest deadline first scheduling.

     

Exact admission control for networks with a bounded delay service

To support the requirements for the transmission of continuous media, such as audio and video, multiservice packet-switching networks must provide service guarantees to connections, including guarantees on throughput, network delays, and network delay variations. For the most demanding applications, the network must offer a service which provides deterministically bounded delay guarantees, referred to as “bounded delay service.” The admission control functions in a network with a bounded delay service require `schedulability conditions' that detect violations of delay guarantees in a network switch. Exact schedulability conditions are presented for three packet scheduling methods: earliest-deadline-first (EDF), static-priority (SP), and a novel scheduling method, referred to as rotating-priority-queues (RPQ). By characterizing the worst-case traffic with general subadditive functions, the presented schedulability conditions can be applied to a large class of traffic models. Examples, which include actual MPEG video traces, are presented to demonstrate the trade-offs involved in selecting a packet scheduling method for a bounded delay service     

Mobile Edge Computing Platform with Container-Based Virtualization Technology for IoT Applications

The next generation of fifth generation (5G) network, implementing mobile edge computing (MEC), network function virtualization (NFV) and software defined networking technologies, establishes a flexible and resilient network in line with various internet of things (IoT) devices. While NFV adds flexibility scale in or out networks by allowing network functions to be dynamically deployed and inter-connected, MEC provide intelligence at the edge of a mobile network; reduces latency, and increases capacity. With the diverse development of networking applications, the proposed MEC with container-based virtualization technology (CVT) as IoT gateway with IoT devices for flow control mechanism in scheduling and analysis methods will effectively enhance the quality of service. In this work, the proposed IoT gateway will be analyzed to elucidate the combined effect of simultaneously deploying virtual network functions and MEC applications on the same network infrastructure. Low latency, high bandwidth and high agility, supporting the connection of large-scale devices, and the efficient combination of resources from network edge and cluster clouds, account for real-time network conditions, reducing the IoT applications and services to indicate that a number is the average of 30% of the latency, that could get more suitable service quality to develop such as both augmented reality and virtual reality application intelligence in coming 5G network.

     

一种基于时延补偿的星上分组调度算法

EDF策略具有有线调度算法中最大调度域和时延保障特性,根据分组时延要求确定服务优先级,是一种动态权重调度策略,通过将IQ-VOQ结构EDF策略引入无线调度并通过加入信道补偿机制和门限丢弃策略,得到一种新的算法IQCEDF,它避开公平排队固有的时延一带宽耦合问题,获得了比EDF更加出色的时延特性,更适于为卫星通信系统分组业务提供服务质量保证。     

Flowmeter for QoS provision in packet switched networks

A flowmeter is a set of traffic-related variables associated with a connection established in a network node as a result of the connection setup. Comprehensive quality-of-service provision to each packet flow is the purpose of flowmeter-based dynamic packet scheduling. The earliest deadline first (EDF) scheduling algorithm is adopted for rate allocation, delay control, and flow control. A gas pressure admission control algorithm is also presented to simplify EDF admission test. The delay performance of the scheduler is evaluated on a subnetwork of the Internet     

Performance Evaluation of Resource Reservation Policies for Rate-Controlled Earliest-Deadline-First Scheduling in Multi-Service Packet Networks

The paper addresses the issue of reserving resources at packet switches along the path of flows requiring a deterministic bound on end-to-end delay. The switches are assumed to schedule outgoing packets using the Rate-Controlled Earliest-Deadline-First (RC-EDF) scheduling discipline. EDF is known to be an optimal scheduling discipline for deterministic delay services in the single scheduler case. We propose a number of static and dynamic reservation policies for mapping the end-to-end delay requirement of a flow into local delay deadlines to be reserved at each scheduler. These policies are based on non-even resource reservation where the resources reserved depend on the capacities and loading at each node in the network. We define and prove the optimality of a certain non-even policy for the case of a single path network with homogenous static traffic. We present extensive simulation results for different scenarios which show that dynamic non-even resource reservation provides superior performance when compared to simple policies such as even dividing of end-to-end delay among the schedulers.     

“5G+MEC”为智能制造赋能的部署应用

MEC是5G网络的关键技术之一,可以将应用本地化,促进网络和业务的深度融合。为实现“5G+MEC”在垂直行业的应用,采用NFV技术部署了服务化架构的5G核心网,并在郑州格力制造园区部署面向智能制造的MEC,采用独立组网方式实现园区5G覆盖,打造了“计算+连接”的5G MEC网络。通过将“5G+MEC”应用在智能制造行业,实现工业制造的网络化、信息化、智能化,使得生产数据在网络边缘处理而不必上传至核心网,降低了网络时延,实现了智能制造的数据闭环。     

Scientific Workflow Makespan Minimization in Edge Multiple Service Providers Environment

The edge computing model offers an ultimate platform to support scientific and real-time workflow-based applications over the edge of the network. However, scientific workflow scheduling and execution still facing challenges such as response time management and latency time. This leads to deal with the acquisition delay of servers, deployed at the edge of a network and reduces the overall completion time of workflow. Previous studies show that existing scheduling methods consider the static performance of the server and ignore the impact of resource acquisition delay when scheduling workflow tasks. Our proposed method presented a meta-heuristic algorithm to schedule the scientific workflow and minimize the overall completion time by properly managing the acquisition and transmission delays. We carry out extensive experiments and evaluations based on commercial clouds and various scientific workflow templates. The proposed method has approximately 7.7% better performance than the baseline algorithms, particularly in overall deadline constraint that gives a success rate.

     

面向5G网络的MEC部署方案

多接入边缘计算技术通过将计算存储能力与业务服务能力向网络边缘迁移,使应用、服务和内容可以实现本地化、近距离、分布式部署,从而在一定程度上解决了5G增强移动宽带、低时延高可靠以及大规模机器通信类终端连接等场景的业务需求.本文在分析MEC技术在LTE网络中的应用方案以及对于5G网络的价值与意义的基础上,给出了5G MEC部...     

基于5G的MEC网络架构与部署策略

多接入边缘计算(MEC)为5G网络必不可少的网元,实现本地化泄流与云服务提供,解决现有网络垂直封闭烟囱式架构不能满足低时延、高带宽等业务需求问题,降低网络传输投资.基于ETSI与3GPP的5G网络进展,提出MEC网络架构与传统无线接入、传输、承载等网络架构融合,使业务面下沉本地化不同场景部署.结合广州实际情况,对本地化...     

TWDM-PON中带有业务区分的混合资源调度算法

针对时分波分复用无源光网络长距离和广覆盖特性带来往返时延增大,造成高优先级业务时延性能严重恶化的问题,提出带有业务区分的混合资源调度算法.根据网络负载实时调整光网络单元组的波长数以实现资源共享,并动态划分子周期以对不同优先级业务进行区分服务;设计混合资源调度算法,以在线方式填充波长空隙,以离线方式保障资源高效调度.仿真结果表明,所提算法能够满足不同优先级业务的时延要求,保证服务质量,并提高信道利用率.     

A Novelistic GSA and CSA Based Optimization for Energy-Efficient Routing Using Multiple Sinks in HWSNs Under Critical Scenarios

Asynchronous transfer mode (ATM) tends to be the most mature infrastructure to serve the imminent media broadband networks and is intended to eliminate network latency and improve traffic output versatility. In Weighted Round Robin (WRR) scheme, the main cause of concern is the delay that is being caused by high volumes of workloads at the wireless source nodes. In this paper, proposed an efficient intelligent time slice based round Robin scheduling algorithm for ATM with the use of integrated speed bit protocol (ISBP). The intelligent time slice offers priority, the blast of the CPU, and the time meaning transfer. The speed bit manager is maintained by the ISBP that contains prioritized objects. Then the intelligent time slice is done to generate the quantum time value. The purpose of this paper to enhance network performance in ATM networks by improving the throughput and average end-to-end delay. The new proposed scheme also offers a significant reduction in the average end-to-end delay when compared to the existing WRR scheme.

     

Intelligent Service Function Chain Mapping Framework for Cloud-and-Edge-Collaborative IoT

With the rapid development of Internet of thing (IoT) technology, it has become a challenge to deal with the increasing number and diverse requirements of IoT services. By combining burgeoning network function virtualization ( NFV) technology with cloud computing and mobile edge computing ( MEC), an NFV-enabled cloud-and-edge-collaborative IoT (CECIoT) architecture can efficiently provide flexible service for IoT traffic in the form of a service function chain (SFC) by jointly utilizing edge and cloud resources. In this promising architecture, a difficult issue is how to balance the consumption of resource and energy in SFC mapping. To overcome this challenge, an intelligent energy-and-resource-balanced SFC mapping scheme is designed in this paper. It takes the comprehensive deployment consumption as the optimization goal, and applies a deep Q-learning(DQL)-based SFC mapping (DQLBM) algorithm as well as an energy-based topology adjustment (EBTA) strategy to make efficient use of the limited network resources, while satisfying the delay requirement of users. Simulation results show that the proposed scheme can decrease service delay, as well as energy and resource consumption.     

Efficient scheduling discipline for Hierarchical Diff‐EDF

Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent quality of service (QoS) requirements to the best‐effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet‐scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees, with Earliest Deadline First (EDF) as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this paper, we propose a new priority assignment scheduling algorithm, Hierarchal Diff‐EDF (Differentiate Earliest Deadline First), which can meet the real‐time needs of these applications while continuing to provide best‐effort service to non‐real time traffic. The Hierarchal Diff‐EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly. Copyright © 2007 John Wiley & Sons, Ltd.     

V2X offloading and resource allocation under SDN and MEC architecture

To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and software defined network (SDN) was constructed.MEC sinks cloud serviced to the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing.The SDN controller could sense network information from a global perspective,flexibly schedule resources,and control offload traffic.To further reduce the system overhead,a joint task offloading and resource allocation scheme was proposed.By modeling the MEC-based V2X offloading and resource allocation,the optimal offloading decision,communication and computing resource allocation scheme were derived.Considering the NP-hard attribute of the problem,Agglomerative Clustering was used to select the initial offloading node,and Q-learning was used for resource allocation.The offloading decision was modeled as an exact potential game,and the existence of Nash equilibrium was proved by the potential function structure.The simulation results show that,as compared to other mechanisms,the proposed mechanism can effectively reduce the system overhead.     

MEC enabled satellite-terrestrial network:architecture,key technique and challenge

The introduction of mobile edge computing (MEC) technology in satellite-terrestrial networks can effectively improve the quality of user experience and reduce network redundant traffic,but also brings some challenges.Firstly,the basic architecture of satellite-terrestrial networks and MEC technology was introduced.Moreover,the motivation of introducing MEC into satellite-terrestrial networks and the deployment of MEC were discussed.Then,the architecture of MEC enabled satellite-terrestrial networks was proposed,and the key techniques and typical applications were summarized and analyzed.Finally,the key challenges such as task scheduling and mobility management and some open research issues in integrated networks were summarized.It hopes to provide new ideas for future research in this field.     

OKRA: optimal task and resource allocation for energy minimization in mobile edge computing systems

To cope with the computational and energy constraints of mobile devices, Mobile Edge Computing (MEC) has recently emerged as a new paradigm that provides IT and cloud-computing services at mobile network edge in close proximity to mobile devices. This paper investigates the energy consumption problem for mobile devices in a multi-user MEC system with different types of computation tasks, random task arrivals, and unpredictable channel conditions. By jointly considering computation task scheduling, CPU frequency scaling, transmit power allocation and subcarrier bandwidth assignment, we formulate it as a stochastic optimization problem aiming at minimizing the power consumption of mobile devices and to maintain the long-term stability of task queues. By leveraging the Lyapunov optimization technique, we propose an online control algorithm (OKRA) to solve the formulation. We prove that this algorithm is able to provide deterministic worst-case latency guarantee for latency-sensitive computation tasks, and balance a desirable tradeoff between power consumption and system stability by appropriately tuning the control parameter. Extensive simulations are carried out to verify the theoretical analysis, and illustrate the impacts of critical parameters to algorithm performance.

     

An Efficient Scheduling Discipline for Packet Switching Networks Using Earliest Deadline First Round Robin

This paper addresses a frame-oriented scheduling discipline, EDF-RR (earliest deadline first round robin), for OQ (output-queued) switch architecture and data traffic consisting of fixed-length cells. Bandwidth reservation for an active session is performed by holding a number of cell slots for the session in a repeatedly-transferred frame. Each cell that is going to be transferred in the frame is assigned a virtual release time and a virtual deadline according to the bandwidth reservation scheme. The transmitting order of the cells in the frame is determined by non-preemptive non-idling EDF algorithm so that cells of a backlogged session in the frame are distributed as uniformly as possible. Through the analysis applying real-time scheduling theory and network calculus as well as network simulation, EDF-RR takes the advantage of O(1) computational complexity, and possesses tight delay bounds and lenient buffer requirements. The proposed scheduling discipline is appropriate for distributed real-time systems as we show that sessions can be configured based on message traffic models and deadline requirements. Also, a modified version of EDF-RR, called EDF-DRR, can be applied as traffic regulator when jitter requirements exist among active sessions. This work was sponsored in part by the Federal Aviation Administration (FAA) via grant DTFA03-01-C-00042. Findings contained herein are not necessarily those of the FAA.     

Joint power control and user scheduling for backbone-assisted industrial wireless networks with successive interference cancellation

In a backbone-assisted industrial wireless network (BAIWN), the technology of successive interference cancellation (SIC) based non-orthogonal multiple access (NOMA) provides potential solutions for improving the delay performance. Previous work emphasizes minimizing the transmission delay by user scheduling without considering power control. However, power control is beneficial for SIC-based NOMA to exploit the power domain and manage co-channel interference to simultaneously serve multiple user nodes with the high spectral and time resource utilization characteristics. In this paper, we consider joint power control and user scheduling to study the scheduling time minimization problem (STMP) with given traffic demands in BAIWNs. Specifically, STMP is formulated as an integer programming problem, which is NP-hard. To tackle the NP-hard problem, we propose a conflict graph-based greedy algorithm, to obtain a sub-optimal solution with low complexity. As a good feature, the decisions of power control and user scheduling can be made by the proposed algorithm only according to the channel state information and traffic demands. The experimental results show that compared with the other methods, the proposed method effectively improves the delay performance regardless of the channel states or the network scales.