Study on Task Assignment of Two-stage Multi-service Capability Port Logistics Service Providers

This paper mainly studies the problem of multi-task assignment of providers in port logistics service supply chain.As a core enterprise,port plays the role of logistics service integrator.With the continuous development of industrial integration,logistics service providers not only provide one kind of logistics service,but also develop into composite suppliers who capable of providing a variety of logistics services.This paper studies the task assignment problem of multi-service capability providers in the port logistics service supply chain.The two-stage logistics service provider task assignment model was built,which is based on the mixed evaluation method(including MOORA and FMEA)and the multi-objective planning method.Eventually,the effectiveness of the model method was verified by combining with an example.

QoS-Constrained,Reliable and Energy-Efficient Task Deployment in Cloud Computing

Reliability,QoS and energy consumption are three important concerns of cloud service providers.Most of the current research on reliable task deployment in cloud computing focuses on only one or two of the three concerns.However,these three factors have intrinsic trade-off relationships.The existing studies show that load concentration can reduce the number of servers and hence save energy.In this paper,we deal with the problem of reliable task deployment in data centers,with the goal of minimizing the number of servers used in cloud data centers under the constraint that the job execution deadline can be met upon single server failure.We propose a QoS-Constrained,Reliable and Energy-efficient task replica deployment(QSRE)algorithm for the problem by combining task replication and re-execution.For each task in a job that cannot finish executing by re-execution within deadline,we initiate two replicas for the task:main task and task replica.Each main task runs on an individual server.The associated task replica is deployed on a backup server and completes part of the whole task load before the main task failure.Different from the main tasks,multiple task replicas can be allocated to the same backup server to reduce the energy consumption of cloud data centers by minimizing the number of servers required for running the task replicas.Specifically,QSRE assigns the task replicas with the longest and the shortest execution time to the backup servers in turn,such that the task replicas can meet the QoS-specified job execution deadline under the main task failure.We conduct experiments through simulations.The experimental results show that QSRE can effectively reduce the number of servers used,while ensuring the reliability and QoS of job execution.

支持Web Services语义组合的框架IRS-Ⅱ:分析与讨论

Web Services 是基于 Internet 进行分布式计算的基本元素,面向 Service 的计算将成为未来计算技术发展的趋势。但如何能够自动发现需要的 Service 资源,提高 Web Services 组合的智能化程度,是近来的研究热点之一。IRS-Ⅱ首先提出基于任务本体的 Service 发布、发现和组合方法,可以说是将 Service 发现和组合从语法的层次提升到了语义的层次。本文首先深入分析了IRS-Ⅱ提出的方法及其体系结构,然后对 Web Services 的智能检索和服务组合的问题进行讨论。

基于Web Service的可伸缩工作流管理系统e_Scope Work

在大规模复杂应用环境中,一个业务流程可能涉及企业内或跨地域许多企业内不同的WebService.为了有效支持这类业务流程的处理,提出了一种基于Web Service的可伸缩的工作流管理系统e-ScopeWork的体系结构,研究了其中各组件的功能,详细分析了工作流中任务调度的特点,给出了任务调度、任务管理器处理逻辑以及实现机制,并讨论了流程中任务管理器的部署策略.实现了按应用规模、需求,灵活部署工作流的目标.

一种基于Web Service的异构分布式计算模型

提出了一种基于Web Service的异构分布式计算模型,希望通过利用Web Service这一新技术给异构分布式计算带来一种新思路。通过应用这种模型,能够使用网络中的资源而不必关心网络环境。我们确信因为这种模型带来的一些特点,必将使其日后得到广泛的应用。

Web Service网格计算综合型应用框架的研究

随着网格技术和WebService的不断发展,网格技术与WebService越来越趋融合。针对WebService在网格计算任务调用中请求和分发两种应用框架的单向性,文章提出了一种新的综合型应用框架,该框架可以更有效地在工作代理和网格资源中分配工作任务。最后用实验证明了这三种框架的执行时间差异。

Multitarget stool DNA for colorectal cancer screening:A review and commentary on the United States Preventive Services Draft Guidelines

Multitarget stool DNA(mt-sDNA) testing was approved for average risk colorectal cancer(CRC) screening by the United States Food and Drug Administration and thereafter reimbursed for use by the Medicare program(2014).The United States Preventive Services Task Force(USPSTF) October 2015 draft recommendation for CRC screening included mt-s DNA as an "alternative" screening test that "may be useful in select clinical circumstances",despite its very high sensitivity for early stage CRC.The evidence supporting mt-s DNA for routine screening use is robust.The clinical efficacy of mt-s DNA as measured by sensitivity,specificity,life-years gained(LYG),and CRC deaths averted is similar to or exceeds that of the other more specifically recommended screening options included in the draft document,especially those requiring annual testing adherence.In a population with primarily irregular screening participation,tests with the highest point sensitivity and reasonable specificity are more likely to favorably impact CRC related morbidity and mortality than those depending on annual adherence.This paper reviews the evidence supporting mt-s DNA for routine screening and demonstrates,using USPSTF's modeling data,that mt-s DNA at three-year intervals provides significant clinical net benefits and fewer complications per LYG than annual fecal immunochemical testing,high sensitivity guaiac based fecal occult blood testing and 10-year colonoscopy screening.

Simulation of Service Supply Chainly Formation Based on Mobile Agent

In E-Commerce, consumers and service suppliers can find the services through the searching of Mobile Agents (MA). The suppliers disassemble the service requests of consumers into the sub-requests. Then suppliers respond the sub-requests cooperatively. Thus the Service Supply Chain (SSC) can be formed. But the existing bottom-up and up-bottom supply chain formation fashions cannot be adapted to the SSC in distributed environment of E-Commerce. Task Dependency Network is exploited to illustrate the service relationship among consumers and suppliers. The formation of SSC with some simulations is elaborated. Then the influence on the formation of SSC caused by the type of service suppliers, the quantities of MA and its variety in number is elucidated.

A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

In a cloud environment,consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost.On the other hand,Cloud Service Providers(CSPs)seek to maximize their profits by attracting and serving more consumers based on their resource capabilities.The literature has discussed the problem by considering either consumers’needs or CSPs’capabilities.A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task scheduling in a more efficient way.The paper proposes a model that adopts a Multi-Criteria Decision Making(MCDM)method,called Analytic Hierarchy Process(AHP),to acquire the information of consumers’preferences and service providers’capabilities to prioritize both tasks and resources.The model also provides a matching technique to assign each task to the best resource of a CSP while preserves the fairness of scheduling more tasks for resources with higher capabilities.Our experimental results prove the feasibility of the proposed model for prioritizing hundreds of tasks/services and CSPs based on a defined set of criteria,and matching each set of tasks/services to the best CSPS.

Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

Mobile Edge Computing(MEC)is proposed to solve the needs of Inter-net of Things(IoT)users for high resource utilization,high reliability and low latency of service requests.However,the backup virtual machine is idle when its primary virtual machine is running normally,which will waste resources.Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization.First,these virtual machines are deployed into slots randomly,and then some tasks with cooperative relationship are off-loaded to virtual machines for processing.Different deployment locations have different resource utilization and average service response time.We want tofind a balanced solution that minimizes the average service response time of the IoT application while maximizing resource utilization.In this paper,we propose a task scheduler and exploit a Task Deployment Algorithm(TDA)to obtain an optimal virtual machine deployment scheme.Finally,the simulation results show that the TDA can significantly increase the resource utilization of the system,while redu-cing the average service response time of the application by comparing TDA with the other two classical methods.The experimental results confirm that the perfor-mance of TDA is better than that of other two methods.

美国预防临床服务指南工作组《慢性阻塞性肺疾病筛查推荐意见》更新与解读

慢性阻塞性肺疾病(COPD)是严重危害人类健康的常见病,亦是导致死亡的重要病因,且极大部分诊断不足。COPD筛查是否可以实现疾病早期诊断并改善患者预后?2022年美国预防临床服务指南工作组(U.S.Preventive Services Task Force,USPSTF)针对无症状成年人,通过评估最新研究证据并分析COPD筛查的获益和危害,更新发布了《慢性阻塞性肺疾病筛查推荐意见》(以下简称推荐)。基于有限的证据,USPSTF提出了D级推荐(中度确定筛查没有净获益),不推荐对无症状成年人进行COPD筛查,该推荐与2016版一致。本文将总结分析该推荐的核心要点及其对我国全科医生的指导意义。

基于动态服务缓存辅助的任务卸载方法

针对服务缓存和任务卸载联合优化中,由于缺乏对用户服务请求多样性和动态性的综合考虑而导致的用户体验质量降低问题,提出一种基于动态服务缓存辅助的任务卸载方法。首先,针对边缘服务器执行缓存服务动作空间较大的问题,重新定义了动作,并筛选出最优的动作集合以提高算法训练的效率;其次,设计一种改进的多智能体Q-Learning算法学习最优的服务缓存策略;再次,将任务卸载问题转换为凸优化问题,利用凸优化工具获得最优解;最后,利用拉格朗日对偶法求得最优的计算资源分配策略。为了验证所提方法的有效性,基于真实数据集进行了充分的实验。实验结果表明,对比Q-Learning、双层深度Q网络(D2QN)以及多智能体深度确定性策略梯度(MADDPG)方法,所提方法的响应时间分别降低了8.5%、11.8%和12.6%,平均体验质量分别提高了1.5%、2.7%和4.3%。

震害评估任务驱动的遥感信息服务链构建方法

地震是全球影响最大的自然灾害之一。利用遥感数据对灾区进行动态震害评估,有助于支持应急救援和恢复重建工作,并在一定程度上降低灾害损失。然而,随着Web服务和在线计算技术的快速发展,如何根据不同震害评估任务需求,选择合适的遥感数据和处理服务进行智能组合,构成遥感信息服务链,已成为亟待解决的难题。因此,本文提出了一种任务驱动的遥感信息服务链构建方法,通过分析震害评估任务与遥感服务的特点,基于本体构建统一描述语义的震害评估任务描述模型与遥感信息服务描述模型,研究逐级精化的服务多级语义匹配方法,并从服务类型、服务功能、服务质量三个方面进行服务匹配。结果表明,本方法可构建出12条可用服务链,用时均在70 min内,且最优归一化服务质量指标达到0.607。研究成果能够支持遥感信息服务链构建,可为震害服务管理提供技术支持。

面向缓存的动态协作任务迁移技术研究

边缘网络中不断出现的计算密集和延迟敏感型业务推动了任务迁移技术的快速发展。然而,任务迁移过程中存在应用场景复杂多变、问题建模难度高等技术瓶颈。尤其是考虑用户移动时,如何保证用户服务的稳定性和连续性,设计合理的任务迁移策略仍是一个值得深入探讨的问题。因此,提出了一种移动感知的服务预缓存模型和任务预迁移策略,将任务迁移问题转化为最优分簇与边缘服务预缓存的组合优化问题。首先,基于用户的移动轨迹对当前执行任务状态进行预测,引入动态协作簇和迁移预测半径的概念,提出了一种面向移动和负载两种任务场景的预迁移模型,解决了何时何地迁移的问题。然后,针对需要迁移的任务,基于最大容忍时延约束分析协作簇半径和簇内目标服务器数量的极限值,提出了以用户为中心的分布式多服务器间动态协作分簇算法(Distributed Dynamic Multi-server Cooperative Clustering Algorithm,DDMC)以及面向服务缓存的深度强化学习算法(Cache Based Double Deep Q Network,C-DDQN),解决了最优分簇和服务缓存问题。最后,利用服务缓存的因果关系,设计了一种低复杂度的交替最小化服务缓存位置更新算法,求解出了最佳迁移目标服务器集合,实现了任务迁移中的服务器协作及网络负载均衡。实验结果表明,提出的迁移选择算法具有良好的鲁棒性和系统性能,相比其他迁移算法所消耗的总成本降低了至少12.06%,所消耗的总时延降低了至少31.92%。

MSs-MEC中基于DRL的服务缓存和任务迁移联合优化算法

多服务移动边缘计算(multiple-services mobile edge computing,MSs-MEC)能根据需求自适应调整服务缓存决策,使得部署在用户侧的边缘服务器能够灵活处理不同服务类型的任务。但在实际应用中,特定类型任务的成功迁移依赖于服务环境的提前安装。此外,同时进行任务迁移和服务缓存可能会因时间冲突而导致计算延时。因此,针对上述相关问题,首先将任务迁移和服务缓存决策进行解耦,针对深度强化学习(deep reinforcement learning,DRL)在具有高维的混合决策空间的性能提升不明显的缺点(例如资源分配时利用率不高),将DRL与Transformer结合,通过在历史数据中学习,输出当前时隙的任务迁移决策和下一时隙的任务决策,保证任务到达边缘服务器时能立即执行。其次,为了提高资源分配问题中的资源利用率,将问题分解为连续资源分配问题和离散的任务迁移与服务缓存问题,利用凸优化技术求解资源分配最优决策。广泛的数值结果表明,与其他基线算法相比,提出的算法能有效地减少任务的平均完成时延,同时在资源利用率和稳定性方面也有优异的表现。

电商客服对话提示信息的双任务操作注意分配研究

目的 为研究双任务操作下,不同类型对话提示信息对电商客服注意分配的影响.方法 选取视觉呈现位置和三种常见提示音为自变量,设计了三种实验情景:只呈现两种位置差异的视觉信息、只呈现三种不同的听觉信息、同时呈现视听觉组合信息,对被试人员操作过程中的反应时及正确率进行了分析.结果 电商客服人员在同时接收视听觉对话提示信息时,存在注意分配,视觉上更偏向左侧,听觉上更偏向于机械提示音,当位于左侧的视觉对话提示信息与钢琴音同时出现时,电商客服的操作表现优于其他组合的视听觉对话提示信息.结论 研究对话提示信息双任务操作的注意分配,为电商企业提升客服注意力培训、设计对话提示信息具有一定指导意义.

基层治理中的双向压力型体制及其运行逻辑——基于H镇网格化管理的个案分析

压力型体制作为本土概念业已成熟,但现有研究大多关注上级压力下传的单一向度,忽略了压力型体制对基层服务需求的主动回应。H镇网格化管理的案例表明,在基层治理场域中存在双向压力型体制。这种体制以二重性的压力运行过程应对上级管理要求和群众服务需求的两大压力环境。通过自上而下和自下而上两种压力的对流与互通,分别回应了上下差异性任务需求,也让两侧压力环境分别实现了势能释放和能量互补。双向压力型体制的概念是沟通压力型体制经典框架和基层治理经验的中层理论,凝练了基层实现服管结合的有益经验,蕴含着我国基层治理的独特逻辑。

新媒体应用背景下档案专业服务大局的实践路径——基于“闻档察社”微信公众号的案例分析

本文介绍了依托新媒体平台能够捕捉时事并融合创作立体呈现、突破圈际以辐射多元阅读受众、传播高效以推动响应大政方针的客观优势,“闻档察社”原创微信公众号形成档案专业服务中心大局的特色实践,具体表现为密切追踪时事以专业视角切入、理论联系实践并多方协同思政、契合多元受众同时扩展辐射范围等。在此基础上,笔者从内容创作、运营主体、成果输出三个方面提出“闻档察社”在未来的发展目标,或可为其他同类型新媒体运作提供参考。

基于第三方工作任务的紧密型校企合作探索

良好的校企合作关系需要校、企双方共同维护,其中学校应该起主导作用。南京铁道职业技术学院城轨运营管理专业利用第三方工作任务,在查找安全隐患、解决安全难题、提升职工心理素质等方面为南京地铁运营公司提供了全面的运营安全咨询服务;南京地铁运营公司在获得专业服务的同时,也对学校的学生实习、教师实践、科研立项等工作给予有力支持。校企双方紧密合作,各取所需、互惠互利、相互促进,共同推进校企合作深入发展。

2023年美国预防临床服务指南工作组《成年人抑郁症和自杀风险筛查推荐声明》解读

成年人抑郁症和自杀已成为我国乃至全球重要的公共卫生问题,给患者及社会带来了沉重的疾病负担。2023年美国预防临床服务指南工作组在JAMA上发表了《成年人抑郁症和自杀风险筛查推荐声明》(以下简称USPSTF推荐),并发布了最新证据报告和系统评价结果,认为应对成年人进行抑郁症筛查,包括孕妇、产妇及老年人,但目前自杀筛查的风险与获益证据不充分,无法确定筛查的利弊。本文结合USPSTF推荐和国内外研究现状,从成年人抑郁症和自杀的流行病学、危险因素、早期筛查工具及利弊、治疗和干预、推荐对全科指导价值等方面进行了概述。