Optimal control of parallel queues with impatient customers

We consider a queueing system with a number of identical exponential servers. Each server has its own queue with unlimited capacity. The service discipline in each queue is first-come-first-served (FCFS). Customers arrive according to a state-dependent Poisson process with an arrival rate which is a non-increasing function of the number of customers in the system. Upon arrival, a customer must join a server’s queue according to a stationary state-dependent policy, where the state is taken to be the number of customers in servers’ queues. No jockeying among queues is allowed. Each arriving customer is limited to a generally distributed patience time after which it must depart the system and is considered lost. Two models of customer behavior are considered: deadlines until the beginning of service and deadlines until the end of service. We seek an optimal policy to assign an arriving customer to a server’s queue. We show that, when the distribution of customer impatience satisfies certain property, the policy of joining shortest queue (SQ) stochastically minimizes the number of lost customers during any finite interval in the long run. This property is shown to always hold for the case of deterministic customer impatience.     

Customer satisfaction‐aware scheduling for utility maximization on geo‐distributed data centers

With the increasingly growing amount of service requests from the world‐wide customers, the cloud systems are capable of providing services while meeting the customers' satisfaction. Recently, to achieve the better reliability and performance, the cloud systems have been largely depending on the geographically distributed data centers. Nevertheless, the dollar cost of service placement by service providers (SP) differ from the multiple regions. Accordingly, it is crucial to design a request dispatching and resource allocation algorithm to maximize net profit. The existing algorithms are either built upon energy‐efficient schemes alone, or multi‐type requests and customer satisfaction oblivious. They cannot be applied to multi‐type requests and customer satisfaction‐aware algorithm design with the objective of maximizing net profit. This paper proposes an ant‐colony optimization‐based algorithm for maximizing SP's net profit (AMP) on geographically distributed data centers with the consideration of customer satisfaction. First, using model of customer satisfaction, we formulate the utility (or net profit) maximization issue as an optimization problem under the constraints of customer satisfaction and data centers. Second, we analyze the complexity of the optimal requests dispatchment problem and rigidly prove that it is an NP‐complete problem. Third, to evaluate the proposed algorithm, we have conducted the comprehensive simulation and compared with the other state‐of‐the‐art algorithms. Also, we extend our work to consider the data center's power usage effectiveness. It has been shown that AMP maximizes SP net profit by dispatching service requests to the proper data centers and generating the appropriate amount of virtual machines to meet customer satisfaction. Moreover, we also demonstrate the effectiveness of our approach when it accommodates the impacts of dynamically arrived heavy workload, various evaporation rate and consideration of power usage effectiveness. Copyright © 2014 John Wiley & Sons, Ltd.     

Product from solutions for multiserver centres with concurrent classes of customers

The MultiServer centre with Concurrent Classes of Customers (MSCCC) is a service centre consisting of B parallel identical exponential servers. The customers requesting service at the MSCCC centre belong to K groups. Customers arriving at the MSCCC centre are queued in the order of their arrival. A customer from group k will go into service at the MSCCC centre provided that one or more of the B servers is free and that at most n − 1 other group k customers are in service at the MSCCC centre.

The MSCCC centre can be applied to model systems where customers simultaneously occupy two resources. The system resources are partitioned into K primary and B secondary resources. A customer of group k can access primary resource k if it already is in possession of a secondary resource and if at most n − 1 other group k customers are using primary resource k.

This paper defines the MSCCC centre and presents several examples of computer (sub)systems that can be modelled using the MSCCC centre. The MSCCC centre is shown to satisfy local balance: therefore a multiclass queuing network consisting of BCMP and MSCCC centres has a product form solution. The joint probability distribution (JPD) for a queuing network consisting of several BCMP centres and one MSCCC centre is derived. Aggregation techniques are next used to reduce the JPD to a computationally tractable form. A Mean Value Analysis algorithm is presented for calculating the closed and open chain performance measures at the MSCCC centre.     

考虑客户分类的随机时间车辆路径优化模型与算法

针对一类考虑客户分类、随机旅行时间、随机服务时间及时间窗约束的车辆路径问题构建了机会约束规划模型,该模型考虑两类客户（普通客户与优质客户）并通过添加机会约束条件确保优质客户获得准时服务的概率。同时,设计了变邻域迭代局部搜索算法,并给出了一种基于最小等待时间的初始解生成启发式规则。基于Solomon算例进行了多组仿真实验。仿真实验结果表明,所设计生成初始解的启发式规则是有效的;所给算法能够在短时间内找到确定问题和随机问题的近似最优解;客户比与车辆使用数目呈正相关关系。研究结果对解决资源有限条件下克服随机不确定性因素带来的不利影响、保证客户服务水平等问题有一定的参考意义。     

基于VoD系统批处理阈值的调度分析

本文运用排队论的方法对视频服务系统批处理情形下的部分指标进行了定性分析，分析了系统服务状态；以用户等待平均数和系统吞吐量为主要考察对象，给出了系统吞吐量 、用户等待平均数、批处理阈值、系统服务强度、用户耐心程度的关系；阐述了用户时延受阈值、服务强度及用户耐心程度的影响。仿真结果表明，这也是一种节省资源、提
提高视频服务水平的有效途径。     

Analysis of Networks of the Resource Queuing Systems

Consideration was given to the model of a queuing network with resource queuing systems—the multi-server systems with losses where servicing of the accepted customer occupies random volumes of resources with the given distribution function depending on the customer class and the type of required servicing. Customer servicing in a node can be interrupted by a signal arriving at an exponential time from the start of servicing, and during the time of customer sojourn in the network it may be interrupted more than once. Analytical formulas for calculation of the fundamental probability-time model characteristics—including the joint distribution functions of the number of customers in the nodes and the volumes of resources occupied by them—were proposed on the assumption of the Poisson flows incoming to the nodes and arbitrary servicing.     

基于云计算神经网络物流车辆调度算法研究

研究了物流车辆调度优化问题。针对云计算下任务调度算法没有考虑调度的服务质量和用户满意度的问题,特别是在物流任务调度问题中存在复杂的计算网络,造成计算率降低,为了解决上述问题,提出了一种新的有关云计算和神经网络相结合的物流作业调度算法。算法充分考虑了调度的服务质量以及用户满意度,建立一个参数化的处理模型,计算用户在各个资源上的综合满意度,再将任务分配到满足用户需求和使系统资源达到均衡的资源上执行,最后采用改进的神经网络进行优化车辆调度。实验结果表明,改进算法不仅能满足用户的多种需求,提高了用户的满意度,同时也提高了资源调度率和系统资源的利用率。     

Matrix based proactive resource provisioning in mobile cloud environment

Mobile cloud computing is a dynamic, virtually scalable and network based computing environment where mobile device acts as a thin client and applications run on remote cloud servers. Mobile cloud computing resources required by different users depend on their respective personalized applications. Therefore, efficient resource provisioning in mobile clouds is an important aspect that needs special attention in order to make the mobile cloud computing a highly optimized entity. This paper proposes an adaptive model for efficient resource provisioning in mobile clouds by predicting and storing resource usages in a two dimensional matrix termed as resource provisioning matrix. These resource provisioning matrices are further used by an independent authority to predict future required resources using artificial neural network. Independent authority also checks and verifies resource usage bill computed by cloud service provider using resource provisioning matrices. It provides cost computation reliability for mobile customers in mobile cloud environment. Proposed model is implemented on Hadoop using three different applications. Results indicate that proposed model provides better mobile cloud resources utilization as well as maintains quality of service for mobile customer. Proposed model increases battery life of mobile device and decreases data usage cost for mobile customer.     

Single server retrial queue with group admission of customers

We consider a retrial queueing system with a single server and novel customer׳s admission discipline. The input flow is described by a Markov Arrival Process. If an arriving customer meets the server providing the service, it goes to the orbit and repeats attempts to get service in random time intervals whose duration has exponential distribution with parameter dependent on the customers number in orbit. Server operates as follows. After a service completion epoch, customers admission interval starts. Duration of this interval has phase type distribution. During this interval, primary customers and customers from the orbit are accepted to the pool of customers which will get service after the admission interval. Capacity of this pool is limited and after the moment when the pool becomes full before completion of admission interval all arriving customers move to the orbit. After completion of an admission interval, all customers in the pool are served simultaneously by the server during the time having phase type distribution depending on the customers number in the pool. Using results known for Asymptotically Quasi-Toeplitz Markov Chains, we derive stability condition of the system, compute the stationary distribution of the system states, derive formulas for the main performance measures and numerically show advantages of the considered customer׳s admission discipline (higher throughput, smaller average number of customers in the system, higher probability to get a service without visiting the orbit) in case of proper choice of the capacity of the pool and the admission period duration.     

On the total amount of resources occupied by serviced customers

We consider a model of a multi-server queueing system with losses caused by lack of resources necessary to service claims. A claim accepted for servicing occupies a random amount of resources of several types with given distribution functions. Random vectors that define the requirements of claims for resources are independent of the processes of customer arrivals and servicing, mutually independent, and identically distributed. Under the assumptions of a Poisson arrival process and exponential service times, we analytically find the joint distribution of the number of customers in the system and the vector of amounts of resources occupied by them. We show sample computations that illustrate an application of the model to analyzing the characteristics of a videoconferencing service in an LTE wireless network.     

基于自适应节的多媒体流QoS保证的研究

分布式多媒体计算机系统的一个关键问题是保证连续多媒体流的服务质量（QoS),大多数多媒体流要求的QoS是在一定范围内,即[QoSmin,QoSmax]。为了保证QoS,计算机系统和网络系统必须分配足够的CPU、I/O、内存和网络带宽资源。在多媒体流传输过程中,这些资源的可利用率是动态变化的,尤其是带宽资源,如Internet,文中提出了自适应节的概念,采用PID调节技术,在[QoSmin,QoSmax]内,动态调节QoS,自适应动态的可利用资源变化,既保证了多媒体流的QoS,又提高了资源的利用率。     

A multi-server perishable inventory system with negative customer

In this paper, we consider a continuous review perishable inventory system with multi-server service facility. In such systems the demanded item is delivered to the customer only after performing some service, such as assembly of parts or installation, etc. Compared to many inventory models in which the inventory is depleted at the demand rate, however in this model, it is depleted, at the rate at which the service is completed. We assume that the arrivals of customers are according to a Markovian arrival process (MAP) and that the service time has exponential distribution. The ordering policy is based on (s, S) policy. The lead time is assumed to have exponential distribution. The customer who finds either all servers are busy or no item (excluding those in service) is in the stock, enters into an orbit of infinite size. These orbiting customers send requests at random time points for possible selection of their demands for service. The interval time between two successive request-time points is assumed to have exponential distribution. In addition to the regular customers, a second flow of negative customers following an independent MAP is also considered so that a negative customer will remove one of the customers from the orbit. The joint probability distribution of the number of busy servers, the inventory level and the number of customers in the orbit is obtained in the steady state. Various measures of stationary system performance are computed and the total expected cost per unit time is calculated. The results are illustrated numerically.     

Markov queueing system with finite buffer and negative customers affecting the queue end

A multiserver queueing system with finite buffer, Markov input flow, and Markov (general) service process of all customers on servers with the number of process states and intensities of inter-phase transitions depending on the number of customers in the system is considered. A Markov flow of negative customers arrives to the system; one negative customer “kills” one positive customer at the end of the queue. A recurrent algorithm for computing stationary probabilities of system states is obtained; and a method for calculating stationary distribution of waiting time before starting service of a positive customer is proposed.     

A mechanism for resource pricing and fairness in peer-to-peer networks

In peer-to-peer (P2P) networks, each peer acts as the role of client and server. As a client, each peer is regarded as a service customer. It sends requests to other peers to download files and obtains resource allocation from them. As a server, each peer is thought as a service provider. It receives service requests from other peers and allocates its resources to them. To encourage cooperation between peers, fairness is very important in P2P networks since it fosters an incentive to the peers to offer resources to the network. We formulate a fair resource allocation model for P2P networks and investigate the utility optimization problem by Lagrangian method. In order to realize the optimal resource allocation, we present a novel price-based resource allocation scheme by applying the first order Lagrangian method and low-pass filtering scheme, so that a service provider can allocate its resources to its customers based on offered prices, achieving the efficient and fair allocation of the available resources to the serviced customers. Simulation results confirm that the proposed algorithm can achieve the optimum within reasonable convergence times.     

A multiserver MAP/PH/<Emphasis Type="Italic">N</Emphasis> system with controlled broadcasting by unreliable servers

A multiserver queuing system with an unlimited buffer is considered. The customer arrival is described by the Markov arrival process. The service time has a phase-type distribution. The service may occur with errors. The service strategy is as follows. If the number of busy servers is higher than a certain threshold value at the moment of the customer arrival, then the customer is copied, and the copies are serviced by all the free servers. If the number of busy servers is not higher than this threshold at the moment of the customer arrival, then the customer is serviced by one server. Stationary distributions of the number of customers and the residence time within the system are obtained. The threshold’s influence on the main parameters of the system’s productivity is numerically investigated.     

FCM-based customer expectation-driven service dispatch system

Maintaining long-term customer loyalty has been an important issue in the service industry. Although customer satisfaction can be enhanced with better service quality, delivering appropriate services to customers poses challenges to service providers, particularly in real-time and resource-limited dynamic service contexts. However, customer expectation management has been regarded as an effective way for helping service providers achieve high customer satisfaction in the real world that is nevertheless less real-time and dynamic. This study designs a FCM-based customer expectation-driven service dispatch system to empower providers with the capability to deal effectively with the problem of delivering right services to right customers in right contexts. Our evaluation results show that service providers can make appropriate decisions on service dispatch for customers by effectively managing customer expectations and arranging their contextual limited resources and time via the proposed service dispatch system. Meanwhile, customers can receive suitable service and obtain high satisfaction when appropriate services are provided. Accordingly, a high-performance ecosystem can be established by both service providers and customers who co-create value in the dynamic service contexts.     

电力体制改革新时代下如何提升客户满意度

过去电网企业是垄断经营,随着电力体制改革和国有企业改革的纵深推进,客户有了更多选择。优质服务关乎电网企业新时代改革发展大局,只有优质服务才能使电网企业在改革发展中进入良性循环。然而,从第三方客户满意度调查报告中反映的情况可以看出,部分单位还存在垄断思维,“以客户为中心”的服务意识在实际工作中还未得到很好的落实,具体表现在停电次数多、电压不稳定、业扩流程长、抄表催费欠规范等客户用电体验较敏感的供电服务上。本文从客户体验管理角度,关注客户的用电体验和感受,把满足人民美好生活的电力需要作为电网企业工作的出发点和落脚点,围绕提升客户服务质量的关键点、电网企业存在的客户服务短板、提升客户满意度的有效措施等方面进行了有益地探讨。     

Geom/G/1/n system with LIFO discipline without interrupts and constrained total amount of customers

Consideration was given to the discrete-time queuing system with inversive servicing without interrupts, second-order geometrical arrivals, arbitrary (discrete) distribution of the customer length, and finite buffer. Each arriving customer has length and random volume. The total volume of the customers sojourning in the system is bounded by some value. Formulas of the stationary state probabilities and stationary distribution of the time of customer sojourn in the system were established.     

A Single-Server Queueing System with Background Customers

A single-server queueing system with a Markov flow of primary customers and a flow of background customers from a bunker containing unbounded number of customers, i.e., the background customer flow is saturated, is studied. There is a buffer of finite capacity for primary customers. Service processes of primary as well as background customers are Markovian. Primary customers have a relative service priority over background customers, i.e., a background customer is taken for service only if the buffer is empty upon completion of service of a primary customer. A matrix algorithm for computing the stationary state probabilities of the system at arbitrary instants and at instants of arrival and completion of service of primary customers is obtained. Main stationary performance indexes of the system are derived. The Laplace—Stieltjes transform of the stationary waiting time distribution for primary customers is determined.__________Translated from Avtomatika i Telemekhanika, No. 6, 2005, pp. 74–88.Original Russian Text Copyright © 2005 by Bocharov, Shlumper.     

Comprehensive understanding of smart product service system from multi-dimension and multi-perspective: An innovative service model for Customer-product Interaction Life Cycle (CILC)

With the improvement of living standards and the rapid development of the Internet, customers gradually pursue personalized smart products and services. Traditional smart product service system is mainly aimed at the service of customers and products in one or several interactive links. Furthermore, in the mass personalization model, in order to give full play to the customer experience and participation satisfaction, it is necessary to study the smart product service system based on the interaction between customers and products. However, there is a gap in the research on integrating the whole life cycle of customer-product interaction. In order to meet this industrial need, the innovation of this paper is to construct an innovative service model for Customer-product Interaction Life Cycle (CILC) and analyse the service impact factors and countermeasures using fuzzy DEMATEL method. The study can provide enterprises with the top-level framework and decision-making of smart product service system based on CILC, and realize the effective integration, expansion and value-added of service resources. At the same time, the application of this research methods can shorten the distance between customers and products, improve customer satisfaction.