Multi-queue Model Research Articles

Multi-Queue Request Scheduling for Profit Maximization in IaaS Clouds

In cloud computing, service providers rent heterogeneous servers from cloud providers, i.e., Infrastructure as a Service (IaaS), to meet requests of consumers. The heterogeneity of servers and impatience of consumers pose great challenges to service providers for profit maximization. In this article, we transform this problem into a multi-queue model where the optimal expected response time of each queue is theoretically analyzed. A multi-queue request scheduling algorithm framework is proposed to maximize the total profit of service providers, which consists of three components: request stream splitting, requests allocation, and server assignment. A request stream splitting algorithm is designed to split the arriving requests to minimize the response time in the multi-queue system. An allocation algorithm, which adopts a one-step improvement strategy, is developed to further optimize the response time of the requests. Furthermore, an algorithm is developed to determine the appropriate number of required servers of each queue. After statistically calibrating parameters and algorithm components over a comprehensive set of random instances, the proposed algorithms are compared with the state-of-the-art over both simulated and real-world instances. The results indicate that the proposed multi-queue request scheduling algorithm outperforms the other algorithms with acceptable computational time.

Congestion Control and Traffic Differentiation for Heterogeneous 6TiSCH Networks in IIoT.

The Routing Protocol for Low power and lossy networks (RPL) has been introduced as the de-facto routing protocol for the Industrial Internet of Things (IIoT). In heavy load scenarios, particular parent nodes are likely prone to congestion, which in turn degrades the network performance, in terms of packet delivery and delay. Moreover, there is no explicit strategy in RPL to prioritize the transmission of different traffic types in heterogeneous 6TiSCH networks, each according to its criticality. In this paper, we address the aforementioned issues by introducing a congestion control and service differentiation strategies to support heterogeneous 6TiSCH networks in IIoT applications. First, we introduce a congestion control mechanism to achieve load balancing under heavy traffic scenarios. The congestion is detected through monitoring and sharing the status of the queue backlog among neighbor nodes. We define a new routing metric that considers the queue occupancy when selecting the new parent node in congestion situations. In addition, we design a multi-queue model to provide prioritized data transmission for critical data over the non-critical ones. Each traffic type is placed in a separate queue and scheduled for transmission based on the assigned queue priority, where critical data are always transmitted first. The performance of the proposed work is evaluated through extensive simulations and compared with existing work to demonstrate its effectiveness. The results show that our proposal achieves improved packet delivery and low queue losses under heavy load scenarios, as well as improved delay performance of critical traffic.

Theoretical Analysis on Edge Computation Offloading Policies for IoT Devices

The Internet of Things (IoT) has gained great attention in recent years, due to its significant role in industry innovations and promotions. However, it is still facing many technical challenges before fully gaining ground, mainly resulting from limited computational and energy resources of IoT devices and best-effort underlying network paradigms. Thanks to the emerging edge computing that optimizes the cloud computing by processing data at edge networks, IoT devices can offload computation-intensive tasks to their assigned edge computing servers with response time guaranteed and energy consumption saved. As a result, how to perform task offloading by IoT devices has become a key challenge widely discussed. Nevertheless, most of the existing works focus on the tradeoff between executing a task locally and remotely through techniques, such as optimization and game theory, rather than related theoretical model to analyze communication procedures of offloading policies. Thus, in this paper, we propose a multiqueue model to explore the impact of offloading policies on performance of the IoT devices with their assigned edge computing server. Particularly, we consider two simple policies, namely Locality-First policy and Probability-based policy, and obtain their analytic solution of the task mean response time and energy consumption of the IoT devices and edge computing server. Extensive simulations are performed and related results have proved accuracy of the proposed model.

Analysis of multiple-server polling systems by means of the power-series algorithm

We consider a polling model with multiple servers, each of which visits the queues according to its own service order table. In general, such a model is not tractable by means of analytical techniques. In this paper, we show how the model can be analyzed by the power-series algorithm (PSA), a tool for the numerical evaluation and optimization of the performance of a broad class of multi-queue models. Various numerical experiments with the PSA are performed, providing new insights into the behavior of multiple-server polling systems

Performance analysis of flexible workcentres using multiqueue models

We construct a multiqueue model of high fidelity for detailed performance evaluation of flexible machine centres. These models permit one to represent part type specific demand, processing, and setup time values, and to obtain part type specific performance figures. We show through numerical examples that variabilities in system parameters can induce paradoxical system behaviour. We also present an enhanced model which concerns a workpiece undergoing several operations at the work centre, and its application to evaluate alternative schedul ing strategies.

Analysis of a multiqueue model for an ISDN access interface

A performance evaluation method for D-channel access control in narrow band ISDN systems is studied. The access control, which consists of a contention resolving mechanism among terminals and a priority mechanism between signaling information and data, is represented as a multiqueue model with gates. This model has three kinds of arrivals: control signals, user-user signals, and D-channel packets; burst arrival processes of the user-user signals and D-channel packets are represented as batch Poisson processes. Using a decomposition method and results from queueing models with setup times, the Laplace-Stieltjes transforms of access delay distribution are approximated. This approximation is useful for constructing narrow band ISDN systems.

A numerical approach to cyclic-service queueing models

An iterative numerical technique for the evaluation of queue length distributions is applied to multi-queue systems with one server and cyclic service discipline with Bernoulli schedules. The technique is based on power-series expansions of the state probabilities as functions of the load of the system. The convergence of the series is accelerated by applying a modified form of the epsilon algorithm. Attention is paid to economic use of memory space. The technique is based on power-series expansions of the state probabilities as functions of one parameter (the traffic intensity) of the systems. The coefficients of these power series can be recursively calculated for a large class of multi-queue models. The coefficients of the power-series expansions of the moments of the queue length distributions follow directly from those of the state probabillities. In most instances a bilinear transformation ensures convergence of the power series over the whole range of traffic intensities for which the system is stable. We have introduced in Blanc (2,3) extrapolations of the coefficients of the power series in order to accelerate the convergence of the series. One of these extrapolations will be combined with the epsilon algorithm (cf. Brezinski (6), Wynn (13)) in the present paper. The advantages of the present technique are that quantities are calculated iteratively, that it is relatively easy to compute additional terms of the power series in order to increase accuracy, that algorithms for accelerating the convergence of sequences can be applied, and that, once the coefficients of the

Waiting-time approximations in multi-queue systems with cyclic service

This study is devoted to mean waiting-time approximations in a single-server multi-queue model with cyclic service and zero switching times of the server between consecutive queues. Two different service disciplines are considered: exhaustive service and (ordinary cyclic) nonexhaustive service. For both disciplines it is shown how estimates of the mean waiting times at the various queues can be obtained when no explicit information on arrival intensities and service-time distributions is available, while only the utilizations at the queues and the lengths of the busy periods of the system can be measured. In the exhaustive case, a known mean waiting-time approximation is shown to be suitable for our purposes; in the nonexhaustive case, a new approximation has been derived which is simple and yet more accurate than existing approximations. Extensive simulation validates the approximation methods.

Diffusion Approximation for a Token Ring System with Nonexhausive Service

This paper derives approximate formulas for a token ring system with nonexhaustive service, which is commonly used in local area networks. In order to obtain performance measures, the token ring system is regarded as a multiqueue model with cyclic service. The model under consideration is a generalization of the ones treated in the literature. The virtual load probability density function is derived via a diffusion approximation technique. The relation between the virtual load and the actual waiting time is presented. The approximate formula obtained here is evaluated by comparing it to simulation results as well as to other results presented in the literature.

Analysis of a Loop Transmission System with Round-Robin Scheduling of Services

A finite population, multi-queue model is developed for a loop transmission system. Approximate expressions for the state transition matrix and other system variables are derived in recursive forms. It is also shown that a number of useful system parameters, such as average message response time, average cycle time, and average response time conditioned on message length, can be obtained. The analytical results have been validated by simulation.