Queue Size Research Articles

Prediction of Two-Node Tandem Queue with Feedback Having State and Time Dependent Service Rates

Queuing networks are current area of great research and application interest, in view of their increased applicability in - modelling manufacturing facilities and computer/communication networks, production and assembly lines, hospitals, transport systems, banks and so forth. The present paper develops and analyses a tandem queuing model having two nodes with feedback. Such type of model finds its application in many fields, e.g. telecommunication, inventory, hospitals, traffic control and so on. For example, in hospitals, a patient first visits the doctor and goes through a series of examinations, after which he revisits the doctor for medication. The inter-arrival time is exponentially distributed, whereas the service rate for each node depends on the aggregate of customers in the respective queues and thus follows non-homogeneous Poisson process. After constructing the difference –differential equations, and using PGF technique, we have obtained the joint probability distribution for queue size. Some key measures such as the “average number of customers in queue”, “utilization time of each queue”, “average waiting time in each queue” are computed.

Analysis on Computation-Intensive Status Update in Mobile Edge Computing

In status update scenarios, the freshness of information is measured in terms of age-of-information (AoI), which essentially reflects the timeliness for real-time applications to transmit status update messages to a remote controller. For some applications, computational expensive and time consuming data processing is inevitable for status information of messages to be displayed. Mobile edge servers are equipped with adequate computation resources and they are placed close to users. Thus, mobile edge computing (MEC) can be a promising technology to reduce AoI for computation-intensive messages. In this paper, we study the AoI for computation-intensive messages with MEC, and consider three computing schemes: local computing, remote computing at the MEC server, and partial computing, i.e., some part of computing tasks are performed locally, and the rest is executed at the MEC server. Zero-wait policy is adopted in all three schemes. Specifically, in local computing, a new message is generated immediately after the previous one is revealed by computing. While in remote computing and partial computing, a new message is generated once the previous one is received by the remote MEC server. With infinite queue size and exponentially distributed transmission time, closed-form average AoI for exponentially distributed computing time is derived for the three computing schemes. For deterministic computing time, the average AoI is analyzed numerically. Simulation results show that by carefully partitioning the computing tasks, the average AoI in partial computing is the smallest compared to local computing and remote computing. The results also indicate numerically the conditions on which remote computing attains smaller average AoI compared with local computing.

An adaptive, fault tolerant, flow-level routing scheme for data center networks

Recent Data center network topologies put forward multiple paths between the end hosts to provide high bisection bandwidth. For the sake of utilizing the multiple paths efficiently many load-balancing techniques are proposed in literature. These load-balancing proposals mainly deal with distribution of traffic among multiple paths. Further, a good load-balancing technique scales down the latency of flows. While balancing the traffic among multiple paths, few proposals also take care of congestion. Flow-level solutions avoid flow splitting to prevent the packet re-ordering at the destination. Such adaptive solutions try to re-route (change the path) flows dynamically based on the feedback received from the network. In case of link failures, re-routing of the flow based on the queue size of the remote switch alone may be sub-optimal. The path to be chosen among multiple paths for re-routing, also poses a valid question. This paper proposes FlowFurl, an adaptive, distributed, end host driven and flow-level load-balancing technique. This adaptive routing technique supports dynamic flow-to-path assignment. This flow-to-path assignment is performed not only based on the congestion at the switch, but also the status of the links along the path. FlowFurl is the first technique to combine link failure and congestion information parameter for re-routing of flows. The proposed technique is deployment friendly, however it incurs small amount of overhead (small amount of memory at each switch to maintain the link state). We show that our proposed scheme FlowFurl performs better than considered schemes in terms of average flow latency, percentage of flows that achieve deadline and average flow throughput, by utilizing local information such as connectivity information with congestion information.

An Energy-Efficient Distributed Dynamic Bandwidth Allocation Algorithm for Passive Optical Access Networks

The rapid deployment of passive optical access networks (PONs) increases the global energy consumption of networking infrastructure. This paper focuses on the minimization of energy consumption in Ethernet PONs (EPONs). We present an energy-efficient, distributed dynamic bandwidth allocation (DBA) algorithm able to power off the transmitter and receiver of an optical network unit (ONU) when there is no upstream or downstream traffic. Our main contribution is combining the advantages of a distributed DBA (namely, a smaller packet delay compared to centralized DBAs, due to less time being needed to allocate the transmission slot) with energy saving features (that come at a price of longer delays due to the longer queue waiting times when transmitters are switched off). The proposed algorithm analyzes the queue size of the ONUs in order to switch them to doze/sleep mode when there is no upstream/downstream traffic in the network, respectively. Our results show that we minimized the ONU energy consumption across a wide range of network loads while keeping delay bounded.

Stochatic Decomposition Result of an Unrelaible Queue with Two Types of Services

The single server queue with two types of heterogeneous services with generalized vacation for unreliable server have been extended to include several types of generalizations to which attentions has been paid by several researchers. One of the most important results which deals with such types of models is the “Stochastic Decomposition Result”, which allows the system behaviour to be analyzed by considering separately distribution of system (queue) size with no vacation and additional system (queue) size due to vacation. Our intention is to look into some sort of united approach to establish stochastic decomposition result for two types of general heterogeneous service queues with generalized vacations for unreliable server with delayed repair to include several types of generalizations. Our results are based on embedded Markov Chain technique which is considerably a most powerful and popular method wisely used in applied probability, specially in queueing theory. The fundamental idea behind this method is to simplify the description of state from two dimensional states to one dimensinal state space. Finally, the results that are derived is shown to include several types of generalizations of some existing well- known results for vacation models, that may lead to remarkable simplification while solving similar types of complex models.

Analysis of a model of batch arrival single server queue with random vacation policy

This article deals with batch arrival single server queue with random vacation policy, in which the server takes the maximum number of random vacations till it finds some customers waiting in a queue at a vacation completion epoch. If no arrival occurs after completing maximum number of random vacations, the server stays dormant in the system and waits for the upcoming arrival. Here, it is assumed that the customer’s arrival in batches conforms to compound Poisson process, although service time and vacation time are generally distributed. Explicit expressions are obtained for steady state queue size distribution at service completion point and steady state system size probabilities. Some significant measures such as a mean number of batches served during the busy period, Laplace-Stieltjes transform of waiting time, unfinished work and its corresponding mean values are also obtained. A cost optimal policy is developed in terms of the average cost function to determine a locally optimal random vacation policy at a lower cost. Finally, various numerical results are presented for the above system performance measures.

Effect of two forms of feedback on the performance of the Rate Control Protocol (RCP)

The Rate Control Protocol (RCP) uses explicit feedback from routers to control network congestion. RCP estimates it’s fair rate from two forms of feedback: rate mismatch and queue size. An important design question that remains open in RCP is whether the presence of queue size feedback is helpful, given the presence of feedback from rate mismatch. The feedback from routers to end-systems is time-delayed, and may introduce instabilities and complex nonlinear dynamics. Delay dynamical systems are often modeled using delay differential equations to facilitate a mathematical analysis of their performance and dynamics. The RCP models with and without queue size feedback give rise to two distinct nonlinear delay differential equations. Earlier work on this design question was based on methods of linear systems theory. For further progress, it is quite natural to employ nonlinear techniques. In this study, we approach this design question using tools from control and bifurcation theory. The analytical results reveal that the removal of queue feedback could enhance both stability and convergence properties. Further, using Poincaré normal forms and center manifold theory, we investigate two nonlinear properties, namely, the type of the Hopf bifurcation and the asymptotic stability of the bifurcating limit cycles. We show that the presence of queue feedback in the RCP can lead to a sub-critical Hopf bifurcation, which would give rise either to the onset of large amplitude limit cycles or to unstable limit cycles. Whereas, in the absence of queue feedback, the Hopf bifurcation is always super-critical, and the bifurcating limit cycles are stable. The analysis is complemented with computations and some packet-level simulations as well. In terms of design, our study suggests that the presence of both forms of feedback may be detrimental to the performance of RCP.

Nonlinear performance evaluation model for throughput of AQM scheme using full factorial design approach

SummaryThe performance of active queue management (AQM) is measured in terms of throughput, delay, queue size, and loss rate. We have carried out the optimized performance measure of throughput for AQM scheme random early detection (RED) using full factorial design (FDD) technique that is a new approach of performance analysis particularly for congestion control algorithms. We have considered the input factors, viz, buffer size, maximum threshold, and the number of file transfer protocol (FTP) sources for the evaluation of RED that can be used for other AQM schemes, viz, adaptive RED, three‐section RED (TRED), and adaptive queue management with random dropping (AQMRD). The effect of each input factor as well as their interactions are evaluated using factorial design technique that results to obtain the nonlinear equation for performance measure in terms of input factors buffer size, maximum threshold, and the number of FTP sources. Finally, we show the contour plots for variation of performance measure throughput (steady state) from minimum to maximum values with respect to the different setting of input parameters.

Cloud computing based load balancing algorithm for erlang concurrent traffic

<p>The distribution of scheduler from user inquiries in the clouds is complex. In keeping up with the cloud computing environment and the inquirers, the clouds meet with some problematic load balancing complications as an improving load balancing tool induces the rigorous efficiency of the cloud based website’s user access. Overloaded or underloaded conditions originate processing catastrophe regarding the prolonged execution time, bandwidth hog, malfunction, and etc. Besides, to manipulate Erlang concurrent tasks is another skyward situation. Hence, the load balancing is obliged to exhaust all mentioned conditions. The proposed load balancing algorithm for Erlang concurrent tasks (those are and could also be autonomous and unstable.) on VMware workstations is introduced. There are several load patterns within the clouds corresponding to CPU’s load (utilization), memory load (queue size), link capacity load (bandwidth), and so on. The proposed load balancing is to spot underloaded and overloaded conditions then stabilizes the weight amidst computing nodes. There are countless load balancing approaches in the cloud environment to examine performance parameters. A short outline of corresponding performance metrics in the review and their findings are presented. To investigate the fit efficiency of the proposed algorithm, the simulation is applied then results based on the proposed method are compared to the existing ones. The outcomes settle the weight balancing, outperform others when executing Erlang traffic, and are catered in the context.</p>

The Evaluation QS-WFQ Scheduling Algorithm For IoT Transmission To Cloud

This study using the Weighted Fair Queue scheduling algorithm when the weights can change and calculated based on changes in the average queue size in the buffer. This algorithm divides the priorities of each sensor into three priorities, namely high, medium and low priority. Each queue is given a weight that is adjusted to the resource requirements of each traffic. High priority data will take precedence, but medium and low priority data will remain underserved and guaranteed by network resources.The results of this study show packet loss ratio when the ratio of the number of buffers and the amount of data is 1: 3 with variations in the number of high, medium and low priority buffers 75: 75: 150 and 50: 50: 200 is 0%. The delay time in the high priority and the medium priority buffer has almost the same delay time when data is transmitted, whereas for the low priority buffer increased in the delay time.

Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study

This paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvesting energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the buffers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modelled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of the data buffer and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission success probability from buffers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which define the network parameters that ensure stable network operation and finite packet delay. Furthermore, the spatially averaged network performance, in terms of transmission success probability, average queueing delay, and average queue size are investigated. For self-sustainable networks, the results quantify the required buffer size and packet delay, which are crucial for the design of IoT devices and time critical IoT applications.

Congestion Control in the Wild—Investigating Content Provider Fairness

Congestion control (CC) is an indispensable component of transport protocols to prevent congestion collapse as it distributes the available bandwidth among all competing flows, ideally in a fair manner. It thus has a large impact on performance and there exists a constantly evolving set of CC algorithms, each addressing different performance needs. While the algorithms are commonly tested regarding the problems underlying their implementation, the interaction with existing algorithms is often not considered. Additionally considering the fact that content providers (CPs) such as content distribution networks (CDNs) are known to tune TCP stacks for performance gains, the large assortment of algorithms opens the door for custom parametrization and potentially unfair bandwidth sharing. In this paper, we thus empirically investigate if current Internet traffic generated by CPs still adheres to the conventional understanding of fairness. For this, we compare fairness properties of testbed hosts to actual traffic of six major CPs subject to different queue sizes and queueing disciplines in a home-user setting. Additionally, we investigate how mice and elephant flows from the different CPs interact. We find that some employed CC algorithms lead to significantly asymmetric bandwidth shares and very poor flow completion times for mice flows. Fortunately, AQMs such as FQ_CoDel are able to alleviate such unfairness.

Scheduling algorithms for converged ring-based WDM-PON for mobile backhaul traffic

In this work, different heuristic and optimization algorithms are proposed for downstream wavelength scheduling in ring-based WDM-PON mobile backhaul networks, where optical networking units (ONUs) are integrated with base stations (BSs). The main objective of this work is to improve the time delay of the packet delivery from the infrastructure to the end-users for both fixed and wireless traffic. This is achieved through dynamic wavelength scheduling and sharing techniques in a converged ring-based WDM-PON access architecture by taking into account the priorities of the data sent and also the cooperation area for mobile users between adjacent ONUs/BSs. Further, an integer linear program (ILP) was developed for wavelength selection, to be used as a benchmark when comparing with the two proposed algorithms. All heuristic algorithms and the optimization algorithm are examined under different traffic load and queue size scenarios to ascertain the network's performance in terms of maximum packet delivery delay.

Queue and Priority-Aware Adaptive Duty Cycle Scheme for Energy Efficient Wireless Sensor Networks

In Wireless Sensor Networks (WSN), energy efficiency is a fundamental issue that requires attention in the design of communication protocols. Energy waste occurs as a result of collision and idle listening. The widely used mechanism for energy saving in WSN is duty cycling. Duty cycling coordinates the sleep/wake-up time of sensor nodes to maximize the network lifetime while achieving specific application goals such as high throughput or low latency. Most existing works focused more on static duty cycle, which cannot guarantee the desired end-to-end delay at varying network conditions. In applications with specified delay requirements, the duty cycle of every node should be adjusted separately at runtime depending on the network conditions to achieve the desired delay and energy efficiency. In this paper, we present an Energy Efficient and QoS-aware (EEQ) MAC protocol with a duty cycle scheme that adapts the node's duty cycle to the queue size and priority class of a packet to reduce the delay of high priority packets and support time-bounded delivery of priority packets. By checking the queue size and the priority class of packets in the message queue of each node, the node determines whether or not to adjust its duty cycle. In this approach, a node increases the length of its active period in the event of high traffic which provides less waiting time for the packets in the queue. The sender node informs the receiver the duration for which it has to stay awake at the beginning of data transmission, both the sending and the receiver's duty cycle is controlled based on the queue length and the priority of the packets. This approach saves energy and lessen packet latency. Finally, extensive simulation experiments were conducted to evaluate its energy performance within different network topologies. Comparisons with the existing energy-aware MAC protocol verified the effect of EEQ on improving the energy efficiency and extending the lifespan of WSNs.

Analysis of an <i>M</i><SUP align="right">[<i>X</i>]</SUP>/<i>G</i>(<i>a</i>, <i>b</i>)/1 queueing model with multiple vacation controllable arrival during multiple vacation and two phases of repair with delay

The objective of this paper is to analyse an M[X]/G(a, b)/1 queueing model with multiple vacation, controllable arrival during multiple vacation and two phases of repair with delay. Whenever the queue size is less than 'a', the server resumes multiple vacation and continues this until at least 'a' customers are waiting in the queue. After finishing a batch of service, if the server is breakdown with probability γ, the server will be sent for repair after a short interval of time called delay time. After this delay, two consecutive phases of repair (first phase repair, second phase repair) are considered. After the second phase of repair or when there is no breakdown with probability 1-γ, the server starts a vacation if the queue length is less than 'a'. Otherwise, the server starts a service under the general bulk service rule. Using supplementary variable technique, the probability generating function of the queue size at an arbitrary time is obtained for the steady-state case. Also some performance measures and cost model are derived. Numerical illustrations are presented to visualise the effect of various system parameters.

EQueue: Elastic Lock-Free FIFO Queue for Core-to-Core Communication on Multi-Core Processors

In recent years, the number of CPU cores in a multi-core processor keeps increasing. To leverage the increasing hardware resource, programmers need to develop parallelized software programs. One promising approach to parallelizing high-performance applications is pipeline parallelism, which divides a task into a serial of subtasks and then maps these subtasks to a group of CPU cores, making the communication scheme between the subtasks running on different cores a critical component for the parallelized programs. One widely-used implementation of the communication scheme is software-based, lock-free first-in-first-out queues that move data between different subtasks. The primary design goal of the prior lock-free queues was higher throughput, such that the technique of batching data was heavily used in their enqueue and dequeue operations. Unfortunately, a lock-free queue with batching heavily depends on the assumption that data arrive at a constant rate, and the queue is in an equilibrium state. Experimentally we found that the equilibrium state of a queue rarely happens in real, high-performance use cases (e.g., 10Gbps+ network applications) because data arriving rate fluctuates sharply. As a result, existing queues suffer from performance degradation when used in real applications on multi-core processors. In this paper, we present EQueue, a lock-free queue to handle this robustness issue in existing queues. EQueue is lock-free, efficient, and robust. EQueue can adaptively (1) shrink its queue size when data arriving rate is low to keep its memory footprint small to utilize CPU cache better, and (2) enlarge its queue size to avoid overflow when data arriving rate is in burstiness. Experimental results show that when used in high-performance applications, EQueue can always perform an enqueue/dequeue operation in less than 50 CPU cycles, which outperforms FastForward and MCRingBuffer, two state-of-the-art queues, by factors 3 and 2, respectively.

Guaranteed time slot trade-off in QOS improvement with IEEE standard 802.15.4 for wireless sensor networks at the MAC layer

Abstract The performance of wireless sensor networks (WSNs) with IEEE standard 802.15.4 at different types of devices can be improved with the appropriate utilization of guaranteed time slots (GTSs) in superframe at the media access control (MAC) layer. GTS implementation at the MAC layer enhances quality of service (QoS) by providing guarantee for delivery in time to the data collected at real time by the reduced functional device (RFD) from the surroundings to be transmitted to the fully functional device (FFD). Results prove that trade-off has to be done in implementing GTSs for various network performance parameters like queue size, queuing delay, CSMA medium access delay, CSMA transmission failures, and network output load to improve QoS.

Queues With the Dropping Function and Non-Poisson Arrivals

We deal with the single-server queueing system, in which an arriving job (packet, customer) is not allowed to the queue with the probability depending on the queue size. Such a rejected job is lost and never returns to the queue. The study is motivated, but not limited to, active queue management in Internet routers. The exponential service times and general interarrival times are assumed, what makes the model to be a generalization of classic G/M/1 and G/M/1/N queueing models. Firstly, a replacement for the $\rho stability condition, which is too excessive in the considered system, is proven. Then, several popular performance characteristics are derived, including the distribution of the queue size, waiting time, workload and the time to reach a given level, as well as the loss ratio. Finally, numerical examples are presented, demonstrating the impact of the standard deviation of the interarrival time on the system performance, as well as the performance of the system for different parameterizations of the dropping function.

Queue size estimation of nodes in a heterogeneous ocean network with multiple priority traffic

Ocean network is a heterogeneous wireless network of fishing vessels at sea to provide internet over sea. The types of messages exchanged between fishing vessels include emergency data, normal data, voice and video messages. As the connectivity is intermittent, it is necessary to select the most appropriate message from the transmission queue for forwarding. This paper focuses on designing a queuing model with multiple priorities to estimate the queue size of each type of message in a node. Solving the steady state equations gives the number of emergency packets, data packets, audio packets and video packets waiting in the node to be transmitted. Hence the message dissemination algorithm can select the appropriate queue for transmitting the message to maximise the available resources with fairness.

Jumping the Queue: Nepotism and Public-Sector Pay

We set up a model with search and matching frictions to understand the effects of employment and wage policies, as well as nepotism in hiring in the public sector, on unemployment and rent seeking. Conditional on inefficiently high public-sector wages, more nepotism in public-sector hiring lowers the unemployment rate because it limits the size of queues for public-sector jobs. Wage and employment policies impose an endogenous constraint on the number of workers the government can hire through connections.