Search

With the increasing reliance on cloud computing as the foundational infrastructure for technological operations, the urgency and efficacy with which failed virtual machines can be successfully repaired earns significant weight. In this study, we have presented a queueing model that analyzes the repair process of failed virtual machines in cloud computing system. This model includes various important components, such as control N -policy, server unreliability, discouragement behavior of failed virtual machines (like balking and reneging), retention of reneged machines, redundancy, and two-level Bernoulli feedback. A steady-state performance analysis has been performed. The proposed model provides practical suggestions for cloud service providers to improve the reliability and availability of their services, which insights more than theoretical frameworks. This study is unique in the field of queueing models of cloud computing machining environment, as it incorporates parallel consideration of control N policies, balking, reneging, retention, server vacation, two-level Bernoulli feedback and unreliable server behavior. A thorough examination of the behavior of key performance indicators has been conducted and presented using detailed graphical representations. In addition, a cost function is formulated for the proposed model. Further, the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) techniques are utilized to optimize the total cost function, thereby gaining valuable insights into the system's behavior across various conditions as well as to compare the outcomes of GWO and PSO. • Developed a queueing model for cloud computing system for efficient repair of failed virtual machines, incorporating N-policy, balking, reneging, retention, server vacation, Bernoulli feedback, and server unreliability. • Utilized the matrix analytic method to determine system steady-state probabilities to establish various performance measures. • Established a cost function for the proposed model and optimized it using Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). • Compared the outcomes of GWO and PSO for assessing the effectiveness, efficiency, strengths, and weaknesses of GWO and PSO to identify the optimal approach for enhancing system performance. [ABSTRACT FROM AUTHOR]

A general and flexible bi-clustering algorithm for the analysis of Hilbert data is presented in the Object Oriented Data Analysis framework. The algorithm, called HC2 (i.e. Hilbert Cheng and Church), is a non-parametric method to bi-cluster Hilbert data indexed in a matrix structure. The Cheng and Church approach is here extended to the general case of data embedded in a Hilbert space and then applied to the analysis of the regional railway service in the Lombardy region with the aim of identifying recurrent patterns in the passengers' daily access to trains and/or stations. The analysed data, modelled as multivariate functional data and time series, allows to measure both overcrowding and travel demand, providing useful insights to best handle the service. [ABSTRACT FROM AUTHOR]

With the prevalence of COVID-19, the modeling of epidemic propagation and its analyses have played a significant role in controlling epidemics. However, individual behaviors, in particular the self-protection and migration, which have a strong influence on epidemic propagation, were always neglected in previous studies. In this paper, we mainly propose two models from the individual and population perspectives. In the first individual model, we introduce the individual protection degree that effectively suppresses the epidemic level as a stochastic variable to the SIRS model. In the alternative population model, an open Markov queueing network is constructed to investigate the individual number of each epidemic state, and we present an evolving population network via the migration of people. Besides, stochastic methods are applied to analyze both models. In various simulations, the infected probability, the number of individuals in each state and its limited distribution are demonstrated. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide simulation modelling for bulk arrival bulk service queueing system involved in a textile industry and analyze the performance metrics. Design/methodology/approach: This paper describes the simulation modelling of a bulk queueing system with limited number of admissions and multiple vacations. The model is developed for the proposed queueing system using Flexsim 2017, and it is explained through an application observed in a textile industry involving the process of cone winding. Findings: In this paper, the simulation model has been developed to study the behaviour of queues at different resources in a production system. Various performance measures such as average components, average waiting time, total number of inputs and outputs, processing time and idle time involved in a textile industry are evaluated using simulation and justified through numerical illustration. Practical implications: The proposed simulation model may be used in various scenarios wherever a real time situation exists related to bulk queueing system. The results produced in this paper can be used by the manufacturing industries to enhance the need-based accuracy. It is worth pointing out that the findings are of direct practical relevance and can be successfully used for a number of industrial applications. Originality/value: The approach suggested in this paper attempts to deal with the queueing system involved in a textile industry and provides numerical results in less time with less computer resources. It provides a reasonably good approximation for simple and complex queueing models where it is difficult to find closed form of theoretical results. [ABSTRACT FROM AUTHOR]

The article discusses high-frequency trading (HFT) and its key components. According to the author, the barriers to entry into HFT have started to decline by 2010 due to the advent of more esoteric technologies. Problems associated with collocation, which is the first step in HFT, include data center contact, contract negotiation and profit. The two networking methods used in HFT are data-center cross and cross-data-center wide area network (WAN) links. The author says correlated burst is the key to addressing the internal Network Address Translation (NAT) problem. Also discussed are the queue position, trading rates and exchange networking.

The article discusses the obstacles to scalability of Web applications. These obstacles include two-hase commit, insufficiet caching, serial processing, absence of feature flags, single copy of the database, use of database for queuing, use of database for full-text searching, object relational models and the lack of instrumentation. Obstacles to scaling beyong optimization speed include the lack of browse-only mode, the lack of a code repository and version control, lack of documentation and lack of fire drills.

The article discusses active queue management (AQM), examining how it can be used to manage buffers and control queue delay. The article proposes Controlled Delay, of CoDel, an approach to AQM which could be used on the Internet and tested on Linux-based routers. The article discusses the bufferbloat problem, CoDel's algorithm, and link rates and packet-sojourn time in CoDel. The article provides information on simulations which were used to test CoDel, data packets at different bandwidths, and dynamic link testing.

A new algorithm called the tree convolution algorithm, for the computation of normalization constants and performance measures of product-form queueing networks, is presented. Compared to existing algorithms, the algorithm is very efficient in the solution of networks with many service centers and many sparse routing chains. (A network is said to have sparse routing chains if the chains visit, on the average, only a small fraction of ail centers in the network.) In such a network, substantial time and space savings can be achieved by exploiting the network's routing information. The time and space reductions are made possible by two features of the algorithm: (1) the sequence of array convolutions to compute a normalization constant is determined according to the traversal of a tree; (2) the convolutions are performed between arrays that are smaller than arrays used by existing algorithms. The routing information of a given network is used to configure the tree to reduce the algorithm's time and space requirements; some effective heuristics for optimization are described. An exact solution of a communication network model with 64 queues and 32 routing chains is illustrated. [ABSTRACT FROM AUTHOR]

Consistency control has to be enforced in database management systems (DBMS) where several transactions may concurrently access the database. This control is usually achieved by dividing the database into locking units or granules, and by specifying a locking policy which ensures integrity of the information. However, a drawback of integrity enforcement through locking policies is the degradation of the global system performance. This is mainly due to the restriction imposed by the locking policies to the access of transactions to the database, and to the overheads involved with the management of locks. A framework for the quantitative analysis of the impact of these factors on the performance of DBMS is presented in this paper. In a first step, the main factors which determine the behavior of these systems are pointed out and analyzed independently. The results hereby obtained are aggregated in a second step to yield a global performance evaluation. Throughout this hierarchical modeling approach various analytical techniques are used and the results are illustrated by numerical examples. The paper concludes by pointing out the final results' sensitivity to some basic assumptions concerning transaction behavior and the need for more experimental studies in this area. [ABSTRACT FROM AUTHOR]

In the last two decades there has been special interest in queueing networks with a product form solution. These have been widely used as models of computer systems and communication networks. Two new computational algorithms for product form networks are presented. A comprehensive treatment of these algorithms and the two important existing algorithms, convolution and mean value analysis, is given. [ABSTRACT FROM AUTHOR]

The possibility of giving different quality of service to jobs of different classes by regulating their memory allocation is examined in the context of a paged computer system. Two parameterized algorithms which partition the main memory between two classes of jobs are considered. Initially, a closed system consisting of a processor and paging and file devices, with fixed numbers of jobs, is studied to determine optimal degrees of multiprogramming and the proportion of processor time devoted to each class. Applying a decomposition approach and treating the closed system as a single server, the response times in an open system with external arrivals are studied. The object is to investigate the effect of the memory allocation parameters on the expected response times under the two algorithms. Numerical solutions and economical lower bounds for the expected response times as functions of the control parameters are obtained. A way of applying the results to systems with more than two job classes is indicated. [ABSTRACT FROM AUTHOR]

Describes the internal structure of a computer operating system as a set of cooperating sequential processes. Synchronization by means of semaphores and extended semaphores; Explanation of the semaphore constructions; Design principle; Discussion of project management and performance.

Pricing control is an important problem in service systems and it aims to control customer behaviors through an economic way, instead of administrative commands. In this paper, we study a dynamic pricing and service rate control problem in an open Jackson network with limited capacity. The goal is to determine the optimal admission prices and the optimal service rates at every state such that the long-run average social welfare is maximized. The original problem is decomposed into a rate-setting problem plus a price-setting problem. To solve the rate-setting problem, we derive a difference formula based on the sensitivity-based optimization theory. When the cost rate function is convex in service rates and the value rate function is concave in arrival rates, we decompose the rate-setting problem into a series of convex optimization subproblems. When the rate functions have linear structure, these subproblems are even simpler and a bang–bang control is optimal. For the price-setting problem, we determine the state-dependent prices so as to induce the optimal arrival rates obtained by the rate-setting problem. We propose a recursive algorithm to numerically compute the conditional expected delays at every state. Finally, we conduct numerical experiments to explore the optimality properties and some useful insights for this dynamic pricing control problem. [ABSTRACT FROM AUTHOR]

The multiclass queueing network (McQN) arises as a natural multiclass extension of the traditional (single-class) Jackson network. In a single-class network, subcriticality (i.e., subunitary nominal workload at every station) entails stability, but this is no longer sufficient when jobs/customers of different classes (i.e., with different service requirements and/or routing scheme) visit the same server; therefore, analytical conditions for stability of McQNs are lacking, in general. In this note, we design a numerical (simulation-based) method for determining the stability region of a McQN, in terms of arrival rate(s). Our method exploits certain (stochastic) monotonicity properties enjoyed by the associated Markovian queue-configuration process. Stochastic monotonicity is a quite common feature of queueing models and can be easily established in the single-class framework (Jackson networks); recently, also for a wide class of McQNs, including first-come-first-serve networks, monotonicity properties have been established. Here, we provide a minimal set of conditions, under which the method performs correctly. Eventually, we illustrate the use of our numerical method by presenting a set of numerical experiments, covering both single- and multiclass networks. [ABSTRACT FROM AUTHOR]

Keywords: Rotterdam; Netherlands; Europe; Manufacturing; Business EN Rotterdam Netherlands Europe Manufacturing Business 320 320 1 07/24/23 20230727 NES 230727 2023 JUL 27 (NewsRx) -- By a News Reporter-Staff News Editor at Blood Weekly -- Investigators discuss new findings in Business - Manufacturing. Keywords for this news article include: Rotterdam, Netherlands, Europe, Manufacturing, Business, Erasmus University. [Extracted from the article]

The article discusses the Oregon 217 Active Traffic Management project deployed in July 2014 as a comprehensive implementation of automated technologies to improve the operations and safety of Oregon Route 217 freeway system by the state's Transportation Department. Noted are the systems of the project to address safety and reliability, including travel time, queue warning, congestion-response. The use of active traffic management strategies to manage transportation systems is also noted.

We develop a gradient algorithm for optimizing the performance of product-form networks through online adjustment of control parameters. The use of standard algorithms for finding optimal parameter settings is hampered by the prohibitive computational burden of calculating the gradient in terms of the stationary probabilities. The proposed approach instead relies on measuring empirical frequencies of the various states through simulation or online operation so as to obtain estimates for the gradient. Besides the reduction in computational effort, a further benefit of the online operation lies in the natural adaptation to slow variations in ambient parameters as commonly occurring in dynamic environments. On the downside, the measurements result in inherently noisy and biased estimates. We exploit mixing time results in order to overcome the impact of the bias and establish sufficient conditions for convergence to a globally optimal solution. We discuss our algorithm in the context of different systems, including queueing networks, loss networks, and wireless networks. We also illustrate how the algorithm can be used in such systems to optimize a service/cost trade-off, to map parameter regions that lead to systems meeting specified constraints, and to achieve target performance measures. For the latter application, we first identify which performance measures can be controlled depending on the set of configurable parameters. We then characterize the achievable region of performance measures in product-form networks, and finally we describe how our algorithm can be used to achieve the target performance in an online, distributed fashion, depending on the application context. [ABSTRACT FROM PUBLISHER]

The \mathrmc\mu rule is known to be optimal in many queueing systems with memoryless service and inter-arrival times. We establish a \mathrmc\mu rule for a parallel flexible server system with two tiers. Multiple job classes arrive and wait in separate queues. The first tier contains classes that can only be served by one server each, and the second tier contains a class that can be served by all servers. The \mathrmc\mu preferences give priority to the first tier. Sequencing decisions are made to minimize linear holding costs. [ABSTRACT FROM AUTHOR]

In this technical note, we consider closed tandem queueing networks with finite buffers and blocking. We assume that at least one station has subexponential service time distribution. We analyze this system under communication blocking and manufacturing blocking rules. Our objective is to derive expressions for the tail asymptotics of transient cycle times and waiting times. Furthermore, we study under which conditions on system parameters these tail asymptotics also hold for their stationary counter parts. Finally, we provide numerical examples to understand the convergence behavior of the tail asymptotics. [ABSTRACT FROM PUBLISHER]

Consider a generalized processing system with several queues, where the available service rate combinations are fluctuating over time due to reliability and availability variations, and the scheduler must respond dynamically to the workload and service availability. We establish that cone schedules, which leverage the geometry of the queueing dynamics, maximize the system throughput for a broad class of processing systems, even under adversarial arrival processes. [ABSTRACT FROM PUBLISHER]

The article offers hardware-based tips and optimisations intended to give a fast computer system. Topics covered include the importance of Advanced Host Controller Interface (AHCI) in allowing solid-state drive (SSD) to take advantage of Native Command Queuing, the proper way to ensure the monitor is calibrated correctly and the disadvantages of dangling cables inside a computer. Also mentioned is the installation of random access memory (RAM).

We study tandem queueing systems with finite buffers in which servers work more efficiently in teams than on their own and the synergy among collaborating servers can be task-dependent. Our goal is to determine the dynamic server assignment policy that maximizes the long-run average throughput. When each server works with the same ability at each task that she/he is assigned to, we show that any nonidling policy where all servers work in teams of two or more at all times is optimal. On the other hand, when the server abilities are task-dependent, we show that for Markovian systems with two stations and two servers, depending on the synergy among the servers, the optimal policy either assigns the two servers to different stations when possible, or lets them work in a team at all times. Finally, for larger Markovian systems, we provide sufficient conditions that guarantee that the optimal policy has all servers working together at all times. [ABSTRACT FROM AUTHOR]

The article offers the author's view on how computer programmers in the U.S. mirror the Domain-Driven Design (DDD) data from one system to another. The author states that computer programers can maintain customer data by allowing the system to interact with a data storage mechanism. The author notes the use of the RabbitMQ, an open source message queues. The author mentions the use of sets of test to cause messages to be published to the queue.

This paper presents a game theoretic framework for studying Stackelberg routing games on parallel networks with horizontal queues, such as transportation networks. First, we introduce a new class of latency functions that models congestion due to the formation of physical queues. For this new class, some results from the classical congestion games literature (in which latency is assumed to be a non-decreasing function of the flow) do not hold. In particular, we find that there may exist multiple Nash equilibria that have different total costs. We provide a simple polynomial-time algorithm for computing the best Nash equilibrium, i.e., the one which achieves minimal total cost. Then we study the Stackelberg routing game: assuming a central authority has control over a fraction of the flow on the network (compliant flow), and that the remaining flow (non-compliant) responds selfishly, what is the best way to route the compliant flow in order to minimize the total cost? We propose a simple Stackelberg strategy, the Non-Compliant First (NCF) strategy, that can be computed in polynomial time. We show that it is optimal for this new class of latency on parallel networks. This work is applied to modeling and simulating congestion relief on transportation networks, in which a coordinator (traffic management agency) can choose to route a fraction of compliant drivers, while the rest of the drivers choose their routes selfishly. [ABSTRACT FROM AUTHOR]

This paper studies a stochastic system where the performance of the server changes stochastically and cyclically. We first investigate the performance measures of the system, including the queue length and the overall cost. In particular, we derive an exact expression for the expected length of the renewal cycle, and present closed matrix forms for the mean and variance of the queue length. We then develop an explicit method to tackle a workload control problem, based on an M/G/1 queue approximation. Numerical examples are presented to illustrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Smart energy grid is an emerging area for new applications of machine learning in a nonstationary environment. Such a nonstationary environment emerges when large-scale failures occur at power networks because of external disruptions such as hurricanes and severe storms. Power distribution networks lie at the edge of the grid, and are especially vulnerable to external disruptions. Quantifiable approaches are lacking and needed to learn nonstationary behaviors of large-scale failure and recovery of power distribution. This paper studies such nonstationary behaviors in three aspects. First, a novel formulation is derived for an entire life cycle of large-scale failure and recovery of power distribution. Second, spatial-temporal models of failure and recovery of power distribution are developed as geolocation-based multivariate nonstationary GI(t)/G(t)/\infty queues. Third, the nonstationary spatial-temporal models identify a small number of parameters to be learned. Learning is applied to two real-life examples of large-scale disruptions. One is from Hurricane Ike, where data from an operational network is exact on failures and recoveries. The other is from Hurricane Sandy, where aggregated data is used for inferring failure and recovery processes at one of the impacted areas. Model parameters are learned using real data. Two findings emerge as results of learning: 1) failure rates behave similarly at the two different provider networks for two different hurricanes but differently at the geographical regions and 2) both the rapid and slow-recovery are present for Hurricane Ike but only slow recovery is shown for a regional distribution network from Hurricane Sandy. [ABSTRACT FROM PUBLISHER]

Pickup and delivery problems (PDPs), in which objects or people have to be transported between specific locations, are among the most common combinatorial problems in real-world logistical operations. A widely-encountered type of PDP is the Stacker Crane Problem (SCP), where each commodity/customer is associated with a pickup location and a delivery location, and the objective is to find a minimum-length tour visiting all locations with the constraint that each pickup location and its associated delivery location are visited in immediate, consecutive order. The SCP is NP-Hard and the best known approximation algorithm only provides a 9/5 approximation ratio. In this paper, we examine an embedding of the SCP within a stochastic framework, and our objective is three-fold: First, we describe a large class of algorithms for the SCP, where every member is asymptotically optimal, i.e., it produces, almost surely, a solution approaching the optimal one as the number of pickups/deliveries goes to infinity; moreover, one can achieve computational complexity O(n^2+\varepsilon) within the class, where n is the number of pickup/delivery pairs and \varepsilon is an arbitrarily small positive constant. Second, we characterize the length of the optimal SCP tour asymptotically. Finally, we study a dynamic version of the SCP, whereby pickup and delivery requests arrive according to a Poisson process, and which serves as a model for large-scale demand-responsive transport (DRT) systems. For such a dynamic counterpart of the SCP, we derive a necessary and sufficient condition for the existence of stable vehicle routing policies, which depends only on the workspace geometry, the distributions of pickup and delivery points, the arrival rate of requests, and the number of vehicles. Our results leverage a novel connection between the Euclidean Bipartite Matching Problem and the theory of random permutations, and, for the dynamic setting, exhibit novel features that are absent in traditional spatially-distributed queueing systems. [ABSTRACT FROM AUTHOR]

The article presents questions and answers related to web applications development including the execution of a simple structured query language (SQL) update, re-signaling SQL error back to the report program generator (RPG) program, and job monitoring driven by data queueing.

This short communication considers a tandem queue fed by Lévy input. The main result concerns expressions for the Laplace transform of the transient workload in the downstream queue, under the condition that the system starts off empty. This expression greatly simplifies if the driving Lévy process is spectrally one-sided; in that situation the transform is given explicitly in terms of the Laplace exponent of the Lévy input. [ABSTRACT FROM AUTHOR]

The article demonstrates the performance of the shortest-path graph analysis with the use of Structure Query Language Common Language Runtime (SQL CLR) procedure. It mentions the creation of a database, then creating a CLR stored procedure and the use of the Visual Studio for performing the shortest-path analysis. It also notes the required random-access priority queue data structure for the shortest-path algorithm.

In this technical note, we discuss the optimality properties of service rate control in closed Jackson networks. We prove that when the cost function is linear to a particular service rate, the system performance is monotonic w.r.t. (with respect to) that service rate and the optimal value of that service rate can be either maximum or minimum (we call it Max–Min optimality); When the second-order derivative of the cost function w.r.t. a particular service rate is always positive (negative), which makes the cost function strictly convex (concave), the optimal value of such service rate for the performance maximization (minimization) problem can be either maximum or minimum. To the best of our knowledge, this is the most general result for the optimality of service rates in closed Jackson networks and all the previous works only involve the first conclusion. Moreover, our result is also valid for both the state-dependent and load-dependent service rates, under both the time-average and customer-average performance criteria. [ABSTRACT FROM AUTHOR]

Abstract: Open queueing networks are useful for the performance analysis of numerous real systems. Since exact results exist only for a limited class of networks, decomposition methods have been extensively used for approximate analysis of general networks. This procedure is based on several approximation steps. Successive approximations made in this approach can lead to a considerable error in the output. In particular, there are no general accurate formulas for computing the mean waiting time and the inter-departure variance in general multiple-server queues. This causes the results from decomposition methods when applied to G/G/m queueing networks to be very approximative and to significantly deviate from actual performance values. We suggest substituting some approximate formulae by low-cost simulation estimates in order to obtain more accurate results when benefiting from the speed of an analytical method. Numerical experiments are presented to show that the proposed approach provides improved performance. [Copyright &y& Elsevier]

The article describes key aspects of a conceptual solution that leverage the power of parallel processing in a multicore computer. Basic assumptions are presented involving technologies beyond the Task Parallel Library (TPL). The functions of the remote task client are provided along with attributes of the task coordinator and the role of task execution nodes. The implementation of the remote task client is discussed in relation to client requests. The semantics of the throttles are reviewed.

Scheduling policies that favor small jobs have received growing attention due to their superior performance with respect to mean delay, e.g., Shortest Remaining Processing Time (SRPT) and Preemptive Shortest Job First (PSJF). In this paper, we study the delay distribution of a generalization of the class of scheduling policies called SMART (because policies in it have “SMAll Response Times”), which includes SRPT, PSJF, and a range of practical variants, in a discrete-time queueing system under the many sources large deviations regime. [ABSTRACT FROM AUTHOR]

We consider a stationary waiting time in a Poisson driven single-server m-node tandem queue with either constant or non-overlapping service times. Each node except for the first one has a finite buffer, and is operated under production blocking. By using (max,+)-algebra, we explicitly express the stationary waiting time at each node as a function of finite buffer capacities. We also address that the explicit expression is separable and monotone decreasing with respect to the buffer sizes. These properties are applied to a buffer allocation problem with probabilistic constraints on stationary waiting times. [ABSTRACT FROM AUTHOR]

The article offers the author's insights on his messaging applications software called Queue with Position Reservation or PRQueue. He states that using PRQueue assures that the order of messages on output queue conforms to the existing input queue despite of which core routines complete the process. He also mentions that the design of PRQueue permits the user to hide or divide thread safety code so that he or she does not need to worry on writing any unlocking or locking logic.

The article explores the input/output (I/O) scheduler and the file system in the SUSE Linux Enterprise Server. Among the techniques that can be used to manipulate the request queue in the I/O scheduler are request merging and priority reordering. Also discussed are the types of Linux I/O Schedulers including the Deadline and Completely Fair Queuing (CFQ) schedulers. It offers tips on selecting the right file system for server performance such as choosing Oracle Cluster File System 2 (OCFS2) for cluster performance.

The article focuses on the advanced uses of Dynamic Array Service Program (DASP). It says that DASP is applicable in integrated language environment (ILE) programs. It discusses the dynamic array program JOBMON Asynchronous Job, which monitors message queues. It examines how JOBMON works and the subroutines it uses such as DO loop, CALCWAIT, and SHUTDOWN. It also presents figures showing JOBMON's programming codes including the main section, the iniatilizations, and SUBMIT subroutine.

The consensus problem is considered for a team of second-order mobile agents communicating via a network with noise, variable delays and occasional packet losses. A queuing mechanism is applied and the switching process of the interaction topology of the network is modeled as a Bernoulli random process. In such a framework, a necessary and sufficient condition is presented for the mean-square robust consensus. Moreover, a necessary and sufficient condition of the solvability of the mean-square robust consensus problem is established. An approach to designing consensus protocol is proposed and numerical examples are given to illustrate the results. [ABSTRACT FROM AUTHOR]

The article discusses how to install an International Business Machine Corp. (IBM) toolkit Rational Developer for i (RDi) to monitor message queue on IBM's System i. It mentions that the said tool will show all messages in the view and warns user if a message arrives with severity greater than or equal to the severity users required in the queue. The process of installing the said tool is offered including the RDi plug-ins to use, finishing the applications, and deploying the applications made.

We consider performance of open multiclass queueing networks under general scheduling policies. Two linear program (LP) performance bounds are compared, the achievable region method and the approximate linear program with quadratic approximation architecture. The latter is shown to give tighter upper and lower bounds. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with state-dependent open Markovian (or exponential) queuing networks, for which arrival and service rates, as well as routing probabilities, may depend on the queue lengths. For a network of this kind, following Mandelbaum and Pats, we provide a formal definition of its associated fluid model, and we focus on the relationships which may occur between the network stochastic dynamics and the deterministic dynamics of its corresponding fluid model, particularly focusing on queuing networks whose fluid models have global periodic attractors. [Copyright &y& Elsevier]

Abstract: On the basis of variable structure control (VSC), an active queue management (AQM) controller is presented for a class of TCP communication networks. In the TCP/IP networks, the packet drop probability is limited between 0 and 1. Therefore, we modeled TCP/AQM as a rate-based non-linear system with a saturated input. The objective of the VSC-based AQM controller is to achieve the desired queue size and to guarantee the asymptotic stability of the closed-loop TCP non-linear system with saturated input. The performance and effectiveness of the proposed control law are then validated for different network scenarios through numerical simulations in both MATLAB and Network Simulator-2 (NS-2). Both sets of simulation results have confirmed that the proposed scheme outperforms other AQM schemes. [Copyright &y& Elsevier]

The article focuses on the features of Windows Communication Foundation (WCF) 4.0 of .NET Framework 4.0 that will be released in 2010. It cites that WCF 4.0 settle many pain points related to several programs including configuration and messaging. It notes that the new release of WCF will have new enterprise-ready features such as service discovery, web programming and RecieveContext technique for queued messaging. An overview of the use of the new features are presented.

Much of the research on network modeling and analysis has focused on the design of end controllers and network algorithms with the objective of stability and convergence of the transmission rate. However, a network is typically composed of a mixture of both controlled elastic flows and uncontrolled real-time flows. In this paper, we study the effects of marking elasticity (which characterizes how aggressively the marking function responds to congestion) on queue overflow probability for uncontrolled real-time flows. First, we derive lower and upper bounds on the queue overflow probability at a router of a single bottleneck system. Using this, we quantify the trade-off between stability for controlled flows and queue overflow probability for uncontrolled real-time flows as a function of marking elasticity. Next, we compare the capacity required at a router with only FIFO scheduling versus a router with priority scheduling (priority given to the real-time flows) for supporting a given queue overflow probability. We quantify the "scheduling-gain" of priority scheduling over FIFO scheduling, as a function of marking elasticity. We show that this scheduling gain decreases with more elastic marking functions. [ABSTRACT FROM AUTHOR]

In this paper, we consider queue-length stability in wireless networks under a general class of arrival processes that only requires that the empirical average converges to the actual average polynomially fast. We present a scheduling policy, sequential maximal scheduling, and use novel proof techniques to show that it attains 2/3 of the maximum stability region in tree-graphs under primary interference constraints, for all such arrival processes. For degree bounded networks, the computation time of the policy varies as the the logarithm of the network size. Our results are a significant improvement over previous results that attain only 1/2 of the maximum throughput region even for graphs that have a simple path topology, in similar computation time under stronger (i.e., Markovian) assumptions on the arrival process. [ABSTRACT FROM AUTHOR]

The article reports on the developments of mobile point of sale (POS) space centers. One major development of mobile POS space centers is the establishment of line-or queue-busting solutions which allow customers' purchase to be scanned and paid before reaching the checkout counter. They have evolved to become an important part of a retailers' technology expectations. They provide added functionality through wireless applications which can be set up anywhere inside or outside a store. Other developments in mobile POs space centers are the creation of PreScan queue-busting software from Datalogic and Mobile POS Solution Suite from Hypercom.

Abstract-From multi-description/multi-path routing for multi-media applications to content distribution in P2P networks, to community networking, many forms of resource sharing have been proposed to improve network performance. From the perspective of any single user, when ignoring the interaction among users, all such schemes reduce to various forms of providing parallelism and, hence, increased throughput. Focusing on parallelism is by no means sufficient as it ignores the existence of many users with potentially similar strategies. In this paper, we focus instead on the delay performance of a multi-user system where resources are shared. We illustrate the benefit, in an average delay sense, of resource sharing among many (potentially strategic) users via a multiqueue multi-server problem. We use a fork.join queuing model to provide analytical results in a special case of homogeneous users and servers. Our proposed model is simplistic, and yet, it does capture the trade-off between parallelism, traffic load increase, and reassembly/synchronization delay to a large extent. Furthermore, we prove the robustness of a certain locally optimal strategy to non-cooperation in a Nash equilibrium sense. [ABSTRACT FROM AUTHOR]

Processor-sharing queues are often used to model file transmission in networks. While sojourn time is a common performance metric in the queueing literature, average transmission rate is the more commonly discussed metric in the networking literature. Whereas much is known about sojourn times, there is little known about the average service rate experienced by jobs in processor-sharing queues. We focus here upon performance requirements in the form of an upper bound on the probability of failing to achieve a specified minimum transmission rate or a specified minimum average rate. For an M/G/1 processor-sharing queue, we give a closed-form expression for this violation probability. We derive closed-form expressions for the marginal service rate with respect to the violation probability and to the minimum transmission rate, and characterize when each is binding. We then consider the effect of using connection access control by modeling an M/G/1/K processor-sharing queue, and discuss the relationship between queue service rate, queue limit, violation probability, and blocking probability. Finally, we consider a two-class discriminatory processor-sharing queue, and discuss what combinations of class weighting and service rate can be used to achieve specified minimum rate violation probabilities for both classes. [ABSTRACT FROM AUTHOR]

We consider a class of queueing networks referred to as "generalized constrained queueing networks" which form the basis of several different communication networks and information systems. These networks consist of a collection of queues such that only certain sets of queues can be concurrently served. Whenever a queue is served, the system receives a certain reward. Different rewards are obtained for serving different queues, and furthermore, the reward obtained for serving a queue depends on the set of concurrently served queues. We demonstrate that the dependence of the rewards on the schedules alter fundamental relations between performance metrics like throughput and stability. Specifically, maximizing the throughput is no longer equivalent to maximizing the stability region; we therefore need to maximize one subject to certain constraints on the other. Since stability is critical for bounding packet delays and buffer overflow, we focus on maximizing the throughput subject to stabilizing the system. We design provably optimal scheduling strategies that attain this goal by scheduling the queues for service based on the queue lengths and the rewards provided by different selections. The proposed scheduling strategies are however computationally complex. We subsequently develop techniques to reduce the complexity and yet attain the same throughput and stability region. We demonstrate that our framework is general enough to accommodate random rewards and random scheduling constraints. [ABSTRACT FROM AUTHOR]