A Simulation Study Of The Performance Of Cluster-Based Multiprocessor Systems

A cluster-based multiprocessor system that was introduced and analyzed by D. Agrawal and I. Mahgoub (1985, 1987) is considered. The analysis was based on an approximate analytical model, and the results were compared with those obtained for the crossbar and multiple-bus systems using the same model. A simulation model that relaxes two unrealistic assumptions of the approximate analytical model used by Agrawal and Mahgoub is developed here. The results obtained from the simulation model are compared with those obtained from the approximate analytical model for the cluster-based, crossbar, and multiple-bus systems. The simulation results confirm the conclusions arrived at in the previous studies.

Approximate performance/cost analysis of m-level hierarchical multiprocessor systems

A production line is an important class of manufacturing system when large quantities of identical or similar products are to be produced. The performance of a production line is highly influenced by machine failures. When a machine fails, it is then be unavailable during a certain amount of time required to repair it. Analysis of production lines divides into three types: analytical, approximation and simulation models. The analytical and approximation models have assumptions, which make these models unrealistic such as reliable workstations, certain processing distribution, the first workstation cannot be starved and the last workstation cannot be blocked. The main problems in production lines treatment are the calculation of throughput and average levels of buffers because of the great size of state space. An analytical model is reviewed to clarify the limitations to use such treatment in real production lines. Simulation modeling of production lines is considered very important for designers interested in: Workload Allocation Problem (WAP), Server Allocation Problem (SAP), and Buffer Allocation Problem (BAP). This paper studies and analyzes the performance keys, which effect on production lines. A simulation model is developed by using ARENA software and used to analyze and test several bottlenecks that are causing severe congestions in different areas on the production line and could resolve all of these bottlenecks. In this paper, an actual cement production line is used as a case study. After a simulation time of 13 days, a simulation results show the line bottlenecks, workstations utilization, buffer capacities and the line production rate. The outputs clarify redesign of allocation of buffers, which verify an optimum size could be made; it might be taken into consideration when designers implement such lines. Finally modified better workstations utilization, buffer capacities and the line production rate with an increase about 15% of the production rate and economizing of 37 % from buffer capacities

While edge computing has the potential to offer low-latency services and overcome the limitations of traditional cloud computing, it presents new challenges in terms of trust, security, and privacy (TSP) in IoT environments. Cooperative edge computing (CEC) has emerged as a solution to address these challenges through resource sharing among edge nodes. However, for multi-infrastructure providers, incentive and trust mechanisms among edge nodes are crucial technical issues that must be addressed alongside system latency and reliability to meet performance requirements. In this paper, we propose a blockchain-assisted intelligent edge cooperation system (BIECS) to systematically solve these issues. By leveraging blockchain technology, we construct trust among edge nodes and employ an incentive mechanism for resource sharing among multi-infrastructure providers. We formulate the system performance optimization as a multi-objective joint optimization problem and solve it efficiently through a two-stage strategy for selecting edge nodes. We first design an improved Long Short Term Memory (LSTM) model for resource prediction and then select edge nodes for executing offloaded tasks and handling the corresponding blockchain process related to each task execution. To evaluate the performance of BIECS, we implement the system based on Hyperledger Fabric and design extensive experiments. Our proposed system achieves better performance in terms of system delay, throughput, and resource utilization compared to state-of-the-art schemes for edge cooperation.

The WiMAX system outlines support for quality of service (QoS) through several service classes differentiation. However, no specific scheduling has been defined to carry the task. In this paper, we propose a simple and standard-compliant scheduling algorithm for downlink and uplink connections. The proposed algorithm calculates and grants the needed resources in terms of slots based on the QoS requirements and the priority of the service classes. The simulation results show that the scheduling algorithm has fulfilled the QoS provisions of all service classes of WiMAX system in terms of delay and throughput requirements.

As a promising solution for future indoor access networks, resource allocation in Visible light communication or LiFi networks is subject to lots of researches. An interesting approach for network algorithm design is to use some knowledge about the future of the network. With this regards, the anticipatory design may improve the performance of the system in terms of delay and throughput. This paper reviews the state-of-the-art anticipatory algorithms proposed in the literature, given different prediction capabilities. The key element that all of these algorithms share is to find an event that correlates the current actions to the performance of the network in the future. Apart from the amount of possible prediction, two main approaches have been proposed for problem formulation. The optimal anticipatory resource allocation problem can be formulated in terms of a T-step look-ahead optimization problem. This approach requires more accurate information about the future of the network and yields higher performance improvements. The objective function can be adjusted to achieve high fairness and throughput or low latency in the system. On the other hand, the resource allocation algorithm can be expressed as a matching problem on a bipartite graph. The partial knowledge of the future can be added to the problem using proper heuristic preference functions.

Motion detection is a fundamental process that essentially detects a change in the position of an object with respect to its surrounding environment. It is highly demanding in various applications such as health care, defense and surveillance. The existing solutions for motion detection in indoor application are complex and expensive as it requires high end cameras and sensors. Hence, the objective of this paper is to provide an alternative cost effective solution. In the proposed motion detection system, Passive Infra Red (PIR) sensors are used to detect the presence of motion. The control unit of the PIR sensor transmits the trigger interrupt to the control unit of the camera via ZigBee communication. The rotational element present in the camera control unit rotates the camera in line of sight with the PIR sensor. The detected motion is then captured by the camera sensor and stored in Raspberry Pi, a microcontroller, which is then wirelessly transmitted to the receiver for further processing. The proposed motion detection system has been developed and validated in real time. It is observed that the performance of the developed system in terms of delay and QoS are acceptable for single event detection. However the proposed system can be extended for detection of multiple events.

The integration of fog computing technology into the IoT-enabled systems is expected to improve the computing performance of system in terms of delay through task offloading mechanisms. However, to gain such a benefit, the schemes must consider many factors including the heterogeneity nature of fog computing environment, a variety of task requirements and characteristics. In some scenarios, many of single fogs cannot process heavy tasks due to lack of available resources or limited computing capabilities. Meanwhile, fogs with richer resources may have long queues of waiting tasks, thus probably increasing the overall delay of task execution. This paper proposes to use a task splitting to cope with the issues and investigate this impact on the delay of task offloading.

Simulation studies for Web systems have been carried out by many academic researchers and practitioners. Models are often less time-consuming to develop and run production system. Performance Engineering is done to determine the system performance. In the paper various performance models of Cluster-based Web Systems are discussed, as well as their influence on response time. The Queueing Petri Nets simulations are based on different loads, but also on changing environmental parameters and system structures. A novelty in this approach is the use of two client-classes related to customer behavior and routes in the system. In all cases Web system architectures include clusters are taken into consideration. Simulation results obtained from this models are compared with data from a real system and show good accuracy.

This chapter presents a new approach to on-line decision support systems that is scalable, fast, and capable of analysing even up-to-date data. It is based on a database cluster: a cluster of commercial off-the-shelf computers as hardware infrastructure and off-the-shelf database management systems as transactional storage managers. We focus on central architectural issues and on the performance implications of such a cluster-based decision support system. In the first half, we present a scalable infrastructure and discuss physical data design alternatives for cluster-based on-line decision support systems. In the second half of the chapter, we discuss query routing algorithms and freshness-aware scheduling. This protocol enables users to seamlessly decide how fresh the data analysed should be by allowing for different degrees of freshness of the OLAP nodes. In particular it becomes then possible to trade freshness of data for query performance.

In this paper we present a new analytical model for cluster-based parallel systems based on Multi-Chain Open Queuing Network. The proposed model is general enough in terms of node design and clustering which can be extended to any parallel system. To have a good estimation of the model parameters, a benchmark suite has been applied to a real system and parameters calibration is performed based on actual measurements. In this study the hypercube topology was chosen for the interconnection network of the system. We present an analytical modeling and validate it by simulation. The QNAT is used for analytical modeling and the OMNet++ simulator has been used to carry out the simulations. Comparison of simulation and analytical results verifies validity of the model. System workload in simulations is generated using both analytical and experimental distributions and a close match with analytical results in both cases is observed.

Analytical water quality model for biochemical oxygen demand simulation in River Gomti of Ganga Basin, India

In this paper authors propose the approach for investigation of photonic switches performance metrics in modern all-optical networks. The approach includes photonic switches analytical and simulation modeling. The analytical model of the $$4\times 4$$ -photonic switch is based on the M/M/1/4 queuing model using so-called probability translation matrix method that allows to investigate functioning of the system in transient mode. The analytical expressions of such performance metrics as a loss probability, a buffer size and a transient time are obtained. A comparison of analytical and simulation modeling results was carried out. The analysis show that the steady-state loss probability obtained in results of analytical modeling is greater than the analogous parameter obtained in results of simulation modelling by 8%. The study of simulation models of $$4\times 4$$ and $$16\times 16$$ -photonic switches show that the buffer size of these systems does not exceed one packet. Analysis of the $$16\times 16$$ -photonic switch buffer show that the buffer size of the first cascade is four times larger than the buffer of the second cascade. The results of the investigation show that the proposed type of photonic switches can be used in the high-performance all-optical network designed to transmit information from the ground module to tethered high-altitude unmanned module and vice versa.

The interconnection network (IN) is one of the major factors which determine the performance of a multiprocessor system. It is imperative to have a model by which the efficiency of the IN can be correctly evaluated. This paper presents an m–level HMPMB multiprocessor system and analyses its bandwidth performance. Two models are developed for the hierarchically equally likely case and favourite case, respectively. They show that the m–level HMPMB multiprocessor system performs well and is fairly close to a typical memory–oriented partial multiple bus system (MPMB) for high rates of favourite requests.

Compositional Simulation of Well Performance for Fractured and Multiple Fractured Horizontal Wells in Stratified Gas Condensate Reservoirs. Introduction The work for this paper has been carried out to improve development concepts in gas condensate reservoirs in the North Sea. While early North Sea oil fields were characterized by very large dimensions, thick homogeneous layers, and high permeabilities, newer discoveries have not been as blessed. Fields in the Haltenbanken area, such as Asgard have large extensions and reserves, but are found in deeper water and deep formations, characterized by hot reservoir temperatures of more than 300 degrees Fahrenheit, pressures from 7,500 to 13,000 psi, and most importantly, in heterogeneous, low permeable rocks. The need to make these high cost discoveries economic and accurate prediction of reservoir performance is more important than ever. In this context, the application of advanced well technologies such as multi-laterals and hydraulic fracturing takes on more significance. The primary advantages of fracturing are increasing productivity from low permeable rocks and improving the connectivity of the well in stratified formations (Abou-Sayed et. al. (1)). In gas condensate reservoirs, however, fracturing has additional advantages: stimulation reduces pressure drawdown and thus leads to less liquid dropout. Non-Darcy effects are minimized and the well will suffer less productivity reduction once liquid blocking occurs (Setari et. al. (2)). Simulation models developed for these applications differ from conventional approaches. The correct representation of geological features is normally the main gridding criterion. In fractured well simulation, however, the size and aspect ratio of the grid cells have a strong influence in predicting the flow behavior for different well types, fluid compositions, and recovery processes correctly. The goal of this paper is to determine practical simulation guidelines in modeling fractured well productivity in gas condensate fields. Analytical Methods Several analytical methods are available to predict the productivity and performance for vertical fractured wells. New models for horizontal wells have been developed by Babu/Odeh and Joshi, and for multiple fracture wells by Babu, Horne and Temeng, and others. Some of them have now the capability to model stratified reservoirs. The complex equations in these methods can be handled easily with the new faster PCs. Programs such as MEPFRAC/HYFRAC, a Mobil internal analytical software, can predict the productivity in time of multiple fractured wells with different fracture sizes in a stratified reservoir in only a few minutes. Unfortunately, different analytical models were found to have individual restrictions. One limitation of all analytical models is in the definition of fluids because they permit only one set of PVT data and no compositional modeling at all. Therefore, most of the methods are only highly accurate for dry gas or almost incompressible fluids but cannot model gas condensate characteristics. In most cases, simulation and analytical model results agree only during certain flow periods depending on the assumptions used in the analytical model. Another limitation is that either uniform flux or infinite conductivity descriptions are applied in the individual methods. After comparing the benefits of a number of analytical models with simulation results, our conclusion is that no analytical method is available to predict fractured well productivity reductions due to liquid effects in gas-condensate systems with sufficient detail. The only complete tool to predict this is fully-compositional simulation. Even a black oil representation is inadequate when finely-gridded models are used, since incorrect predictions result if improper fluid models are selected. See Coats and Hwang. Simulation of Fractured Wells in Coarse-Grid Gas Condensate Models Fracture representation in coarse simulation models depends on the selection of well productivity corrections derived from analytical techniques or locally fine gridded simulations. The necessary correction depends upon the timeframe, or flow regime, which needs to be treated most accurately. Figure 1 illustrates the timeframes and flow regimes for one example and the drainage patterns along fractures for infinite flow and uniform-pressure fracture systems. The flow periods begin with linear flow in the fracture and progress to pseudo-radial flow as the drainage area increases. P. 175