Performance and dependability analysis of fault-tolerant networks

A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.

Stochastic Geometry has attained massive growth in modelling and analysing of wireless network. This suits well for analysing the performance of large scale wireless network with random topologies. Analytical framework is established to evaluate the performance of the network. Here we have created a mathematical model for uplink analysis and the gain of uplink and downlink is obtained. Then ad-hoc network architecture is designed and the performance of the network is compared with the traditional method. Finally, a new scheduling algorithm is developed for cellular network and the gain parameter is quantified with the help of Stochastic Geometry tool. The accuracy is acquired from extensive Monte Carlo simulator.

Analysis of network and application performance is traditionally based on mathematical models derived from first principles. Such models are usually complex, difficult to use, and do not exhibit satisfactory accuracy. This paper describes a new way of achieving high accuracy in predicting network performance. The new solution is built on a unique combination of network-component models and probabilistic analysis. The resulting model-based approach provides high fidelity for decision making in both monitoring and prediction modes. This paper discusses key features of the technique and illustrative results. Resulting capabilities are implemented in a system called NetPredictor/sup TM/, which can monitor and predict quality of service (QoS) and compliance with service-level agreements (SLAs). It also empowers users to perform service-level management (SLM) and to make informed decisions about effects of contemplated changes in a network. Networks can be combinations of LANs, WANs, intranets, and the Internet.

Fiber Distributed Data Interface (FDDI) networks offer a standardized, high-speed interconnection between components in a distributed computer system. Extensive research has been conducted on the performance of FDDI networks consisting of hundreds of stations distributed over an area of several hundred square meters. This paper extends the prior work to the case of small networks; for example 10 stations distributed around a single room laboratory. The characteristics for these smaller networks differ in some instances from the behavior of larger networks - these differences can be significant in applications where high performance is demanded from a small FDDI based network.

The ever-increasing number of customers and the need for higher data rates and multimedia services require the deployment of Small Cell Networks. In this paper, we propose a new computational approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels, using the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and channels allocation in as small cell, without generating nor storing the reachability set. In addition, we develop the formulas of the main stationary reliability and performance indices as a function of the network parameters, the stationary probabilities and independently of the reachability set markings.

This thesis provides a detailed analysis of the effects of TCP and UDP traffic over a LAN and WAN medium. In addition, it also analyses some real time applications like audio, video and web browsing that is affected by TCP traffic while sharing a bottleneck node and/or link resources. As network industry is growing continuously, the network administrator should be aware of TCP and UDP traffic that is traversing through their network. The analysis and monitoring of the traffic is crucial as it directly affects the performance of the network. Finding a cause for the poor performance of the network is quite important because it gives an idea to troubleshoot and resolve the issues effectively. In this thesis, we have created topologies using Cisco’s Virtual Internet Routing Lab (VIRL) [7]. They replicate an organizational infrastructure with client-server environment in LAN and WAN. Routing protocols such as OSPF and BGP are used to mimic the real world internet. A built-in LXC-iperf tool is used to generate the TCP and UDP traffic. During the generation of the traffic, various parameters are changed or controlled to see their effect on the network performance. As a learning and informative research, this thesis considers several Quality of Service (QoS) parameters that characterize the performance of an overall network. In particular, this thesis obtains packet loss, throughput, and jitter as QoS parameters when the resource has both TCP and UDP traffics simultaneously. We have examined, the effects on (i) TCP throughput and packet loss and (ii) UPD packet loss and jitter of (a) real time audio, (b) video, and (c) web browsing applications. These parameters examine how the traffic be manipulated to keep minimum packet loss, minimum jitter and maximum throughput. It is needless to say that all are competing with each other (TCP/UDP traffic) for sharing bottleneck resources. We have used a sample time of 15 seconds for each of our experimental results presented in this thesis. Our analysis shows that the best performance of the real time video and audio application is obtained when we select large size packet but its size being less than MTU of the link (without reducing the data rates). Similarly, in case of web browsing, we notice that throughput increases by increasing the window size and decreasing the latency. Efficient outcomes with the traffic analysis are achieved only if the experiments are carried out with adequate amount of attention.

Technologies such as microservices, containerization and Kubernetes in cloud-native environments make large-scale application delivery easier and easier, but problem troubleshooting and fault location in the face of massive applications is becoming more and more complex. Currently, the data collected by the mainstream monitoring technologies based on sampling is difficult to cover all anomalies, and the kernel's lack of observability also makes it difficult to monitor more detailed data in container environments such as the Kuber-netes platform. In addition, most of the current technology solutions use tracing and application performance monitoring tools (APMs), but these technologies limit the language used by the application and need to be invasive into the application code, many scenarios require more general network performance detection diagnostic methods that do not invade the user application. In this paper, we propose to introduce network monitoring at the kernel level below the application for the Kubernetes cluster in Alibaba container service. By nonintrusive collection of user application L7/L4 layer network protocol interaction information based on eBPF, data collection of more than 10M throughputs per second can be achieved without modifying any kernel and application code, while the impact on the system application is less than 1%. It also uses machine learning methods to analyze and diagnose application network performance and problems, analyze network performance bottlenecks and locate specific instance information for different applications, and realize protocol-independent network performance problem location and analysis.

Phased mission modelling of systems with maintenance-free operating periods using simulated Petri nets

This study focuses on performance analysis and optimization of enterprise wireless networks. Fundamental performance parameters of Wi-Fi networks such as signal strength, signal-to-noise ratio (SNR), data rate, and channel interference were evaluated in detail in the study. The analysis process was carried out using Ekahau AI Pro software and Ekahau Sidekick device in a corporate facility, consisting of three main buildings. The obtained data revealed that signal strength dropped to -85 dBm levels in certain areas, negatively affecting the network's coverage area. Particularly in the ground floor of building B-C, secondary signal levels were found to be insufficient for roaming. Across the campus, SNR levels were observed to be 30 dB and above, and these values were found to provide ideal connectivity. During the analysis, it was discovered that in some areas, the number of access points broadcasting signals on the same channel increased up to 6. It has been assessed that this situation may negatively affect network performance in areas where interference is intense. Data rates varied between 1 - 300 Mbps in the 2.4 GHz frequency band and 1 - 585 Mbps in the 5 GHz band. The study provides significant data for performance analysis and optimization of enterprise wireless networks.

Analytical modeling techniques can be used to study the performance of optical multistage interconnection network (OMIN) effectively. MINs have assumed importance in recent times, because of their cost-effectiveness. An N/spl times/N MIN consists of a mapping from N processors to N memories, with log/sub 2/N stages of 2/spl times/2 switches with N/2 switches per stage. The interest is on the study of the performance of unbuffered optical multistage interconnection network using the Banyan network. The uniform reference model approach is assumed for the purpose of analysis. In this paper we apply the analytical modeling approach on an N/spl times/N OMIN with limited crosstalk (conflicts between messages) unto (log/sub 2/N-1). Messages with switch conflicts satisfying the constraint of (log/sub 2/N-1) are allowed to pass in the same group, but in case of a link conflict, than that message is routed in a different group. The analysis is performed by calculating the bandwidth of the network operating under a load l and allowing random traffic and using a greedy routing strategy. A number of equations are derived using the theory of probability and the performance curves are plotted. The results obtained show that the performance of the network improves by allowing limited crosstalk in the network.

In order to satisfy the requirement of extremely high data rate in traffic hotspot regions, millimeter wave (mmWave) has attracted significant attention in wireless communication networks. While the coverage performance of mmWave networks based on the distribution of signal-to-interference-plus-noise ratio (SINR) has been widely studied, it provides only very limited information on the link reliability. In this paper, we provide a fine-grained performance analysis of the mmWave networks with hotspots. Specifically, we first establish a general and tractable framework to investigate the performance of mmWave networks using the Poisson cluster process integrated with several features of the mmWave band. Both open and closed association strategies are considered. To show what fraction of users in the networks achieves target reliability when the SINR is given, we derive the tier association probability and the moments of the conditional SINR distribution, based on which the exact meta distributions of SINR are given. Interestingly, in clustered mmWave networks, the widely used standard and generalized beta approximations do not work well when the blockage effect is severe. To resolve this issue, we provide a modified approximation by scaling the standard beta distribution, which is shown to be closer to the exact results. We conduct extensive simulations to study the impact of mmWave and deployment features on the performance of clustered mmWave networks. Numerical results reveal that the optimal scattering variance of mmWave base stations scales with the cluster size to maximize the number of concurrent reliable links, and increasing the antenna directivity results in more reliable communications than elevating the transmit power of mmWave base stations.

In this paper, we discuss the phase change flow of network and the change law of the network performance under different traffic input rates. Based on the stability conditions of the and the system, the approximate expressions of the phase change flow of the network traffic are We also derive the analytical results of the queue length, average delay, network throughput and performance indicators and the deviation degree of the network behavior on the stability of the network behavior. At the same time, we carry out the simulation of the data according to the actual situation, and the simulation results show that (1) The global behavior of heterogeneous network heterogeneous topology has local characteristics from the free flow regime to the congestion state. It is a feasible method to improve the network performance by transforming the network topology improve the value of the network traffic flow. (3) As the network load increases, the global behavior of the network is directly from the free flow state to the global congestion state. There is no state between the two states. (4) When the flow rate exceeds the global phase transition, the queue length and the average delay of the packet are increased dramatically, and the maximum value of network throughput is quickly reduced to zero.

We propose a general design technique for high-performance fault-tolerant networks in multiprocessor systems. The proposed technique called extra link multistage interconnection network (ELMIN) can distribute the load evenly and tolerate faults by providing maximal independent paths at the expense of some additional hardware (extra links), which is much smaller than most of the networks proposed earlier. In this paper, the technique is applied to some specific networks, i.e., the CIN (cube interconnection network) and the d-dilated CIN, to show how to maximize the number of redundant paths. The routing algorithms for the ELMIN have the same simplicity as that of the original MIN. We analyze the performance of the proposed networks and also simulate them along with several others under the buffered and unbuffered packet switching environment. Both analysis and simulation show the high performance of the proposed networks without regard to the presence of faults.

To deal with challenges of enhanced user density, high data rate demand and coverage, conventional macro cellular network architecture is evolving to irregular and complex Heterogeneous Networks (HetNets) through dense deployment of low power Base Stations (BSs) such as pico and femto BSs. Various parameters and their effects are considered while analyzing the performance of HetNets. In this paper we investigate the impact of macro and pico BSs separation on the network performance. We consider picocell within the association region of a macrocell and investigate the association region of picocell, average rate, and Energy Efficiency (EE) of the network. The results show that network performance is improved with increase in macro and pico BSs separation within the association region of a macrocell.

A new analytical model is proposed to investigate the delay and throughput in cognitive mesh networks. The validity of the model is demonstrated via extensive simulation experiments. The model is then used to evaluate the effects of the number of licensed channels and channel utilisation on the network performance.