Performance Evaluation Of Wireless Networks Research Articles

An IEEE Standard for Industrial Wireless Performance Evaluation

Adoption of wireless systems for use in industrial scenarios is increasing, although slowly, in process control and discrete manufacturing. In particular, factories must make the leap towards wireless networks as a central form of communications to enable certain capabilities out-lined by Industry 4.0. Acceptance of wireless as a principal communications mode is slowed by the fact that it is indeed less reliable and less deterministic than its wired counterparts. The industrial wireless medium is susceptible to interference and multi-path fading effects, and their impacts are exacerbated by the mission critical nature of the attached sensing and control applications. Adoption of wireless networks can be made more acceptable if the uncertainty of the wireless medium is better understood and wireless devices are designed to accommodate such uncertainty. This can be achieved through analysis of the RF environment beyond its propagation characteristics and the standardized evaluation of wireless network performance prior to deployment. This article describes the ongoing approach taken by the IEEE P1451.5p working group for the standardization of industrial wireless network performance evaluation. A strategy for modeling channel degradation factors (aggressors) and perspectives on profiling the model for replication of different radio environment scenarios are presented.

Engineering Financial Performance Evaluation of Wireless Network Based on Intelligent Neural Network Model

Under the global economy, enterprises in the financial industry are facing plenty of opportunities and severe challenges. Aimed at providing a reference enterprise performance evaluation system for related enterprises, the proposed model helps enterprises to learn and sort out their own performance evaluation system according to this structure. A prediction model of BP neural network (BPNN) based on the wireless network is studied as the performance data prediction algorithm. Firstly, the feasibility of this algorithm is analysed through prediction training. Secondly, the proposed neural network algorithm is compared with the traditional algorithm for data prediction. It turns out that this neural network prediction algorithm based on wireless communication is not only universal to the prediction data but also superior to the traditional prediction algorithm in both error gap and relative average error compared with other traditional algorithms. On this basis, the particle swarm optimization (PSO) algorithm is also used to evaluate the performance indicators of three enterprises, and accurate numerical values are obtained to express the corresponding results. Therefore, it is concluded that the subalgorithm can be applied to the enterprise performance evaluation team in the financial industry.

A Network Evaluation Algorithm in Heterogeneous Wireless Networks

Network reliability analyses have received much attention in heterogeneous wireless network performance evaluation during the last few years. In this paper, a method for heterogeneous wireless network reliability evaluation to meet the required levels of heterogeneous wireless network differences of various graph-theoretic connectivity measures is proposed. A concept of heterogeneous wireless network reliability degree is proposed and a heterogeneous wireless network reliability entropy-based method for analyzing the proposed reliability measure is discussed. This method is based on heterogeneous wireless network survivability and stability analyses. Its core is the computation of some heterogeneous wireless network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of heterogeneous wireless network reliability. We illustrate how a new approach to assessing the performance of in heterogeneous wireless networks. Our results also illustrate how the characteristics of the heterogeneous wireless networks may affect the performance of the different measures. We also present some simulation results.

New strategies for planning and performance evaluation of wireless networks: case studies based on the cross-layer approach

The use of wireless local area networks, called WLANs, as well as the proliferation of the use of multimedia applications have grown rapidly in recent years. Some factors affect the quality of service (QoS) received by the user and interference is one of them. This work presents strategies for planning and performance evaluation through an empirical study of the QoS parameters of a voice over Internet Protocol (VoIP) application in an interference network, as well as the relevance in the design of wireless networks to determine the coverage area of an access point, taking into account several parameters such as power, jitter, packet loss, delay, and PMOS. Another strategy is based on a hybrid approach that considers measuring and Bayesian inference applied to wireless networks, taking into consideration QoS parameters. The models take into account a cross layer vision of networks, correlating aspects of the physical environment, on the signal propagation (power or distance) with aspects of VoIP applications (e.g., jitter and packet loss). Case studies were carried out for two indoor environments and two outdoor environments, one of them displaying main characteristics of the Amazon region (e.g., densely arboreous environments). This last test bed was carried out in a real system because the Government of the State of Para has a digital inclusion program called NAVEGAPARA.

Flow-level performance and capacity of wireless networks with user mobility

The performance evaluation of wireless networks is severely complicated by the specific features of radio communication, such as highly variable channel conditions, interference issues, and possible hand-offs among base stations. The latter elements have no natural counterparts in wireline scenarios, and create a need for novel performance models that account for the impact of these characteristics on the service rates of users. Motivated by the above issues, we review several models for characterizing the capacity and evaluating the flow-level performance of wireless networks carrying elastic data transfers. We first examine the flow-level performance and stability of a wide family of so-called α-fair channel-aware scheduling strategies. We establish that these disciplines provide maximum stability, and describe how the special case of the Proportional Fair policy gives rise to a Processor-Sharing model with a state-dependent service rate. Next we turn attention to a network of several base stations with inter-cell interference. We derive both necessary and sufficient stability conditions and construct lower and upper bounds for the flow-level performance measures. Lastly we investigate the impact of user mobility that occurs on a slow timescale and causes possible hand-offs of active sessions. We show that the mobility tends to increase the capacity region, both in the case of globally optimal scheduling and local α-fair scheduling. It is additionally demonstrated that the capacity and user throughput improve with lower values of the fairness index α.

Improving scalability of wireless network simulation with bounded inaccuracies

Discrete event network simulators have emerged as popular tools for verification and performance evaluation of wireless networks. Nevertheless, the desire to model such networks at high fidelity implies high computational costs, limiting most researchers the ability to simulate networks with thousands of nodes. Previous attempts to optimize simulation of large-scale wireless networks have not appropriately modeled accumulation of weak interference, thereby suffering inaccuracies that may be further magnified in the evaluation of upper-layer protocols. This article presents a comprehensive analysis on the effects of common optimization techniques for large-scale wireless network simulation on the overall network performance. Based on the analysis, it formulates distance limit derivation and mobility update reduction that introduce bounded inaccuracy to the radio propagation simulation. It further proposes a novel technique, Lazy Event Scheduling with Corrective Retrospection, that reduces simulation events twenty-five fold without introducing any inaccuracy at all. The experimental results show that these optimizations can substantially improve the runtime performance of an already efficient wireless network simulator, by a factor of up to 55 for wireless networks with 3200 nodes without compromising the simulation's accuracy.

Performance Evaluation of Wireless Networks

Performance Evaluation of Wireless Networks

Special section: topics in performance evaluation of wireless networks

Special section: topics in performance evaluation of wireless networks

Special issue: performance evaluation of wireless networks

Special issue: performance evaluation of wireless networks

Iterative Algorithms for Performance Evaluation of Wireless Networks with Guard Channels

Analytical and modeling work performed since the late eighties have led to nonlinear equations that relate important parameters used for performance evaluation of wireless networks. These nonlinear equations have no closed-form solution and iterative algorithms are used to find numerical solutions. However, iterative algorithms that are not designed to detect and overcome nonconvergence situations may fail to converge. We present an iterative algorithm that numerically solves six dependent nonlinear equations. The algorithm always converges and obtains values of blocking probability, pb, and forced termination probability, pft, at any desired level of accuracy. We then used this algorithm to numerically show that for a given pair of values of pb and pft, there is an optimal number of guard channels that supports a maximal new-call arrival rate.