Performance Modelling and Analysis of Cognitive Mesh Networks

This paper extends previous research efforts related to the simulation performance modelling and analysis of satellite communication networks. Specifically, the use of low earth orbit (LEO) satellite networks for personal communications is examined. Six different satellite constellation configurations are investigated in a packet-switched operating environment. Performance metrics examined are the end-to-end packet delay and the utilization of satellite channels in the dynamic environment. Realistic and accurate models of the physical satellite network and its terrestrial transmitters require that numerous operating characteristics and assumptions be specified. These are based on proposed design requirements of commercial systems, such as Iridium. Via the use of simulation, we show the relative delay and utilization performance of differing satellite network architectures. From these simulation models, mathematical metamodels are derived for the system delays. These innovative models are used to predict the delay performance of different network architectures not previously simulated. Comparison of these metamodels with simulation results show that metamodels provide an accurate means for performance prediction. Copyright © 1999 John Wiley & Sons, Ltd.

The CPqD Cognitive Mesh Network (CCMN) has been developed with traditional cognition elements, such as energy detection based sensing and with the ability to switch the data channel to take advantage of any available channels on a given radio-electric spectrum band. Many of the solutions that utilize cognitive mesh networks are based on the fact that it uses a common control channel (CCC) to manage the system. Therefore the Multi-Channel - One Interface Manager (MC-OIM) alg orithm was developed to maximize channel usage with a system that does not depend of any CCC . The MC-OIM algorithm was evaluated using network simulator ns-3 and simulation results were validated with testes that were done in a real scenario.

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.

The diversity of methodologies and applications in the literature for the traffic engineering, performance modelling and analysis of convergent multiservice heterogeneous networks attests to the breath and richness of recent research and developments towards the design and dimensioning of the next and future generation Internets. Heterogeneous Networks: Traffic Engineering, Performance Evaluation Studies and Tools describes recent advances in networks of diverse technology reflecting the state-of-the-art technology and research achievements in traffic engineering, performance evaluation studies and tools worldwide. Technical topics presented in the book include: Traffic Modelling and Characterisation Queueing and Interconnection Networks Performance Evaluation Studies TCP Performance Analysis Congestion Control Application Layer Multicast Numerical and Software Tools; This book contains recently extended research papers, which have their roots in the series of the HET-NETs International Working Conferences focusing on the Performance Modelling and Evaluation of Heterogeneous Networks under the auspices of the EU Networks of Excellence Euro-NGI and Euro-FGI. Heterogeneous Networks: Traffic Engineering, Performance Evaluation Studies and Tools is ideal for personnel in computer/communication industries as well as academic staff and master/research students in computer science, operational research, electrical engineering and telecommunication systems and the Internet. CACHE_VSTAMP

The last decade has seen a phenomenal increase in the use of electronic components in automotive systems, resulting in the replacement of purely mechanical or hydraulic-implementations of different functionalities. Today, in high-end cars, it is common to have around 70 electronic control units (ECUs), each consisting of programmable processors, one or more microcontrollers and a set of sensors and actuators. Different functionalities (e.g. adaptive cruise control or anti-lock braking) are then implemented in a distributed fashion with parts of a task being mapped onto one or more ECUs and these ECUs exchanging messages and signals via high-speed communication buses. The heterogeneity and the distributed nature of these implementations, coupled with the emergence of new standards and protocols for the automotive domain have given rise to new challenges - both in terms of programming large-scale ECU networks, as well as in evaluating their performance and timing properties. This tutorial will provide a comprehensive overview of the recent developments in this domain and also highlight some of the challenges facing embedded systems designers and programmers. The topics covered will include time-triggered architectures for implementing safety-critical applications, emerging protocols for the automotive domain such as FlexRay, techniques for performance and timing analysis of FlexRay-based ECU networks, and languages and tools for developing distributed implementations of automotive functionality around FlexRay and other related protocols. Apart from discussing the relevant protocols, languages and modelling/analysis techniques, the tutorial will also cover practical case studies and some commercially available tools and their functionality.

Performance modeling and analysis of computer systems and networks

Performance Modeling and Analysis of WDM Optical Networks under Wavelength Continuity Constraint using MILP

In cognitive radio networks (CRNs), spectrum handoff probability and expected number of spectrum handoffs are important parameters in the evaluation of network performance and design. This paper presents an analytical model for spectrum handoff probability and spectrum handoff rate for CRNs under general distribution of call holding time of secondary users (SUs). The standardized analytical forms of spectrum handoff probability and handoff rate of secondary network under negotiated scenario are derived for a complete service call duration. The effect of mobility parameters: departure rate of SUs ($$\upmu )$$μ) and departure rate of spectrum holes ($$\uplambda )$$ź) on spectrum handoff are also reported in this paper. Extensive results for all the proposed analytical models are obtained and presented in this paper. Analytical results show that exponential and Erlangian distribution functions are not suitable for call holding time of SU in the analysis of spectrum handoff in CRNs. Moreover, the superiority of lognormal distribution function ascertains its use for call holding time of SU in spectrum handoff estimation for better CRN performances. The Monte-Carlo simulation is also performed for spectrum handoff probability to validate the analytical model.

Full-duplex transmission can be easily implemented on a visible light communication (VLC) link. In this paper, we investigate the performance of a VLC network with full-duplex optical links. We propose two contention protocols, named U-ALOHA and FD-CSMA, to utilize the full-duplex capability effectively. Their performances in terms of channel utilization and network throughput are analyzed and simulated and compared with a protocol with half-duplex links. The results show that the proposed protocols can effectively exploit the full-duplex capability. U-ALOHA achieves high channel utilization on the downlink channel while FD-CSMA has good performance on both downlink and uplink channels. Both of them outperform the protocol with half-duplex links when the traffic load is sufficiently high.

In recent years, channel-hopping-based medium access control protocols have been proposed to improve the capacity in a decentralized multichannel cognitive radio (CR) network without using extra control channels. Each CR user has to stochastically follow a default channel-hopping sequence in order to locate a channel and conduct its frame transmission. In this paper, theoretical analysis is conducted on the probability of channel availability and the average frame delay for primary users (PUs) by considering the impact caused by imperfect sensing of CR users and imperfect synchronization between the primary and CR networks. According to the proposed analytical model with realistic considerations, an optimal channel-hopping sequence (OCS) approach is designed for the CR users based on a dynamic programming technique. It is designed by exploiting the optimal load balance between channel availability and channel utilization within the delay constraints of PUs. By adopting the OCS approach, maximum aggregate throughput of CR users can be achieved while considering PU's quality-of-service (QoS) requirements. Moreover, in addition to the paired CR networks, the logical partition problem that occurs in generalized CR networks will also be addressed. This problem can severely degrade the aggregate throughput due to the decreased probability of connectivity between CR users, especially in a CR network with heavy traffic. Therefore, both wake-up successive contention (WSC) and wake-up counter-reset successive contention (WCSC) algorithms are proposed to increase the number of negotiations by both exploring the blind spot of imperfect sensing and amending the contention mechanisms between CR users. Compared to conventional channel-hopping sequences, numerical results illustrate that the proposed approaches can effectively maximize aggregate throughput for CR users under the QoS requirements of PUs.

In this paper, we propose a novel end-to-end resource management scheme for heterogeneous services in cognitive mesh networks (CMNs). Due to the highly dynamic nature of spectrum availability in cognitive radio networks (CRNs), we design a two-step approach, namely long-time route selection and periodic resource allocation. By introducing the interference cushion to resource allocation, we prevent real-time (RT) traffic from starving non-real-time (NRT) traffic. We formulate the problems of channel and power allocation for RT and NRT flows as two mixed-integer nonlinear programming (MINLP) problems which are NP-hard in general, and propose low-complexity yet efficient suboptimal algorithms to solve the formulated MINLP problems. Simulation results show the effectiveness of the proposed algorithms in terms of RT flow's mean access ratio and NRT flow's mean throughput. Also, we find that how to set interference cushion can affect the performance tradeoff between QoS provisioning for RT traffic and throughput maximization for NRT traffic.

In this paper, we present an analytical study for the performance of a two-tier primary-secondary network based on IEEE 802.11 DCF mechanism. It is assumed that multiple primary users (PUs) and secondary users (SUs) coexist in the radio environment and share a single band such that the SUs are allowed to contend only if they sense the channel idle for a certain period of time. First, we derive the PUs' medium access delay in the presence of SUs. Then, assuming an exponential packet inter-arrival time for the primary network, and using M/G/1 queue modeling, we determine the collision probability and throughput for the primary and secondary networks, as well as the PUs' average total delay including the queuing delay. Numerical along with simulation results show how the performance in the primary network, with given packet arrival rate, can be affected as functions of the sensing time, packet payload size and population size of the SUs. The findings of this work can be used effectively to study the performance of any IEEE 802.11 based primary-secondary network, such as cognitive radio networks where SUs may exploit a primary channel opportunistically based on a predefined policy, as well as to optimize the performance of distributed cognitive radio MAC protocols.

We propose a general framework for a comprehensive performance analysis of cooperative spectrum sensing (CSS) in cognitive radio (CR) networks. Specifically, we investigate the detection accuracy of a relay-based CR network over independent nonidentical Nakagami- m fading channels. Based on the probability density function (pdf) approach, we derive new exact and approximated closed-form expressions for the average detection probability and the average false alarm probability employing two diversity combining techniques, namely, the maximal ratio combining (MRC) scheme and the selection combining (SC) scheme. We also investigate the convergence rate of infinite series that appears in the derived exact closed-form expressions and propose to use a powerful acceleration algorithm that allows for the series termination with a finite number of terms. The results obtained reveal the importance of including the relaying link statistics and the combination techniques in the performance analysis of CR networks. The derived closed-form expression can be used to determine the energy threshold and the relaying power constraint that meet a given detection accuracy value over nonidentically distributed Nakagami- m fading.

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.

This paper investigates the physical layer security for a buffer-aided cooperative cognitive radio network in the presence of an eavesdropper, wherein the relay is equipped with a buffer so that it can store packets received from secondary source. Multiple primary users (PUs) locate in the transmission range of the secondary users (SUs), and quality of service (QoS) requirement of them must be guaranteed. To improve the seure performance of cognitive radio networks, we propose a novel secure link selection scheme which incorporates the instantaneous strength of the wireless links and the status of buffer, the interference on PUs should be kept below a specific threshold simultaneously. Closed-form expressions of secrecy outage probability (SOP) for cognitive radio network is obtained based on the Markov chain. Numerical results demonstrate that the proposed scheme can significantly enhance the secure performance compared to the conventional relay selection scheme.