Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks

Wireless networking is a crucial component of communication in this era of digitization. The key characteristics that determine a wireless network's performance are smooth connectivity, quicker communication, and increased customer satisfaction. Scalability deals with the erratic workload and new resources that are added to the network. Scalability is crucial for both Quality of Experience (QoE) and Quality of Service (QoS) in such a power-constrained environment because wireless devices are battery-operated. Managing power consumption and network performance simultaneously in scalable networking scenario is quite challenging, especially during handover. This research proposed a methodology to assess the impact of scalability on wireless node power consumption and network performance in order to develop energy-efficient handoff mechanisms. The Type-I and Type-II wireless node sets were used between the WiFI and WiMAX networks in a vertical handover scenario. In the study, two distinct scalability scenarios were taken into account. Three distinct voltage levels—cutoff voltage, nominal voltage, and charge voltage —had been used to examine the consumption of power. Throughput, residual energy, and Packet Delivery Ratio (PDR) were computed to examine the network's performance in a scalable, power-constrained context. Two different scalability scenarios were considered in the study. The power consumption was investigated using three different voltage levels: charge voltage, nominal voltage, and cutoff voltage. The network's performance under scalable, power-constrained conditions was investigated by computing throughput, packet delivery ratio (PDR), and residual energy. The result obtained in the study showed the variation in battery drainage of wireless nodes under the effect of various scalability factors. This study will provide a blueprint for developing novel algorithms which eventually will improvise network performance and strengthen the base of Green Networking.

The traffic in wireless networks has become diverse and fluctuating both spatially and temporally due to the emergence of new wireless applications and the complexity of scenarios. The purpose of this paper is to quantitatively analyze the impact of the wireless traffic, which fluctuates both spatially and temporally, on the performance of the wireless networks. Specially, we propose to combine the tools from stochastic geometry and queueing theory to model the spatial and temporal fluctuation of traffic, which to our best knowledge has seldom been evaluated analytically. We derive the spatial and temporal statistics, the total arrival rate, the stability of queues and the delay of users by considering two different spatial properties of traffic, i.e., the uniformly and non-uniformly distributed cases. The numerical results indicate that although the fluctuation of traffic (reflected by the variance of total arrival rate) when the users are clustered is much fiercer than that when the users are uniformly distributed, the unstable probability is smaller. Our work provides a useful reference for the design of wireless networks when the complex spatio-temporal fluctuation of the traffic is considered.

A new multi-rat scheduling algorithm for heterogeneous wireless networks

Transmission power plays a crucial role in the design and performance of wireless networks. The issue is therefore complex since an increase in transmission power implies that a high quality signal is received at the receiver and hence an increase in channel capacity. Conversely, due to the shared nature of the wireless medium an increase in transmission power also implies high interference in the surrounding region and hence a quadratic reduction in the capacity of wireless networks. Recent literatures indicate that employing multiple channels can mitigate the negative effects of wireless interference and thus greatly improve the overall network capacity. Therefore, it is worth investigating the effect of exploiting power on the capacity of multi-channel multi-radio (MC-MR) wireless networks. Specifically, in this paper we address the following questions: (a) Can we maximize the capacity of MC-MR wireless networks by exploiting power? (b) Under what criteria can we increase the transmission power of the nodes in a MC-MR network? %In this paper, we address these issues and investigate the impact of employing high transmission power and multiple channels in a static wireless network when node placements are chosen arbitrarily. When $n$ nodes each with $m$ half-duplex interfaces are optimally deployed in a torus of unit area, traffic patterns are optimally assigned, each transmission's range is optimally chosen and in the presence of $c$ channels, we show that in contrast to the setting where nodes transmit at minimum power level $P_0$ the transport capacity, measured in bit-meters per second, of MC-MR network exploiting power is increased by $\Theta(\frac{c}{c_{min}})$ in region $c_{min} mn/2$ when nodes tune to transmit power level of $P_0(\frac{c}{c_{min}})^(\frac{\alpha}{2})$ and $P_0n^{\frac{\alpha}{2}}$ respectively. Where $c_{min}$ is the minimum number of channels required to achieve conflict-free transmissions in a network. Our analysis also sheds light into several insights that designers may want to consider to improve the performance of energy-efficient bandwidth-constrained wireless networks.

In a multi-hop wireless network, connectivity is determined by the link that is established by the receiving signal strength computed by subtracting the path loss from the transmission power. Two path loss models are commonly used in research, namely two-ray ground and shadow fading, which determine the receiving signal strength and affect the link quality. Link quality is one of the key factors that affect network performance. In general, network performance improves with better link quality in a wireless network. In this study, we measure the network connectivity and performance in a shadow fading path loss model, and our observation shows that both are severely degraded in this path loss model. To improve network performance, we propose power control schemes utilizing link quality to identify the set of nodes required to adjust the transmission power in order to improve the network throughput in both homogeneous and heterogeneous multi-hop wireless networks. Numerical studies to evaluate the proposed schemes are presented and compared.

Wireless network security protocols are essential for enhancing security, privacy and confidentiality. However, network security protocols also require network resources in other to carry out authentication of users through the use of encryption keys and packet encryption. It is therefore relevant to investigate the effects of the amount of resources used by recommended wireless network security protocols in other to determine if user quality of experience and user quality of service is affected by the implementation wireless network security protocols. Our research investigates and examines the effect of security protocols on wireless network performance. The Wi-Fi Protected Access 2 - PreShared Key (WPA2-PSK) was used as the security protocol in focus while throughput was the network performance feature that was analyzed. Experiments were carried out which showed that throughput in a non-secured Wireless Local Area Network (WLAN) is a bit higher than throughput in a secured WLAN. Our research contributes to the future development of WLAN protocols with low network resource consumption in other to contribute to improved network performance.

The performance of Wireless Local Area Network (WLAN) is highly dependent on the processes that are implemented in the Medium Access Control (MAC) sublayer regulated by the IEEE 802.11 standard. In turn, various parameters affect the performance of the MAC sublayer, the most important of which is the number of stations in the network and the offered load. With the massive growth of multimedia traffic, research of the network performance depending on traffic types is relevant. In this paper, we present the impact of a high-/low-priority traffic ratio on WLAN performance with different numbers of access categories. The simulation results show different impact of high-/low-priority traffic ratio on the performance of the MAC sublayer of wireless LANs depending on different network-sizes and on network conditions. Performance of the large network with two access categories and with the prevalent high-priority traffic is significantly higher than in the case of using four categories on the MAC sublayer. This allows us to conclude that the performance improvement of the large network with the prevalent high-priority traffic can be achieved by an adaptive adjustment of the access categories number on the MAC sublayer.

Wireless local area networks (WLANs) have risen in popularity for in-car networking systems that are designed to make driving safer. Wireless mesh networks (WMNs) are widely deployed to expand the coverage of high-speed WLANs and to support last-mile connectivity for mobile users anytime and anywhere at low cost. Many recent measurement studies have shown that the traffic arrival process in wireless networks exhibits the bursty and correlated nature. A new analytical model is developed in this paper as a cost-effective performance tool to investigate the quality-of-service (QoS) of the WMN that interconnects multiple WLANs in the presence of bursty and correlated traffic. After validating its accuracy via extensive simulation experiments, the analytical model is then used to investigate the performance of the hybrid wireless networks.

Analyzing massive amounts of data using complex machine learning models requires significant computational resources. The conventional approach to such problems involves centralizing training data and inference processes in the cloud, i.e., in data centers. However, with the proliferation of mobile devices and increasing application of the Internet-of-Things (IoT) paradigm, very large amounts of data are collected at the edges of wireless networks, and due to privacy constraints and limited communication resources, it is undesirable or impractical to upload this data from mobile devices to the cloud for centralized learning. This problem can be solved by distributed learning at the network edge, by which edge devices collaboratively train a shared learning model using real-time mobile data. The avoidance of raw-data uploading not only helps to preserve privacy but may also alleviate network-traffic congestion and minimize latency. With that said, distributed training still requires a substantial amount of information exchange between devices and edge servers over wireless links. In the process, wireless impairments such as noise, interference, and imperfect knowledge of channel states can significantly slow down distributed learning (e.g., convergence speed) and degrades its performance (e.g., learning accuracy). This makes it crucial to optimize wireless network performance so as to support the efficient deployment of distributed learning algorithms. On the other hand, distributed learning algorithms provide a powerful tool-set for solving complex problems in wireless communication and networking. One important framework, called federated learning (FL), enables users to collaboratively learn a shared model while helping to preserve local data privacy. The application of FL can endow edge devices with capabilities of user behavior prediction, user identification, and wireless environment analysis. As another example, distributed reinforcement learning is capable of leveraging distributed computation power and data to solve complex optimization and control problems that arise in various use cases, such as network control, user clustering, resource management, and interference alignment. To cover this paradigm of distributed learning over wireless networks, this two-part Special Issue features papers dealing with two main research challenges: a) optimization of wireless network performance for efficient implementation of distributed learning in wireless networks, and b) distributed learning for solving communication problems and optimizing network performance.

Performance analysis of coverage-centric heterogeneous cellular networks using dual-slope path loss model

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.

Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

Hyper-Dense Heterogeneous (HDH) deployments, which are made of different kinds of Base Stations (BSs), constitute a promising solution to meet the high data rates envisioned for 5G cellular systems. However, the presence of such a large number of BSs, each of which is expected to deliver a large amount of data to the end-users, is pushing the bottleneck of cellular networks from the Radio Access Network (RAN) to the backhaul, which is becoming as critical as the radio infrastructure. Hence, new network topologies and network architectures are under debate, whose objective is to overcome the backhaul cost and capacity crunch. In order to adequately design these emerging network topologies, appropriate abstraction models need to be introduced for system-level analysis. In this context, stochastic geometry has recently emerged as a promising tool for system-level performance evaluation of cellular systems. In this paper, we adopt a Poisson Tree model for analyzing a hierarchical backhaul and the RAN of a HDH network, where the nodes of the tree are traffic concentrators, BSs and users. The proposed model captures the impact of the finite user density (load) on the network performance and the distribution of the Signal-to-Interference-plus-Noise-Ratio (SINR), which is determined by the positions of users and BSs, as well as by the channel conditions and the other-cell interference.

Modelling and simulation of Rayleigh fading, path loss, and shadowing fading for wireless mobile networks

IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks (LR-WPAN) including sensor networks. Timeliness guarantee is an important feature of the recently standardized IEEE 802.15.4 protocol, making it very much appealing for Wireless Sensor Network applications under timing constraints. Guaranteed Time Slot (GTS) is defined by IEEE 802.15.4 MAC protocol to provide real-time guaranteed service for delay-sensitive applications in beacon-enabled network. This paper presents a comparative analysis of the network performance of WSN in normal mode of operation with CSMA/CA and WSN using GTS mode. Various test cases are created to analyze the performance of Wireless Sensor Network under different node densities to reduce the collisions occurred due to simultaneous conversations between the nodes. Simulation results show that the performance of Wireless Sensor Network with GTS mode improves, with regards to delay and throughput metrics.