End-to-End Wireless Performance Simulator: Modelling Methodology and Performance

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.

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.

Interactive transparent networking–modeling examples of snoop and WTCP protocols

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.

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.

Day by day popularity of wireless devices used to access the Internet is increasing. It indicates that in the near future TCP protocol will be frequently used over the wireless links. The wireless links characteristics are significantly different from characteristics of wired links. TCP (Transport Control Protocol) is basically designed for wired network. One of the main reasons for TCP's degraded performance in wireless networks is TCP's interpretation that packet loss is caused by congestion. However, in wireless cellular networks packet loss occurs mostly due to high bit error rate, packet corruption, or link failure. As TCP is designed to use over wired network it needs to change when it is used over wireless network. Hence, various mechanisms were proposed to improve TCP performance over wireless links. TCP performance in wired/wireless networks may be substantially improved by modifying some of the algorithms used in TCP. This paper proposes a new TCP protocol named Modified-TCP (MTCP) that uses modified congestion algorithm, fast and local retransmission and SACK (selective acknowledgment). This makes the proposed protocol better suited in a wide range of applications in mixed wired and wireless links. This paper shows the results after comparing performance of MTCP with TCP over wired cum wireless network using network simulator ns-2.

A new multi-rat scheduling algorithm for heterogeneous wireless networks

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.

The emergence of new applications puts forward more stringent requirements on the performance of wireless communication networks, therefore novel architecture is required to satisfy the development demands. Among the research of 6G wireless networking architecture, the cell-free network is considered as one of the most potential enabler technologies. However, the current network is generally based on rigid architecture (i.e. centralized or distributed) and cannot be flexibly adapted to different applications. This paper first investigates a 6G inter-frequency networking architecture based on cell-free technology, and proposes a real-time adjustment method for the network architecture, which combines both distributed and centralized processing to achieve dynamic on-demand adjustment.

Current wireless networks are based on unicast routing protocol derived from wired networks. The purpose of this paper is to implement and to evaluate opportunistic routing protocols in new generation’s wireless network. This is a comparative study between two opportunistic protocols, which are extremely opportunistic routing protocol and simple opportunistic adaptive routing protocol. The main goal of this survey is to show the benefits required by using opportunistic approach to optimize the new generation’s wireless networks operations and implemented the most used protocols under MATLAB framework.

Call admission control (CAC) protocols play a very role in the performance of wireless networks. In this paper, we present a call admission control protocol for cellular wireless networks. Our protocol depends on degrading the existing calls by reducing the bandwidth allocated to them in order to admit important calls. Our protocol assign priorities for the incoming calls, and in the same time assign priorities to the existing calls, both admitted calls are admitted according to their priorities and the existing calls are degraded according to their priorities. We show simulation results for the relation between network utilization, call blocking probability, and average assigned bandwidth during the life of the call.

Data transmission in wireless networks is vulnerable to errors, due to the nature of wireless characteristics. As a result, corrupted packets are a common case in wireless data transmissions. Many techniques have been proposed to tackle these issues and one of the recommended techniques is the partial packet recovery (PPR) scheme. There are various existing PPR methods that have been proposed in wireless networks over the past two decades. In addition, the recent works have shown the possibility of network coding along with its capabilities in recovering the partial packets. A review study of PPR approaches in wireless networks is presented in this study. The authors classify the approaches into several groups based on the soft information in the PHY layer. Furthermore, they describe the PPR techniques that have used in each of these groups. Their studies found that there are 24 protocols have been proposed using PPR to improve the performance in wireless networks.

In wireless networks, the broadcast nature of wireless transmission enables cooperation by sharing the same transmissions with nearby receivers and thus can help improve spatial reuse and boost network throughput along a multi-hop routing. The performance of wireless networks can be further improved if prior information available at the receivers can be utilized to achieve perfect interference subtraction. In this paper, we investigate performance gain on network throughput for wireless cooperative networks by using a simple MUD scheme, called overlapped transmission, in which multiple transmissions are allowed only when the information in the interfering signal is known at the receiver. It is shown that the scheme of cooperative transmission with overlapping increases network throughput by 24% compared to that of direct transmission with overlapping. We then propose a new cooperation scheme called supplementary cooperation, which improves the performance gain of direct transmission with overlapping by 42%. Analytical results are developed to show that in a general network scenario, supplementary cooperation achieves bit error rate (BER) reduction of 34.87%, compared with the conventional cooperative transmission. Furthermore, we proposed a criterion for finding the best cooperative route to achieve maximum network throughput in a general network.

Network coding (NC) is a promising technique recently proposed to improve network performance in terms of maximum throughput, minimum delivery delay, and energy consumption. The original proposal highlighted the advantages of NC for multicast communications in wire-line networks. Recently, network coding has been considered as an efficient approach to improve performance in wireless networks, mainly in terms of data reliability and lower energy consumption, especially for broadcast communications. The basic idea of NC is to remove the typical requirement that different information flows have to be processed and transmitted independently through the network. When NC is applied, intermediate nodes in the network do not simply relay the received packets, but they combine several received packets before transmission. As a consequence, the output flow at a given node is obtained as a linear combination of its input flows. This chapter deals with the application of network coding principle at different communications layers of the protocol stack, specifically, the Medium Access Control (MAC) and physical (PHY) Layers for wireless communication networks.

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