MAC Layer Research Articles

Jamming Attacks Detection Based on IGWO for Optimization of Fast Correlation-Based Feature extraction in Wireless Communication

Background: Wireless networks are essential communication technologies that prevent cable installation prices and burdens. Because of this technology's pervasive usage, wireless network safety is a significant problem. Owing to distributed and open wireless medium aspects, attackers might use different jamming methods to exploit physical and MAC layer protocol vulnerabilities. In addition, jamming attacks require to be accurately grouped so that suitable countermeasures can be considered. Given the potential severity of such attacks, precisely identifying and classifying them is critical for implementing effective responses. The motivation for this paper is the need to improve the detection and categorization of jamming signals using modern machine learning algorithms, consequently enhancing wireless network security and reliability. Objective: In this paper, we compare some machine learning models' efficiency for diagnosing jamming signals. Methods: Such algorithms refer to support vector machine (SVM) and k-nearest neighbors (KNN). We checked the signal features that recognize jamming signals. After the jamming attack model, the developed grey wolf optimizer version known as IGWO (improved grey wolf optimizer) has been discussed for feature extraction of software usability. Four separate metrics were employed as features to detect jamming attacks in order to evaluate the machine learning models. This novel feature extraction method is crucial for improving the accuracy of jamming detection. Results: The measurements of these parameters were gathered through a simulation of a real setting. And generated a large dataset using these parameters. Conclusion: The simulation results illustrate that the KNN algorithm based on jamming detection could diagnose jammers having a minimal likelihood of false alarms and a high level of accuracy.

Optimal resource management for multi-access edge computing without using cross-layer communication

We consider a Multi-access Edge Computing (MEC) system with a set of users, a base station (BS) with an attached MEC server, and a cloud server. The users can serve the service requests locally or can offload them to the BS which in turn can serve a subset of the offloaded requests at the MEC and can forward the requests to the cloud server. The user devices and the MEC server can be dynamically configured to serve different classes of services. The service requests offloaded to the BS incur offloading costs and those forwarded to the cloud incur additional costs; the costs could represent service charges or delays. Aggregate cost minimization subject to stability warrants optimal service scheduling and offloading at the users and the MEC server, at their application layers, and optimal uplink packet scheduling at the users’ MAC layers. Classical back-pressure (BP) based solutions entail cross-layer message exchange, and hence are not viable. We propose virtual queue-based drift-plus-penalty algorithms that are throughput optimal, and achieve the optimal delay arbitrarily closely but do not require cross-layer communication. We first consider an MEC system without local computation, and subsequently, extend our framework to incorporate local computation also. We demonstrate that the proposed algorithms offer almost the same performance as BP based algorithms. These algorithms contain tuneable parameters that offer a trade off between queue lengths at the users and the BS and the offloading costs.

Probabilistic performance evaluation of the class-A device in LoRaWAN protocol on the MAC layer

LoRaWAN is a network technology that provides a long-range wireless network while maintaining low energy consumption. It adopts the pure Aloha MAC protocol and the duty-cycle limitation at both uplink and downlink on the MAC layer to conserve energy. Additionally, LoRaWAN employs orthogonal parameters to mitigate collisions. However, synchronization in star-of-star topology networks and the complicated collision mechanism make it challenging to conduct a quantitative performance evaluation in LoRaWAN. Our previous work proposes a Probabilistic Timed Automata (PTA) model to represent the uplink transmission in LoRaWAN. It is a mathematical model that presents the nondeterministic and probabilistic choice with time passing. However, this model remains a work in progress. This study extends the PTA model to depict Class-A devices in the LoRaWAN protocol. The complete characteristics of LoRaWAN’s MAC layer, such as duty-cycle limits, bidirectional communication, and confirmed message transmission, are accurately modeled. Furthermore, a comprehensive collision model is integrated into the PTA. Various properties are verified using the probabilistic model checker PRISM, and quantitative properties are calculated under diverse scenarios. This quantitative analysis provides valuable insights into the performance and behavior of LoRaWAN networks under varying conditions.

Energy-Efficient Clustering in Wireless Sensor Networks Using Grey Wolf Optimization and Enhanced CSMA/CA.

Survivability is a critical concern in WSNs, heavily influenced by energy efficiency. Addressing severe energy constraints in WSNs requires solutions that meet application goals while prolonging network life. This paper presents an Energy Optimization Approach (EOAMRCL) for WSNs, integrating the Grey Wolf Optimization (GWO) for enhanced performance. EOAMRCL aims to enhance energy efficiency by selecting the optimal duty-cycle schedule, transmission power, and routing paths. The proposed approach employs a centralized strategy using a hierarchical network architecture. During the cluster formation phase, an objective function, augmented with GWO, determines the ideal cluster heads (CHs). The routing protocol then selects routes with minimal energy consumption for data transmission to CHs, using transmission power as a metric. In the transmission phase, the MAC layer forms a duty-cycle schedule based on cross-layer routing information, enabling nodes to switch between active and sleep modes according to their network allocation vectors (NAVs). This process is further optimized by an enhanced CSMA/CA mechanism, which incorporates sleep/activate modes and pairing nodes to alternate between active and sleep states. This integration reduces collisions, improves channel assessment accuracy, and lowers energy consumption, thereby enhancing overall network performance. EOAMRCL was evaluated in a MATLAB environment, demonstrating superior performance compared with EEUC, DWEHC, and CGA-GWO protocols, particularly in terms of network lifetime and energy consumption. This highlights the effectiveness of integrating GWO and the updated CSMA/CA mechanism in achieving optimal energy efficiency and network performance.

A Distributed Abstract MAC Layer for Cooperative Learning on Internet of Vehicles

A Distributed Abstract MAC Layer for Cooperative Learning on Internet of Vehicles

Enhanced Call Admission Control based on History in BWA Networks

WiMAX is a wireless technology that supports many blooming applications. To efficiently assign resources to traffic flows, bandwidth allocation and Connection Admission Control (CAC) modules are included in MAC layer and Burst Allocation (BA) module is added to PHY layer. It is essential to lessen delay and effectively schedule requests for BA. In this paper, CAC-based on History (CACH) and scheduler based on Delay Tolerance (SDT) for BA are proposed for WiMAX networks. CACH accepts/ rejects connections based on values in Contention Window (CW) in former Time Frame (TF). SDT and a Bucket-based BA (BBA) assign resources to flows with least amount of DT. Performance is analyzed based on throughput, Packet Loss Ratio (PLR) and delay. Index Terms: WiMAX, Contention Window, Contention Delay, Delay Tolerance, Traffic Priority, Connection Admission Control, Burst Allocation

Channel Bonding Effects of the IEEE802.11n Standard on the WLANs Performance

The evolution of wireless communication technologies has led to the widespread adoption of Wireless Local Area Networks (WLANs). IEEE 802.11n provides many enhancements in physical and MAC layers such as (channel bonding(CB), Multiple Input/Output (MIMO), frame aggregation and block acknowledgment) to achieve higher throughput and improved reliability. As a result, CB is a key technique for enhancing the performance of wireless network. It is frequently used in various fields, such as workplace networks and live streaming. This research paper focuses on analyzing the effect of channel bonding on the performance of the IEEE802.11n WLANs, especially in two terms (throughput and delay). By using the OPNET (Riverbed) Modular version 17.5, five various number of nodes (5, 10, 15, 18 and 30 nodes) uniform topologies are modeled and simulated to investigate the WLANs performance for various MIMO up to 4 SS. Simulation outcomes indicated that applying of CB enhanced both delay and velocity performance. Specifically, in the scenarios (30 nodes), for MIMO (4×4) spatial streams, the average throughput value for channel bonding is (157.28 Mbps) compared to (87.41 Mbps) for no-channel bonding, and the average delay value for channel bonding is (0.0476 Sec) compared to (0.06762 Sec) for no-channel bonding. The enhancement values in the performance of WLANs are 42% and 79.9% for latency and throughput (velocity), respectively.

Simulation and analysis of C-V2X data transmission in different traffic scenarios based on MAC layer scheduling algorithms

With the rapid development of communication technology, vehicles are becoming more and more intelligent, and Vehicle to Vehicle (V2V) communication has become an important cornerstone for the future intelligence of vehicles. Because of the high-reliability and low-latency characteristics of 5G networks, many applications can be realized by using Vehicle to Network (V2N) communications. Different applications have different requirements for Quality of Service (QoS), which should be met by the network, and the base station can use different scheduling methods to satisfy these different requirements. This paper focuses on the scheduler at the MAC layer in 5G base stations. The scheduler must handle both video signals and other communication signals transmitted by the vehicle, and must also consider Hybrid Automatic Repeat reQuest (HARQ) retransmissions. We performed a C-V2X signaling network transmission simulation by using OMNeT++. We considered urban and motorway, two public transportation scenarios. Different types of data are set to be transmitted in two scenarios. We used different scheduling schemes for data scheduling, then investigated the performance of these scheduling schemes for transmitting data. The methods and simulation experiments mentioned in this paper are important for practical generalization.

Ocean-Current-Motion-Model-Based Routing Protocol for Void-Avoided UASNs

An increasing number of scholars are researching underwater acoustic sensor networks (UASNs), including the physical layer, the protocols of the routing layer, the MAC layer, and the cross-layer. In UASNs, the ultimate goal is to transmit data from the seabed to the surface, and a well-performed routing protocol can effectively achieve this goal. However, the nodes in the network are prone to drift, and the topology is easily changed because of the movement caused by ocean currents, resulting in a routing void. The data cannot be effectively aggregated to the sink terminal on the surface. Thus, it is extremely important to determine how to find an alternative node as a relay node after node drift and how to rebuild a reliable transmission path. Although many relay routing protocols have been proposed to avoid routing voids, few of them consider the relay node selection between the outage probability and the ocean current model. Therefore, we propose an ocean current motion model based routing (OCMR) protocol to avoid the routing void in UASNs. We predicted underwater node movement based on the ocean current motion model and designed a protection radius to construct a limited search coverage based on the optimal outage probability; then, the node with the best fitness value within the protection radius was selected as the alternative relay node using an improved WOA. In OCMR, the problem of the routing void caused by ocean current motion is effectively suppressed. The simulation results show that, compared with VBF, HH-VBF, and QELAR, the proposed OCMR platform performs well in terms of the PDR (packet delivery ratio), average end-to-end delay, and average energy consumption.

Optimized IEEE 802.11ax for smart warehouses

Industry 4.0 aspires to digitize factories processes wholly. Wireless technologies represent one of the elements of this goal. However, the current standards and proprietary solutions need to meet the industry’s tight requirements for various use cases, such as smart warehouses, where robots manage and control entire tasks. One of the key research challenges toward replacing wired fieldbuses with wireless links is the design of wireless systems that address short packet transmissions and multi-user environments. Nevertheless, this challenge is partially obstructed by the limits of the current proposals and the industrial channel models. The authors detect as a potential solution the optimization of IEEE 802.11ax that, due to the use of OFDMA, could offer a high-performant system for smart warehouses. This article proposes an ad-hoc wireless system based on IEEE 802.11ax for smart warehouses that comprises optimization for MAC and PHY layers. Furthermore, two retransmission schemes based on frequency domain are described. This article proposes a methodology to evaluate the latency and reliability performance. Compared to previous proposals, the system shows improved performance.

ME-MAC Protocol for MAC Layer in MANET to Overcome HET Problem

Medium Access layer in Mobile Adhoc Network is responsible of transmission of packet through the wireless medium, while transmitting the packet all nodes has to intellect the medium before sending the packet. Every node can able to transmit the packet when the medium if free otherwise the nodes have to wait until the medium becomes free. Some cases the transmission range of the node can be idle but due to Hidden and Exposed node, the node could not be sending the packet to other nodes. Node has to wait unnecessarily event the transmission medium is free. This research article proposed the Mutual Exclusion MAC protocol for avoiding hidden and exposed terminal problem in MANET. The proposed protocol is implemented with the support of Network simulator 3 and results are compared with the existing different protocol proposed for the MAC layer with the parameter and better results shown.

Physical and Data Link Layer Performance Enhancement in MANET to Overcome Hidden -Exposed Node Problem and Packet Loss Due to Buffer Overflow

In order to improve the performance of the MANET , the lower layers of MANET protocol stack has to improve the performance to overcome the hidden and expose node problem in the Physical layer and better buffer management scheme to be included in the data link layer .MAC layer in MANET ,Some cases the transmission range of the node can be idle but due to Hidden and Exposed node , the node could not be send the packet to other nodes. Node has to wait unnecessarily event the transmission medium is free. In case of more traffic in the MANET can leads to overflow in the buffer which causes the packet loss in the transmission. If any packet missed on the transmission the source node has to retransmit to the destination. This research article proposed the Mutual Exclusion MAC protocol for avoiding hidden and exposed terminal problem in MANET and active buffer management algorithm named Intelligent better buffer management (IBM) algorithm which improves the MANET nodes buffers to avoid packet loss . The proposed protocol is implemented with the support of Network simulator 3 and results are compared with the existing different protocol proposed for the MAC layer with the parameter and buffer management schemes and results shown the enhanced results shown.

A Multi-Channel Packet Scheduling Approach to Improving Video Delivery Performance in Vehicular Networks

When working with the Wireless Access in Vehicular Environment (WAVE) protocol stack, the multi-channel operation mechanism of the IEEE 1609.4 protocol may impact the overall network performance, especially when using video streaming applications. In general, packets delivered from the application layer during a Control Channel (CCH) time slot have to wait for transmission until the next Service Channel (SCH) time slot arrives. The accumulation of packets at the beginning of the latter time slot may introduce additional delays and higher contention when all the network nodes try, at the same time, to obtain access to the shared channel in order to send the delayed packets as soon as possible. In this work, we have analyzed these performance issues and proposed a new method, which we call SkipCCH, that helps the MAC layer to overcome the high contention produced by the packet transmission bursts at the beginning of every SCH slot. This high contention implies an increase in the number of packet losses, which directly impacts the overall network performance. With our proposal, streaming video in vehicular networks will provide a better quality of reconstructed video at the receiver side under the same network conditions. Furthermore, this method has particularly proven its benefits when working with Quality of Service (QoS) techniques, not only by increasing the received video quality but also because it avoids starvation of the lower-priority traffic.

Using Multi-Armed Bandit Learning for Thwarting MAC Layer Attacks in Wireless Networks

Using Multi-Armed Bandit Learning for Thwarting MAC Layer Attacks in Wireless Networks

An Adaptive Contention Window using Actor-Critic Reinforcement Learning Algorithm for Vehicular Ad-hoc NETworks

The MAC layer IEEE 802.11p standard’s collision avoidance mechanism is sub-optimal due to the use of a Binary Exponential Backoff (BEB). This technique has an increase in the backoff slot time to minimize the probability of subsequent collisions after the occurrence of a collision. This leads to a degradation of radio bandwidth wastage, especially when managing access to a dense number of stations. An incorrect backoff setting can also increase the likelihood of collisions and decrease network performance. For adaptive CW selection, the proposed model is based on a Reinforcement Learning (RL) Actor-Critic (AC) network to adapt the CW value by learning the VANET environment. NS-3 for VANET is utilized to test and compute the optimal CW values. The proposed AC and EAC outperform traditional BEB used in the IEEE 802.11p standard as the number of vehicles increases. The throughput is enhanced by 54% and 69% respectively for AC and Enhanced AC (EAC). Similarly, the end-to-end delay for AC is reduced by 19%, and for EAC it’s reduced by 25%.

Byzantine Fault Tolerant Consensus in Open Wireless Networks via an Abstract MAC Layer

Byzantine Fault Tolerant Consensus in Open Wireless Networks via an Abstract MAC Layer

Hybrid Relaying Based Cross Layer MAC Protocol Using Variable Beacon for Cooperative Vehicles

Hybrid Relaying Based Cross Layer MAC Protocol Using Variable Beacon for Cooperative Vehicles

QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

Today, the service of Voice over Internet Protocol or (VoIP) is one of the most used service around the globe in many fields, especially with video conferencing applications. Different applications and also many communications companies around the world use the VoIP service. Communication stakeholders aim to keep old customers happy and attract new customers. There was a need for some kind of service quality measures. Metrics are used to quantify the quality of transmission link are known Quality of Service (QoS). Whereas, user satisfaction level is identified by using Quality of Experience (QoE). This paper conducted a simulation model for VoIP service over heterogeneous, using OPNET modeler. This work aims to compare the user satisfaction level of the VoIP service by using different coding schemes in the application level of the User Equipment (UE). The measured QoS parameters over the heterogeneous transmission link were IP packet delay, IP Packet jitter, IP packet loss, MAC layer delay, PHY layer throughput in the network. Additionally, in this simulation model the use of E-Model to assess QoE level using Mean Opinion Score (MOS) metric in predicting the VoIP call quality. The results using the vocoder G.729A during the (30) sec of the voice call simulation time were as follows: Delay 0.57 mSec, Throughput of 290 Kbits/sec, Jitter of 0.02 uSec, MOS value of 3.76. The results using the vocoder G.711 during the same aforementioned time were as follows: Delay 0.25 mSec, Throughput of 70 Kbits/sec, Jitter of 0 Sec), MOS value of 3.08.

QoS Management for XR Traffic in 5G NR: A Multi-Layer System View and End-to-End Evaluation

Extended reality (XR) applications are gaining a lot of momentum in the industry and consumer market. XR applications are characterized by multiple simultaneous data flows with different Quality-of-Service (QoS) requirements, imposing the need for advanced QoS management in 5G networks. Compared to 4G, the 5G NR technology has been designed with enhanced QoS support, by introducing the concept of QoS flows and an additional layer for QoS handling. However, recent studies show that additional QoS enhancements are needed in 5G to support the massive adoption of XR services. 3GPP envisions to include some enhancements for XR traffic in 5G-Advanced. In this paper, we review the current 5G QoS framework and study potential design improvements to fulfill XR QoS requirements in future cellular networks. We study QoS control procedures for XR traffics at different layers of the 5G NR protocol stack, including the proper configuration of radio access and core networks. In particular, we analyze various architectures for handling the peculiarities of XR, such as time-constraint and multi-flow applications. Also, we present XR traffic adaptation mechanisms at the application layer, to properly adapt XR traffic statistics to the actual 5G radio environment, and QoS schedulers for the MAC layer, leading to cross-layer performance optimization between XR application and 5G radio access network. Finally, we provide a validation study and end-to-end evaluation of QoS control mechanisms by simulating realistic mixed traffic scenarios in a 5G NR system-level simulator based on ns-3.

Considering Performance Issues in Ad Hoc Networking : A Comprehensive Study

Ad hoc networks have emerged as a versatile and dynamic communication paradigm with applications spanning from mobile devices and sensor networks to emergency response and military operations. However, their inherent decentralized and self-organizing nature gives rise to a myriad of performance challenges that must be comprehensively addressed to ensure reliable and efficient communication. This paper presents a comprehensive study of performance issues in ad hoc networking, aiming to provide a holistic understanding of the various factors impacting network performance. The study begins by examining the fundamental characteristics of ad hoc networks, highlighting their unique advantages and challenges. We delve into critical performance metrics such as throughput, latency, scalability, and energy efficiency, dissecting the factors that influence each of these metrics in ad hoc environments. The role of routing protocols, MAC layer design, and network topologies in shaping network performance is thoroughly analyzed. Furthermore, this study explores the impact of mobility patterns, traffic models, and interference on ad hoc network performance. It delves into the challenges posed by dynamic network topologies, node failures, and the need for adaptive mechanisms to maintain robust connectivity. Quality of service (QoS) considerations and their implications on performance are also discussed in detail. To provide a comprehensive view, we survey state-of-the-art solutions and techniques proposed in the literature to mitigate performance issues in ad hoc networks. These include adaptive routing algorithms, cross-layer optimization approaches, and novel communication paradigms like cognitive radio networks. Finally, we present a roadmap for future research directions in the field of ad hoc networking performance optimization. The goal is to inspire further investigation and innovation in addressing the evolving challenges faced by ad hoc networks, making them more reliable, efficient, and adaptable for a wide range of applications.