Cross-layer Approach Research Articles

A Cross-Layer Approach to Analyzing Energy Consumption and Lifetime of a Wireless Sensor Node

Several wireless communication technologies, including Wireless Sensor Networks (WSNs), are essential for Internet of Things (IoT) applications. WSNs employ a layered framework to govern data exchanges between sender and recipient, which facilitates the establishment of rules and standards. However, in this conventional framework, network data sharing is limited to directly stacked layers, allowing manufacturers to develop proprietary protocols while impeding WSN optimization, such as energy consumption minimization, due to non-directly stacked layer effects on network performance. A Cross-Layer (CL) framework addresses implementation, modeling, and design challenges in IoT systems by allowing unrestricted data and parameter sharing between non-stacked layers. This holistic approach captures system dynamics, enabling network design optimization to address IoT network challenges. This paper introduces a novel CL modeling methodology for wireless communication systems, which is applied in two case studies to develop models for estimating energy consumption metrics, including node and network lifetime. Each case study validates the resulting model through experimental tests, demonstrating high accuracy with less than 3% error.

Enhancing Quality of Service and Energy Efficiency in Wireless Sensor Networks through TDMA-Based Topology and Cross-Layer Approaches

It is necessary to continuously monitor the environment with the sensors in delay-sensitive wireless sensor network applications. The continuous monitoring operation results in higher energy consumption by the sensor nodes; wireless sensor networks are also subject to numerous difficulties, including latency, packet loss, and throughput. These are the most important constraints in wireless sensor networks (WSNs) and need to improve for better quality communication. In this research, quality of service is related to numerous systems that have very sensitive parameters such as end-to-end delay, packet loss, throughput, energy consumption, latency, and average delay. Therefore, it is necessary for the sensors to transmit reliable data within a reasonable timeframe. To find out better communication results, we have used the TDMA (Time Division Multiple Access) approaches in our paper to improve packet delivery ratio (PDR), latency, and throughput. The NS2 simulator is used to test communication between nodes. Latency, the packet delivery ratio (PDR) of transferring data packets, and throughput are measured. The TDMA approach is used in our proposed topology, and we can see a specific area where nodes are connected to communicate with one another. Each node is communicating with the other node using two different paths. Each node's bandwidth, latency, and PDR will be different. Hence, in one path, a TDMA approach is implemented, which results in improved node performance in terms of latency, packet delivery ratio, and bandwidth.

Cross-Layer Methods for Ad Hoc Networks—Review and Classification

The OSI model used to be a common network model for years. In the case of ad hoc networks with dynamic topology and difficult radio communications conditions, gradual departure is happening from the classical kind of OSI network model with a clear delineation of layers (physical, channel, network, transport, application) to the cross-layer approach. The layers of the network model in ad hoc networks strongly influence each other. Thus, the cross-layer approach can improve the performance of an ad hoc network by jointly developing protocols using interaction and collaborative optimization of multiple layers. The existing cross-layer methods classification is too complicated because it is based on the whole manifold of network model layer combinations, regardless of their importance. In this work, we review ad hoc network cross-layer methods, propose a new useful classification of cross-layer methods, and show future research directions in the development of ad hoc network cross-layer methods. The proposed classification can help to simplify the goal-oriented cross-layer protocol development.

Optimization Techniques in Cooperative and Distributed MAC Protocols

The tremendous increase in wireless network application finds distributed allocation of resources allocation very useful in the network. Packet delivery ratio and delay can be improved by concentrating on payload size, mobility, and density of nodes in the network. In this article, a survey is carried out on different cooperative and distributed MAC protocols for communication and optimization algorithms for various applications and the mathematical issues related to game theory optimizations in MAC protocol. Spatial reuse of channel improved by (3-29) % and multi-channel improves throughput by 8% using distributed MAC protocol. The energy utility of individual players can be focused to get better network performance with NASH equilibrium. Fuzzy logic improves channel selection by 17% and secondary users' involvement by 8%. Jamming, interference problems can be addressed using cross layer approach in the MAC and simultaneous data, voice transmissions in IoT; WSN applications can be attained using hybrid distributed MAC protocol.

Deterministic Scheduling and Reliable Routing for Smart Ocean Services in Maritime Internet of Things: A Cross-Layer Approach

Deterministic Scheduling and Reliable Routing for Smart Ocean Services in Maritime Internet of Things: A Cross-Layer Approach

A Study on DDoS Attack Detection Technique Prior to Machine Learning in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are integral to a wide range of critical applications, including environmental monitoring, healthcare, and industrial control systems. Then delves into DDoS attacks, elucidating the various attack types, motives, and their detrimental effects on WSNs. The core of the study investigates DDoS detection techniques, encompassing signature-based, anomaly-based, and hybrid approaches. Optimization mechanisms for DDoS detection in WSNs are explored in-depth, including resource-efficient algorithms and scalability solutions. Consideration is given to striking a balance between detection accuracy and resource consumption, essential in the energy-limited world of WSNs. Machine learning and artificial intelligence's role in DDoS detection is elucidated, with a focus on feature selection, dimensionality reduction, and the application of various supervised and unsupervised learning algorithms. Cross-layer approaches, coordinating physical, data-link, and network layers, are discussed to enhance DDoS detection's robustness against sophisticated attacks. Energy efficiency considerations are integral, with strategies outlined to prolong sensor nodes' lifespans while ensuring reliable DDoS detection. The study culminates in the presentation of real-world experiments and simulations, offering insights into the practical performance of DDoS detection and optimization mechanisms. Various evaluation metrics are employed, such as detection rate, false positives, and resource utilization.

A cross-layer approach for load balancing and energy-efficient QoS-based routing reliability for UWSN

Considering several fundamental needs of network performance, the Routing and Media Access Control (MAC) layers are crucially checked out for their operations. Sometimes, MAC protocol faces difficulties in modifying the situations over underwater communication which are specifically considered to be dynamic. The nodes in water tend to remain unstable and network fluctuations are made depending upon the number of competitors. The existing hybrid MAC protocol does not possess dynamic network loads. It also involves a lack of modification in access control approaches which provide variations in network loads. Finally, it leads to delayed network performance. The routing layer focus on some difficult parameters like increased packet loss, restricted bandwidth with substantial energy incursion, reduced network lifetime, increased propagation delay, less remaining energy, consistent data transfer, and energy organization which are considered to be the most important research issues in Underwater Acoustic Sensor Networks (UWASNs). In MAC and routing layers, a Cross-layer approach involves some techniques which are discussed and implemented using Ns3 simulation to obtain the performance report. It is also proposed to compare the algorithm with existing techniques to provide accurate results. Reinforcement Learning (RL) in the MAC layer for SINR-based time slot allocation and Integrated Artificial Fish Swarm with Bacterial Foraging Algorithm (IAFSBFA) for energy-aware QoS reliable routing in the network layer are used in this system. In this cross-layer approach, load balancing in the MAC layer and efficient routing using a hybrid algorithm gives out better performance in the underwater network.

Enhancing end-to-end determinism and reliability in 6TiSCH networks with disjoint leaf-based MPLS-like tunnels

Industrial multi-hop Internet of Things (IIoT) have strict reliability requirements and they are expected to have deterministic behavior. Reliability is associated with the network’s ability to provide the best goodput possible to the destination from the source application, while deterministic behavior implies that the packets must also arrive at the destination before the maximum allowable deadline defined by the application expires. Although a relevant number of proposals have arisen in recent years, none of them achieve both restrictions simultaneously. In this work, we propose a cross-layer approach to solve this problem, by combining three strategies: (i) the use of the preferred parents (PP) and alternative parents (AP) together with the PRE (Packet Replication and Elimination) technique at the routing level; (ii) the use of MPLS tunnels from the leafNode, improving the Data Plane, to control the energy consumption and (iii) the use of the BDPC (Bounded Delay Packet Control) algorithm. The combination of the former strategies show that the behavior of the packet flows improves the end-to-end Packet Delivery Rate of the packets arriving before the deadline by 2.04 times with respect to standard Minimum Scheduling Function reference network while simultaneously increasing the minimum average network lifetime by 1.5 times, with respect to the hop by hop uncontrolled usage of PRE.

Deep Learning-Based Cross-Layer Power Allocation for Downlink Cell-Free Massive Multiple-Input–Multiple-Output Video Communication Systems

We propose a deep learning-based cross-layer power allocation method for asymmetric cell-free massive MIMO video communication systems. The proposed cross-layer approach considers physical layer channel state information (CSI) and the application layer rate distortion (RD) function, and it aims to enhance video quality in terms of peak signal-to-noise ratio (PSNR). Our study develops a decentralized deep neural network (DNN) model to capture intricate system patterns, enabling accurate and efficient power allocation decisions. The proposed cross-layer approach includes unsupervised and hybrid (supervised/unsupervised) learning models. The numerical results show that the hybrid method achieves convergence with just 50% of the iterations required by the unsupervised learning model and that it achieves a 1 dB gain in PSNR over the baseline physical layer scheme.

Cooperative optimization techniques in distributed MAC protocols – a survey

Purpose Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power. Design/methodology/approach Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol. Findings Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Research limitations/implications Other optimization techniques can be applied for WSN to analyze the performance. Practical implications Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes. Social implications Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage. Originality/value Literature survey is carried out to find the methods which give better performance.

Fuzzy intelligence based V2V routing protocol in Internet of Vehicles: a cross-layer approach

Fuzzy intelligence based V2V routing protocol in Internet of Vehicles: a cross-layer approach

SOHCL-RDT: A self-organized hybrid cross-layer design for reliable data transmission in wireless network

In this paper, we propose “SOHCL-RDT” which stands for a self-organized hybrid cross-layer design for reliable data transmission in wireless network. The communication paradigm is changing and new approach related to machine learning or other optimization algorithms are being introduce rapidly. The TCP/IP or OSI model is not at all equipped to accommodate such a vast changes in its established protocol stacks. Considering this, we have proposed the hybrid cross layer design where the communication or transmission will be handle using two set of protocol stack. One set for the established classical network, and another using cross layer approach. Our design leverages the strengths of both the physical and MAC layers to optimize packet transmission and minimize energy consumption. An optimization algorithm based on gradient descent is also developed to adjust transmission parameters in real-time. The objective is to invoke the classical model only when it needed; it means until unless gradient descent is able to make classification regarding the node scheduling and achieve the acknowledgment, the TCP/IP protocol stack will be in deactivation. Using this method, we have performed our experiments mainly on two parameters named as packet delivery ratio (PDR), end-to-end delay (E2ED); because these are important aspect of reliability. In addition to that, the energy consumption of network is also compared with the existing algorithms. The results show that the proposed hybrid cross-layer design outperforms the existing algorithms. The performance gain can be attributed to the cross-layer approach and the use of the optimization algorithm. Overall, the proposed hybrid cross-layer design is a promising solution for reliable data transmission in wireless sensor networks, with the potential to improve network performance and prolong network lifetime by reducing energy consumption.

Relay-Assisted Platooning in Wireless Networks: A Joint Communication and Control Approach

This paper addresses the problem of the joint design of the mobile communication system and the control scheme for enabling vehicle platooning applications. Vehicles communicate essential information for platooning control through multi-hop vehicle-to-vehicle (V2V) communications and are assisted in this task by Road Side Units (RSU), when available. While classical approaches, adopted in previous and current mobile systems, consider the application needs solely as requirements for the communication network, we advocate a bi-directional interaction of application and communication network. We first study the impact of different communication strategies on the application-level performance, namely the inter-vehicle distance in the platoon. Such schemes introduce a tradeoff between the packet delivery rate and the additional delay introduced by relaying. In order to assess the impact of both metrics, we start by developing a Markov model for the different communication links (inter-vehicle and vehicle-to-RSU). We then propose a cross-layer approach that adapts the application layer (platoon control parameters) to the observed Medium Access Control (MAC) layer performance. We demonstrate via simulations the benefit of the proposed relaying scheme, and that a joint design of application and communication systems is essential for enabling the integration of industrial applications in future generation networks.

Cross Layer based Energy Aware and Packet Scheduling Algorithm for Wireless Multimedia Sensor Network

Video transmission using sensor networks plays a most significant role in industrial and surveillance applications. Multimedia transmission is also a challenging task in case of guaranteeing quality of service in conditions like limited bandwidth, high congestion, multi-hop routing, etc. Cross layer approach is carried out to handle multimedia transmission over sensor networks for improving network adaptivity. Cross layer based energy aware and packet scheduling algorithm is proposed here to reduce congestion ratio and to improve link quality between the routing nodes. Link quality estimation among nodes is done using Semi-Markov process. Node congestion rate is determined for identifying node’s data channel rate. Packet scheduling process determines the highly prioritized packets by using queue scheduler component thereby the active nodes are selected through link quality process and the packets are transmitted to sink based on prioritize level. Simulation analysis is carried out and the efficiency of the proposed mechanism is proved to be better while comparing with the conventional schemes.

Energy and MCS Optimization in HARQ Protocol for Ultrareliable Regime With Maximized Throughput

In this article, we propose a cross-layer approach to maximize the throughput efficiency of the hybrid automatic repeat request (HARQ) protocol while guaranteeing ultrareliable communication (URC). The study combines adaptive modulation and coding and power control, at the physical layer, with automatic repeat request (ARQ)/HARQ at the data-link layer. The proposed optimization approach, based on genetic algorithms, allows a judicious allocation of the available energy budget and a suitable modulation and coding scheme (MCS) choice while keeping the same energy budget. For a given signal-to-noise ratio (SNR), a vector of energy and an MCS are modeled as one individual. The individuals with the highest throughput efficiency are selected to be used in generating the next population through crossover of the survivals and mutation. The individual with the highest throughput efficiency in the last population presents the solution offering the optimized parameters used in the packet transmission. We compare our solution to an existing one that exploits Lagrange multipliers. The results show that the proposed genetic algorithm based solution ensures URC with packet erasure probability less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10^{-5}$</tex-math></inline-formula> from SNR values of 7 and 13 dB in static and fading channels, respectively.

A Cross-layer Approach for MPTCP Path Management in Heterogeneous Vehicular Networks

A Cross-layer Approach for MPTCP Path Management in Heterogeneous Vehicular Networks

Genetic Algorithm for Cross-Layer-Based Energy Hole Minimization in Wireless Sensor Networks

Wireless sensor networks encompass wireless connectivity, low energy consumption protocols, and many algorithms. The sensor node battery is marked as a striking problem in such resource-constrained networks. Once the sensor nodes are mounted in an area, the batteries present in nodes are difficult to repair or replace. Many algorithms and protocols are implemented to progressively minimize the usage of energy in nodes. The sensor in charge of scheduling packets is significantly essential to reduce the processing overhead, energy consumption. Maximum-largest weighted delay first (M-LWDF) and packet dependent (PD) scheduling algorithms have been investigated in the multiuser multiservice systems. Efficiency and performance are better especially for multiuser multiservice to nonloss transmission during resource lag. Proposed work of cross-layer approach using genetic algorithm improves energy quality and efficiency by 24.7% compared to the existing methods and finds useful applications are low.

A Methodology for Abstracting the Physical Layer of Direct V2X Communications Technologies

Recent advancements in vehicle-to-everything (V2X) communications have greatly increased the flexibility of the physical (PHY) and medium access control (MAC) layers. This increases the complexity when investigating the system from a network perspective to evaluate the performance of the supported applications. Such flexibility, in fact, needs to be taken into account through a cross-layer approach, which might lead to challenging evaluation processes. As an accurate simulation of the signals appears unfeasible, a typical solution is to rely on simple models for incorporating the PHY layer of the supported technologies based on off-line measurements or accurate link-level simulations. Such data are, however, limited to a subset of possible configurations, and extending them to others is costly when not even impossible. The goal of this paper is to develop a new approach for modeling the PHY layer of V2X communications that can be extended to a wide range of configurations without leading to extensive measurement or simulation campaigns at the link layer. In particular, given a scenario and starting from results in terms of the packet error rate (PER) vs. signal-to-interference-plus-noise ratio (SINR) related to a subset of possible configurations, we first approximated the curves with step functions characterized by a given SINR threshold, and we then derived one parameter, called implementation loss, that was used to obtain the SINR threshold and evaluate the network performance under any configuration in the same scenario. The proposed methodology, leading to a good trade-off among the complexity, generality, and accuracy of the performance evaluation process, was validated through extensive simulations with both IEEE 802.11p and LTE-V2X sidelink technologies in various scenarios. The results first show that the curves can be effectively approximated by using an SINR threshold, with a value corresponding to 0.5 PER, and then demonstrate that the network-level outputs derived from the proposed approach are very close to those obtained with complete curves, despite not being restricted to a few possible configurations.

Double QoS Guarantee for NOMA-Enabled Massive MTC Networks

Massive connections and diverse Quality of Service (QoS) requirements pose a major challenge for machine-type communication (MTC) networks. In this article, to satisfy the various QoS requirements of a massive number of MTC devices (MTCDs), the devices are divided into multiple clusters based on the QoS characteristics. The cluster access control and intracluster resource allocation problems are studied to satisfy the double delay requirements in the access and data transmission phases in a cross-layer approach. Specifically, we formulate an access control problem to maximize the access efficiency with constraints on access and transmission delays. An efficient algorithm is proposed to adaptively adjust the access time intervals and backoff factors of the clusters for different numbers of active MTCDs and transmission rates. Given the access parameters, nonorthogonal multiple access is adopted in resource allocation to maximize the system utility function while guaranteeing the delay requirements for each accessed MTCD. An efficient sequential convex programming iterative algorithm is proposed to solve the NP-hard nonconvex problem with two typical utility objectives: 1) total throughput and 2) consumed power. Simulation results show that the proposed scheme can achieve better performance in terms of access efficiency, delay, throughput, and consumed power than other schemes. The impacts of various parameters, including delay and traffic rate, on the performance, are disclosed.

A Novel Approach to Enhance the End-to-End Quality of Service for Avionic Wireless Sensor Networks

Going wireless is one of the key industrial trends, which assists the emergence of new manufacturing and maintenance processes by reducing the complexity and cost of physical equipment. However, the adoption of Wireless Sensor Networks (WSNs) in production environments is limited due to the strict Quality of Service (QoS) requirements of industrial applications. In particular, Wireless Avionics Intra-Communication (WAIC) systems operating in 4.3 GHz band are designed for intra-aircraft use cases with considerable restrictions on the transmission power of sensors, which results in multi-hop topologies, complicating a guaranteed QoS. The Internet Engineering Task Force (IETF) has developed the protocol stack IPv6 over the Time Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH) based on the IEEE 802.15.4 Standard for Low-Rate Wireless Networks, which combines the TSCH reliability with ubiquitous IPv6 connectivity and with the robust Routing Protocol for Low-Power and Lossy Networks (RPL). The Scheduling Function (SF) is a core IPv6 over the TSCH mode of IEEE 802.15.4 (6TiSCH) component, but the specification of the SF is an open research topic: numerous scientific articles investigated how QoS for a wide range of applications can be met by developing specialized SFs. However, no full-scale information exchange between the layers of the 6TiSCH stack was considered to optimize the SFs and to improve the network performance. In this work, we propose a novel solution named 6TiSCH-CLX to satisfy demanding QoS requirements using cross-layer communication. It is an extension of the 6TiSCH framework at the network and Medium Access Control (MAC) layers, addressing latency and reliability challenges agnostic of the physical layer. 6TiSCH-CLX is evaluated both analytically and in simulations for several safety-critical avionic intra-communication use cases in WAIC. Preliminary results indicate considerable improvements to latency, while maintaining almost 100% Packet Delivery Ratio (PDR) without retransmissions and they highlight the capability of the cross-layer approach compared to existing solutions.