Cross-layer Protocol Research Articles

A New Cross-Layer Protocol Based Ad Hoc Wireless Networks

A New Cross-Layer Protocol Based Ad Hoc Wireless Networks

Communication architecture and operations for SDR-enabled UAVs network in disaster-stressed areas

The article presents a collaboration and communication architecture for disaster stressed areas where communication losses restrain disaster response and perplex rescue operations. In these areas, the fragile access networks such as cellular or Wi-Fi systems become congested or inaccessible, requiring a reliable emergency communication infrastructure. The proposed architecture involves Unmanned Aerial Vehicles (UAVs), equipped with wireless technologies i.e., 3G/4G/5G/Wi-Fi systems, and manifestly Software Defined Radios (SDRs), enabling self-forming, self-organizing, and self-healing capabilities. The architecture uses a Hybrid Connectivity Module (HCM) which empowers cooperative communication capacities and abridge the technologies to achieve reliable communication link between UAVs, mobile-to-UAV, and UAV-to-mobile towards Ground Control Station (GCS) in catastrophic areas. The seamless connectivity via next generation SDR waveforms and designed algorithms ensure an implementation of versatile multi-user UAVs network. This enables the formation of a backbone network assisting ground devices to communicate GCS. For cooperative communication, the architecture provides a MAC-centric cross-layer protocol which offers efficient multihop routing between UAVs. The data (i.e., text, images, or voice) is routed to devices or GCS via UAVs, which can notify rescue services reliably and help to trace the catastrophic zones. Furthermore, the protocol helps to allocate network resources by creating virtual sub-nets for simultaneous interference-free data transmissions which maximizes the network throughput. The experimental results show the data latency far better than any other existing ad hoc routing protocol (e.g., OLSR or AODV) based designs which usually add delays in the emergency response operations.

A Centralized Cross-Layer Protocol for Joint Power Control, Link Scheduling, and Routing in UWSNs

A Centralized Cross-Layer Protocol for Joint Power Control, Link Scheduling, and Routing in UWSNs

Cluster-Based Cross Layer-Cross Domain Routing Model with DNN-Based Energy Prediction

In WSN, extending the network life is still a major problem that needs to be tackled. Cross-layer protocols are used to get around these problems. In this paper, a new cross-layer design routing model is presented using a clustering-based technique. The proposed model is proceeding with the optimal cluster-based routing model via a new algorithm. Initially during the network generation, the node’s energy is predicted by the deep learning model termed as DNN model on the basis of the distance between node and sink as the input. Subsequently, during the clustering process, the cluster head is optimally selected via a new optimisation algorithm named Self-Improved Shuffle Shepherd Optimisation (SISSO) Algorithm. The cluster head selection is done by considering the constraints including Link quality, Distance, Overhead, Energy and Delay. Finally, a Modified Kernel Least Mean Square (MKLMS)-based data aggregation process is to eliminate the redundant data transmission. The performance of the SISSO method is proven superior over other conventional approaches with regard to the alive node and network lifetime. In the alive node analysis of supernode, the proposed SISSO model achieves the maximal number of alive supernodes at 2,000 rounds (i.e. 0.67) than other conventional methods.

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.

Investigation of Data Quality Assurance across IoT Protocol Stack for V2I Interactions

Networking protocols have undergone significant developments and adaptations to cater for unique communication needs within the IoT paradigm. However, meeting these requirements in the context of vehicle-to-infrastructure (V2I) communications becomes a multidimensional problem due to factors like high mobility, intermittent connectivity, rapidly changing topologies, and an increased number of nodes. Thus, examining these protocols based on their characteristics and comparative analyses from the literature has shown that there is still room for improvement, particularly in ensuring efficiency in V2I interactions. This study aims to investigate the most viable network protocols for V2I communications, focusing on ensuring data quality (DQ) across the first three layers of the IoT protocol stack. This presents an improved understanding of the performance of network protocols in V2I communication. The findings of this paper showed that although each protocol offers unique strengths when evaluated against the identified dimensions of DQ, a cross-layer protocol fusion may be necessary to meet specific DQ dimensions. With the complexities and specific demands of V2I communications, it’s clear that no single protocol from our tri-layered perspective can solely fulfil all IP-based communication requirements given that the V2I communication landscape is teeming with heterogeneity, where a mixture of protocols is required to address unique communication demands.

Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks

AbstractNew cell phone services and apps consume more spectrum. Wireless spectrum allows services and apps to communicate with one another. Wi‐Fi quality is improved via smart spectrum usage and new CRT services. The use of spectrum is beneficial. Cross‐layer architecture improves the energy efficiency of wireless networks. System performance is improved by connecting protocol layers. Cross‐layer configuration does not introduce layer functionality into a network. By protecting networks, cross‐layer design increases communication. C‐LNRD uses self‐determined time slots to promote communication. Agents that collect information. At each level, the monitoring agent monitors traffic, time, and topology. Each layer of agents has its own database. Data is received by the network, MAC, and physical layers. Based on its measurements, each node grants trust. Routes were altered. PR ATTACK does not have RTS, CTS, or RREQ to reduce false positives. Spectrum allocation is improved via cognitive radio and learning technologies. Adaptive Cognitive Radio Networks are created using AI, GA, Fuzzy Logic, and Game Theory (ACRN). DSA creates high‐bandwidth MCRNs. This research looks at MCRNs in order to optimise spectrum usage, throughput, routing delay, and overhead. Multihop, the proposed approach by CRN takes into account spectrum awareness, quality route establishment, and route maintenance in the event that a connection fails due to spectrum or a node transfer. New strategies improve the cross‐layer network protocols of MCRN. Learners gain from spectrum models. Sensors and routers are linked by layers. The proposed routing improves both performance and spectrum use.

A Modified DSR Protocol Using Deep Reinforced Learning for MANETS

Wireless Networks like Mobile Adhoc Networks (MANETs) have been under extensive research over the past few years with congestion control as one of the most important features to ensure efficient and fair sharing of network resources among users. Machine learning (ML) has achieved a success rate in addressing large-scale and complex problems and researchers have begun to shift their attention from the rule-based method to an ML-based approach to handle the complex needs of future networks where conventional rule-based approaches tend to become inefficient and ineffective. To handle the problems in congestion control, precise notification should be generated as the backpressure transmission process. Although backpressure-based routing algorithms give optimal throughput, they typically have poor delay performance under moderate loads. This may be because packets are being sent over longer routes unnecessarily. Furthermore, the existing backpressure-based optimisation algorithms require every node to compute differential backlogs for every destination queue with the corresponding destination queue at every adjacent node. The proposed algorithm proves to be a cross-layer protocol for wireless MANET that generalises the channel access management and routing process which includes traffic management, connection maintenance and distributed scheduling for concurrent transmission. The joint congestion control method with scheduling algorithm has enhanced active radio communication network by interchanging scheduling schema with adaptation modelling and also the optimum congestion dominance and flow control model is being designed using deep reinforced learning.

Cross-Layer Protocol Based on Directional Reception in Underwater Acoustic Wireless Sensor Networks

The long propagation delay of acoustic links leads to the complex randomness of packet collision, which reduces the network packet delivery rate (PDR) and aggravates network congestion. A single vector hydrophone with directional reception characteristics can concentrate the reception gain on a certain direction, which can increase spatial reuse, reduce packet collision, and help to improve the performance of the underwater acoustic wireless sensor networks (UASNs). Herein, this paper proposes a cross-layer protocol with low interference and low congestion (CLIC) based on directional reception. An integrated routing-medium access control (MAC) design is also devised in the CLIC scheme to use the directional beams to create the least-interfering, highest-capacity data transmission links, weighing key factors affecting network performance to obtain routes with low collisions and low congestion. Simulation results show that the CLIC has a higher packet delivery rate (PDR) and higher energy efficiency compared to the QELAR, CITP, and VBF protocols.

IRIS: A low duty cycle cross-layer protocol for long-range wireless sensor networks with low power budget

This paper presents a lightweight cross-layer protocol relIable Routing with coordInated medium acceSs control (IRIS) which is designed for long-range pipeline Wireless Sensor Networks (WSNs) with extremely low power budget, typically seen in a range of monitoring applications. IRIS includes functions of network discovery, medium access control and routing designed for heavily energy constrained networks. The protocol is able to operate with less than 1% duty cycle, thereby conforming to ISM band spectrum regulations in the 868MHz band. The duty cycle can be flexibly configured to meet other regulations/power budgets as well as to improve the route forming performance. Simulation results show a guaranteed route formation in different network topologies with various protocol configurations. An analytical model is presented to validate the simulation results of route formation time. System robustness against unreliable wireless connections and node failures are also demonstrated by simulations. A network of 71 attenuated LoRa nodes is implemented to evaluate the capability of IRIS. Long-term operation of the network shows consistent performance compare with the simulations.

Improved Congestion Control in Wireless Sensor Networks Using Clustering with Metaheuristic Approach

The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.

Cross-Layer MAC/Routing Protocol for Reliability Improvement of the Internet of Things

The IEEE 802.15.4 standard is recognized as one of the most successful for short-range low-rate wireless communications and is used in Internet of Things (IoT) applications. To improve the performance of wireless networks, interest in protocols that rely on interaction between different layers has increased. Cross-layer design has become an issue in wireless communication systems as it can improve the capacity of wireless networks by optimizing cooperation between multiple layers that constitute network systems. Power efficiency and network scalability must be addressed to spread IoT. In multi-hop networks, many devices share wireless media and are geographically distributed; consequently, efficient medium access control (MAC) and routing protocols are required to mitigate interference and improve reliability. Cross-layer design is a novel network design approach to support flexible layer techniques in IoT. We propose a cross-layer protocol for the MAC layer and routing layer to satisfy the requirements of various networks. The proposed scheme enables scalable and reliable mesh networking using the IEEE 802.15.4 standard and provides robust connectivity and efficient path discovery procedures. It also proposes a novel address-allocation technique to improve address-allocation methods that cannot support large sensor networks. Simulation results indicate that the proposed scheme could improve reliability and reduce end-to-end delay.

Quality of Service-Based Cross-Layer Protocol for Wireless Sensor Networks

Sensor nodes in wireless sensor networks (WSN) are used for perceiving, monitoring, and controlling a wide range of applications. Owing to the small size of sensor nodes and limited power sources, energy saving is critical for ensuring network longevity. Protocols in different layers consume energy for their function. It is possible to significantly reduce energy usage by including energy-efficiency measures in the protocol design. Most protocols in the literature focus on the energy efficiency in individual layers. Recent studies have shown that cross-layer designs are more energy efficient than individual layer designs. Therefore, this study presents a cross-layer protocol design that combines network and data link layers to minimize energy consumption. This article proposes a novel "Quality of Service Based Cross-layer (QSCL) Protocol" by combining the IEEE 802.15.4-based MAC protocol and the LEACH-based routing protocol. The dynamic duty cycle of the IEEE 802.15.4 protocol was modified based on the amount of data present in the node, which minimized the energy consumption of the data-transfer mechanism. The cluster head (CH) selection of the LEACH-based protocol was modified to consider the average residual energy (RE) of the nodes and their distance from the sink. This helps preserve the energy in the CH, thereby extending the network lifetime. Simulation studies demonstrated that the proposed QSCL outperformed the existing protocols by prolonging the network lifetime.

Data Gathering in UWA Sensor Networks: Practical Considerations and Lessons from Sea Trials

Underwater acoustic (UWA) network protocol design is a challenging task due to several factors, such as slow propagation of acoustic waves, low frequency bandwidth and high bit error and frame error rates often encountered in real UWA environments. In this paper, we consider the design of a robust and scalable data gathering protocol for UWA sensor networks (UASNs), focusing on practical considerations and lessons learnt from multiple lake and sea trials. A cross-layer protocol is presented that integrates a network discovery process, intelligent routing, scheduling via Transmit Delay Allocation MAC (TDA-MAC) and multi-node Automatic Repeat Request (ARQ), to facilitate reliable data gathering in practical UASN deployments. Furthermore, this paper presents the details of a novel experimental testbed and underwater sensor node prototype that were used for the trials reported in this study. Based on the results of the trials, important conclusions are drawn on the protocol features required to achieve reliable networked communication in realistic UWA environments. The insights gained from the trials are valuable both for further development of the proposed data gathering protocol, and for the wider UWA networking research community concerned with developing practical solutions for real-world UASN deployments.

Congestion Aware MANET Routing Using Evolutionary Game Theory and Cross-Layer Design

A wireless network without infrastructure is called MANET. In MANET, a node can move in any direction, at any speed, and at any time. There is no separate router on this network. Instead, the nodes act as a router. To transfer data in the network in an efficient manner, the network should be congestion-free or less congested. If the network has congestion, it would affect the performance of the network. In the routing process, if a node is aware of the neighbour node’s congestion and selects a congestion-free path, it leads to better performance of the network. In this paper, we have designed two approaches for improving the performance of the network. One is the cross-layer protocol and the other is the evolutionary game theory approach to find the least congestion path. Cross-layer involves transport layer and MAC layer of MANET to avoid congestion. The Linear Rank Selection method is one of the evolutionary game theory approaches used to find the Least Congested Node. We have enhanced this strategy in the GPSR protocol. The proposed EVO GPSR protocol performs 4.65% better throughput, 0.54% less network delay, 2.10% less routing overhead, and 8.20% better packet delivery ratio compared with GPSR protocol. Based on simulation, the performance of the proposed protocol is better than the GPSR protocol.

Design of fieldable cross-layer optimized network using embedded software defined radios: Survey and novel architecture with field trials

The proliferation of wireless devices and their ever increasing influence on our day-to-day life is very evident and seems irreplaceable. This exponential growth in demand, both in terms of the number of devices and Quality of Service (QoS) had spawned the concept of cross-layer optimization several years ago. The primary goal of the cross-layer approach was to liberate the strict boundary between the layers of the traditional Open Systems Interconnection (OSI) protocol stack. The objective was to enable information flow between layers which then can be leveraged to optimize the network’s performance across the layers mitigating the challenges due to scarce resources while meeting QoS demands. The initial decade focused on establishing the theoretical feasibility of this revolutionary concept and gauging the effectiveness and limits of this idea. During the next phase, the advent of software defined radios (SDR) accelerated the growth of this domain due to its added flexibility. Even with the immense interest and progress in this area of research, there has been a gaping abyss between solutions designed in theory and ones deployed in practice. To establish this, we first present an elaborate survey of the cross-layer protocol stack literature with emphasis on their maturity scale. Next, we briefly discuss how a commercial off-the-shelf (COTS), low SWaP (Size, Weight, and Power) embedded SDR (e-SDR) was transformed into a standalone, fieldable transceiver. Thereafter, we provide the software design ethos that focuses on efficiency and flexibility such that the optimization objectives and cross-layer interactions can be reconfigured rapidly. To demonstrate our claims, we provide results from extensive outdoor over-the-air experiments in various settings with up to 10-node network topologies. The results from the field trials demonstrate high reliability, throughput, and dynamic routing capability. To the best of our knowledge, this is the first time in literature, a COTS e-SDR has been leveraged to successfully design a cross-layer optimized transceiver that is capable of forming an ad hoc network that provides high throughput and high reliability in a ruggedized, weatherized, and fieldable form factor.

Optimized Distributive Cross-Layer and Thermal-Aware Convergecast Protocol for Wireless Body Area Network

The Internet of Healthcare Things has significantly altered traditional patient-doctor relationships by allowing essential healthcare treatment from the comfort of one’s home. The wireless body area network is an IEEE 802.15.6 standard that focuses on healthcare data, necessitating various cross-layer and thermal-aware protocols. However, most cross-layer protocols have long convergence delays and a single failure point. Moreover, these protocols exploit excessive broadcasts and handshake acknowledgments, causing communication and processing overheads. Furthermore, thermal-aware protocols focus on thermal variations, disperse data collection, and do not support cross-layer techniques. To address these limitations, this study proposes an optimal distributive cross-layer and thermal-aware convergecast protocol. The proposed protocol enforces a novel hybrid convergecast using probability and both minimum attenuation strategies to collect data from leaf nodes to the root to improve data flow and adaptability in the network. In addition, it accelerates the convergence process by reducing recurrent broadcasts and unnecessary acknowledgments, resulting in improved energy efficiency and thermal control. The proposed protocol supports a distributive hierarchy by establishing multiple parent-child relationships to avoid a single root point failure. A multi-parameter maximum benefit-cost function calculates the next hop according to the extracted weights. Packet loss probability validates the number and sequence of packets received at the sink node. The simulation results demonstrate that cross-layer and thermal-aware protocols can coexist effectively. The proposed protocol reduces delays to 19.4%, improves throughput from 8% to 13.75%, and retains a packet loss probability of 0.3% by keeping the thermal rise within bounds.

Iris: A Low Duty Cycle Cross-Layer Protocol for Long-Range Wireless Sensor Networks with Low Power Budget

This paper presents a cross-layer protocol (IRIS) designed for long-range pipeline Wireless Sensor Networks with extremely low power budget, typically seen in a range of monitoring applications. IRIS uses ping packets initiated by a base station to travel through the multi-hop network and carry monitoring information. The protocol is able to operate with less than 1% duty cycle, thereby conforming to ISM band spectrum regulations in the 868MHz band. The duty cycle can be flexibly configured to meet other regulations/power budgets as well as to improve the route forming performance. Simulation results show guaranteed route formation in different network topologies with various protocol configurations. System robustness against unreliable wireless connections and node failures are also demonstrated by simulations.

Secure Physical Layer Network Coding versus Secure Network Coding.

When a network has relay nodes, there is a risk that a part of the information is leaked to an untrusted relay. Secure network coding (secure NC) is known as a method to resolve this problem, which enables the secrecy of the message when the message is transmitted over a noiseless network and a part of the edges or a part of the intermediate (untrusted) nodes are eavesdropped. If the channels on the network are noisy, the error correction is applied to noisy channels before the application of secure NC on an upper layer. In contrast, secure physical layer network coding (secure PLNC) is a method to securely transmit a message by a combination of coding operation on nodes when the network is composed of set of noisy channels. Since secure NC is a protocol on an upper layer, secure PLNC can be considered as a cross-layer protocol. In this paper, we compare secure PLNC with a simple combination of secure NC and error correction over several typical network models studied in secure NC.

Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications

Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless data communication. Nowadays the WSN has become ubiquitous. WSN is used in combination with Internet of Things and in many Big Data applications, it is used in the lower layer for data collection. It is deployed in combination with several high end networks. All the higher layer networks and application layer services depend on the low level WSN in the deployment site. So to achieve energy efficiency in the overall network some simplification strategies have to be carried out not only in the Medium Access Control (MAC) layer but also in the network and transport layers. An energy efficient algorithm for scheduling and clustering is proposed and described in detail. The proposed methodology clusters the nodes using a traditional yet simplified approach of hierarchically sorting the sensor nodes. Few important works on cross layer protocols for WSNs are reviewed and an attempt to modify their pattern has also been presented in this paper with results. Comparison with few prominent protocols in this domain has also been made. As a result of the comparison one would get a basic idea of using which type of scheduling algorithm for which type of monitoring applications.