Proposed Cross-layer Approach Research Articles

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.

A Cross-Layer Approach for Optimization of MolCom Systems Toward the Internet of Bio-NanoThings

Inspired by conventional communication network protocols, a cross-layer approach for the optimization of nanonetwork-based molecular communication (MolCom) systems toward the Internet of Bio-NanoThings is presented in this study. According to the proposed molecular-layered architecture, a molecular link layer-based xor biomolecular switch adopts the transmission rate of a molecular frame for transmission in the next frame, based on the available molecular information in a physical layer. Owing to the MolCom environment dynamics, the frame transmission rate is optimized by computing the bond throughput and is efficiently processed at receiver nanomachines. The performance of the proposed cross-layer approach is modulated by adopting the enzymatic feedback signaling. Additionally, we develop the analysis of the proposed cross-layer approach by using queueing system in terms of molecular frame loss rate. The numerical results, such as the average time delay delivery of molecular frame and the tolerant traffic rate, reveal that the proposed cross-layer approach improves the nanonetwork-based MolCom system considerably.

Cross-Layer Approach Based Energy Minimization for Wireless Sensor Networks

Prolonging the network lifetime is a crucial constraint in wireless sensor networks. Since data communication requires a more energy consumption than any other process, sensor nodes necessitate an energy efficient communication. Most related works generally consider the propagation path loss model to capture the channel effects for the energy consumption model and the routing metric choice. Nevertheless, this model does not incorporate the small-scale fading. Thus, it is inaccurate to evaluate link reliability. In this paper, we derive the analytical expression of the energy consumption by including the small-scale channel fading and its impact on energy efficiency. Then, we propose a cross-layer approach based on joint network and physical layers by including small and large scale fading. We improve the ad hoc on-demand distance vector protocol at the route discovery mechanism and the data transmission by considering both SNR and residual energy thresholds, and a power adjustment algorithm. Simulation results show that the proposed cross-layer approach significantly prolongs the network lifetime while guaranteeing a communication efficiency level.

WiFlix: Adaptive Video Streaming in Massive MU-MIMO Wireless Networks

We consider the problem of simultaneous on-demand streaming of stored video to multiple users in a multicell wireless network where multiple unicast streaming sessions are run in parallel and share the same frequency band. Each streaming session is formed by the sequential transmission of video “chunks,” such that each chunk arrives into the corresponding user playback buffer within its playback deadline. We formulate the problem as a network utility maximization (NUM) where the objective is to fairly maximize users’ video streaming quality of experience (QoE) and then derive an iterative control policy using Lyapunov optimization, which solves the NUM problem up to any level of accuracy and yields an online protocol with control actions at every iteration decomposing into two layers interconnected by the users’ request queues : 1) a video streaming adaptation layer reminiscent of dynamic adaptive streaming over HTTP (DASH), implemented at each user node; and 2) a transmission scheduling layer where a max-weight scheduler is implemented at each base station. The proposed chunk request scheme is a pull strategy where every user opportunistically requests video chunks from the neighboring base stations and dynamically adapts the quality of its requests based on the current size of the request queue. For the transmission scheduling component, we first describe the general max-weight scheduler and then particularize it to a wireless network where the base stations have multiuser multiple-input multiple-output (MU-MIMO) beamforming capabilities. We exploit the channel hardening effect of large-dimensional MIMO channels (massive MIMO) and devise a low complexity user selection scheme to solve the underlying combinatorial problem of selecting user subsets for downlink beamforming, which can be easily implemented and run independently at each base station. Furthermore, through simulations, we show that deploying MU-MIMO significantly improves video streaming performance and also that the proposed cross-layer approach is able to serve users more fairly than a baseline scheme representative of current systems running independently designed protocol layers.

Correlation‐aware cross‐layer design for network management of wireless sensor networks

The observations of the nodes of a wireless sensor network are spatiotemporally correlated. Sensor nodes can exploit the correlation for enhancing network efficiency. However, an energy-efficient collaboration is required for better network management. For saving energy, sensor nodes schedule between Active and Sleep states. Nodes extract information from medium access control layer, and use that information along with the correlation of observations as a means of energy-efficient collaboration and proper scheduling of their Active and Sleep states. Furthermore, sensor nodes use non-deterministic reinforcement learning-based approach for reducing energy consumption and end-to-end delay by regulating the duration of their Sleep states. Extensive simulations have shown that the proposed cross-layer approach outperforms existing benchmark schemes in terms of end-to-end delay, data accuracy and energy efficiency.

MANET에서 비디오 전송 품질을 위한 Cross-layer 시뮬레이션과 분석

MANET(Mobile ad hoc networks)은 이동 단말로 구성된 동적인 자가 생성 네트워크를 의미한다. 본 연구에서는 MANET에서 비디오 전송 서비스를 다루고 있는 최근 연구를 보완하기 위한 개선된 cross-layer 접근 방법을 제시하고 있다. 본 연구는 ns-3 시뮬레이션을 통해 수행되며, 시뮬레이션에 소요되는 시간을 감안하여 효율적으로 각 계층의 주요 인자의 상호작용을 동시에 고려하기 위해 통계적 실험계획법을 활용하고자 한다. 제안된 cross-layer 접근 방법은 MANET 프로토콜 계층(물리, 네트워크, 전송 계층)과 응용 계층(비디오 인코더)를 동시에 인자로 다루고 있고, 반응 변수로는 객관적 비디오 품질 지표를 포함한다. 본 연구의 결과는 통제 불가능한 인자의 값에 따라 통제 가능한 인자를 설정하여 최적의 비디오 품질을 제공하는 MANET 비디오 전송 어플리케이션을 설계하는 기초 연구로써 활용될 수 있다. Mobile ad hoc networks (MANETs) are self-organized dynamic networks populated by mobile nodes. This paper presents the improved cross-layer approach to complement the recent works for video transmission services on MANET. We use a statistical design of experiment and analysis in order to investigate interactions between major factors of each layer effectively with minimizing ns-3 simulation run time. The proposed cross-layer approach considers MANET protocol layers (i.e., physical, network and transmission layers) and an application layer (i.e., a video encoder) as factors simultaneously. In addition, the approach defines an objective video quality metric as a response variable. The result of this paper can be applicable as a preliminary research to design an optimized video transmission application which has ability to adjust controllable factors to dynamic uncontrollable factors.

Cross Layer Design Approach to Enhance the Quality of Service in Mobile Ad Hoc Networks

The infrastructure-less and dynamic nature of mobile ad hoc networks demands a new set of networking strategies to improve the performance of quality of service (QoS). Providing QoS is a major issue in Manets. The traditional layered approach does not fit well for ad hoc networks due to high mobility and dynamic topology. This paper implements the cross layer design approach on DYMO routing protocol in Manets by using Qualnet simulator in both traditional layered approach and proposed cross layer approach. The proposed methodology uses four QoS metrics: throughput, end-to-end delay, packet delivery ratio and jitter. The experimental result reveals that QoS performance is enhanced in CLD approach for DYMO. The throughput in traditional layered approach for DYMO is 1961 b/s, whereas in the CLD approach it is 2986 b/s. Finally this paper concludes that cross layer approach significantly improves the QoS performance when compared with layered approach.

HEC-MAC: A Hybrid Energy-Aware Cross-Layer MAC Protocol for Wireless Sensor Networks

Wireless Sensor Networks are a key element of the Internet of Things since they are one of the most interesting pervasive systems. However, they are battery-powered, so energy efficiency represents one of the primary design challenges to address. This goal can be primarily achieved through an optimization of the communication procedure, which is the most power-consuming component of a WSN node. Nevertheless, the poor resources of the embedded devices usually limit the complexity of protocol solutions, which thus are not sufficient to reach satisfactory results. For this reason, the current trend aims at integrating both hardware and software solutions. In this work, a cross-layer solution, based on the combined use of a duty-cycling MAC protocol and a reconfigurable beam-steering antenna, is presented and validated. It significantly reduces the nodes' power consumption by exploiting scheduling techniques and directional communications. Specifically, a MAC scheduler manages the activation of the antenna sectors based on information coming from both MAC and network layers. This way, node awakenings occur only when an actual communication has to take place and only the interested antenna sector is activated. The effectiveness of the proposed cross-layer approach has been evaluated through OMNeT++ simulation tool.

A cross-layer approach to timely responsive transmission under collection tree topology in wireless sensor network

Collection tree protocol CTP provides a link quality-based routing schema for wireless sensor networks WSNs with a collection tree topology, under which the link quality is measured by throughput rather than transmission latency. Yet it is not appropriate for the applications that need to transmit packets in a timely manner. Furthermore, implementation of timely responsive service in WSNs demands real-time supports from both routing and transport control layer. In this paper, we propose a cross-layer approach in which the packets with transmission deadlines are routed via an average transmission time ATT protocol and the congestion control is imposed through a performance-differentiated packet dropping policy. Simulation experiments on the TinyOS platform show that ATT protocol outperforms CTP by reducing the transmission delay up to 17.7%, while maintains a slightly better transmission reliability measured by the packet loss rate. The proposed cross-layer approach presents a promising core feature of framework in delivering real-time service in WSNs.

A Cross-Layer QoE-Based Approach for Event-Based Multi-Tier Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) are attracting attention from both academic and industrial environments due to the rapid development of low-cost multimedia sensors. With the enhancement of the multimedia content captured by multimedia devices, WMSNs play an important role in pervasive and ubiquitous systems. The multimedia content in these networks has the potential to enhance the level of collected information, by enlarging the range of coverage, and enabling multi-view support. In the case of WMSN applications, the multi-tier network architecture has proved to be more beneficial than single-tier architecture in terms of energy-efficiency, scalability, functionality and reliability. In this context, a multimedia event detection application is a promising application for multi-tier WMSNs, where the lower-tier nodes detect an event occurrence by means of scalar measurements, and the higher-tier nodes will be woken up to send real-time video flows from the event area. The transmission of multimedia content requires a certain quality level from the user's perspective, while energy consumption and network overhead should be minimized. Among the existing mechanisms for improving video transmissions, application-level Forward Error Correction (FEC) is regarded as a suitable solution to improve video quality level from the user´s standpoint. In this work, the authors propose an adaptive cross-layer approach, which includes a Quality of Experience (QoE)-aware FEC mechanism for WMSNs by generating redundant packets, based on frame importance from user's experience. Additionally, the aothors introduce a multi-tier routing protocol to select the best route to transmit multimedia data. According to the simulation results, the proposed cross-layer approach achieved high video quality level with reduced transmission of redundant packets, which will bring many benefits to a resource-constrained system.

The Effects of Physical Layer on the Routing Wireless Protocol

Mobile ad hoc networks (MANETs) are characterized by multiple entities, a frequently changing network topology and the need for efficient dynamic routing protocols. In MANETs, nodes are usually powered by batteries. Power control is tightly coupled with both the physical and medium access layers (MACs). However, if we increase the transmission power, at the same time we increase the interference to other nodes which diminish the transport capacity of wireless systems. Thus, the routing protocols based on hop count metric suffer from performance degradation when they operate over MANET. Routing in ad hoc wireless networks is not only a problem of finding a route with shortest length, but it is also a problem of finding a stable and good quality communication route in order to avoid any unnecessary packet loss. Cross-layer design of ad hoc wireless networks has been receiving increasing attention recently. Part of these researches suggests that routing should take into account physical layer characteristics. The goal of this paper is to improve the routing reliability in MANET and to reduce power consumption through cross-layer approach among physical, MAC and network layers. The proposed cross-layer approach is based on signal to interference plus noise ratio (SINR) and received signal strength indication (RSSI) coming from the physical layer. This solution performs in one hand the ad hoc on-demand distance vector routing protocol by choosing reliable routes with less interferences using SINR metric and in another hand; it permits to reduce the power transmission when sending the data packets by using RSSI metric.

Revealing of Reducing Manners in Ad Hoc Networks with Crosslayer Approach Using SVM and FDA in Distributed Architecture

Ad hoc network is a structure less network with independent nodes. In the ad hoc network, the nodes have to cooperate for services like routing and data forwarding. The routing attacks in ad hoc networks have given rise to the need for designing novel intrusion detection algorithms, different from those present in conventional networks. In this work, distributed intrusion detection system (IDS) have proposed for detecting malicious sinking behavior in ad hoc network. Detection process of that sinking behavior node is very important to do the further forwarding process in network. Intrusion detection system use linear classifiers for training the intrusion detection model. Cross -layer approach is involved to increase the accuracy of intrusion detection process in ad hoc network. A machine learning algorithm in non linear manner named as Support Vector Machine (SVM) involved for training the detection system and used together with Fisher Discriminant Analysis (FDA). The proposed cross-layer approach aided by a combination of SVM and FDA reduces the feature set of MAC layer without reducing information content.

Improving playout rate of streaming service with power efficiency over wireless multihop networks

There is a trade-off problem between power consumption and streaming service quality over the wireless multihop networks. If the transmission power increases to overcome the bad link condition, the quality of streaming service can improve, but it can stress the other links and deplete the battery power of nodes. However, since the existing algorithms for streaming services do not consider this trade-off problem, streaming service quality cannot be guaranteed with the high power efficiency. In this study, the authors formulate the optimisation problem to solve the trade-off problem. Then, the authors propose a new cross-layer algorithm to achieve the derived optimal solution. The proposed cross-layer approach covers three layers: application layer, transport layer and physical layer. The newly proposed cross-layer algorithm not only avoids the underflow and the overflow of the decoder buffer, but also achieves the high playout rate and the high power efficiency. Through simulation results, it is shown that the proposed algorithm achieves the high and smooth playout rate with the high power efficiency.

Cross-Layer Detection of Sinking Behavior in Wireless Ad Hoc Networks Using SVM and FDA

The uniqueness of security vulnerabilities in ad hoc networks has given rise to the need for designing novel intrusion detection algorithms, different from those present in conventional networks. In this work, we propose an autonomous host-based intrusion detection system for detecting malicious sinking behavior. The proposed detection system maximizes the detection accuracy by using cross-layer features to define a routing behavior. For learning and adaptation to new attack scenarios and network environments, two machine learning techniques are utilized. Support Vector Machines (SVMs) and Fisher Discriminant Analysis (FDA) are used together to exploit the better accuracy of SVM and faster speed of FDA. Instead of using all cross-layer features, features from MAC layer are associated/correlated with features from other layers, thereby reducing the feature set without reducing the information content. Various experiments are conducted with varying network conditions and malicious node behavior. The effects of factors such as mobility, traffic density, and the packet drop ratios of the malicious nodes are analyzed. Experiments based on simulation show that the proposed cross-layer approach aided by a combination of SVM and FDA performs significantly better than other existing approaches.

An adaptive cross-layer mapping algorithm for MPEG-4 video transmission over IEEE 802.11e WLAN

This paper proposes an adaptive cross-layer mapping algorithm to improve the transmission quality of MPEG-4 video stream over an IEEE 802.11e wireless network. Instead of classifying video data to a specific access category in an 802.11e network, we propose an algorithm that dynamically maps MPEG-4 video packets to appropriate access categories according to both the significance of the video data and the network traffic load. Our proposed cross-layer architecture passes information about the significance of video packets from the application layer to the media access control layer. The queue length of a specific access category is used to deduce the network traffic load. We conducted a performance evaluation of our proposed cross-layer approach under both light and heavily loaded network conditions. Our simulation results demonstrate: (a) superior performance of our proposed approach (under both light and heavy loads) over 802.11e (Enhanced Distributed Channel Access (EDCA) and static mapping schemes, (b) not only guarantees prioritized transmission of essential video data but also provides efficient queue length utilization.

Cross-layer resource allocation for integrated Voice/Data traffic in wireless cellular networks

A major task in next-generation wireless cellular networks is provisioning of quality of service (QoS) over the bandwidth limited and error-prone wireless link. In this paper, we propose a cross-layer design scheme to provide QoS for voice and data traffic in wireless cellular networks with differentiated services (DiffServ) backbone. The scheme combines the transport layer protocols and link layer resource allocation to both guarantee the QoS requirements in the transport layer and achieve efficient resource utilization in the link layer. Optimal resource allocation problems for voice and data flows are formulated to guarantee pre-specified QoS with minimal required resources. For integrated voice/data traffic in a cell, a hybrid time-division/code-division medium access control (MAC) scheme is presented to achieve efficient multiplexing. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed cross-layer approach.