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Remote Direct Memory Access (RDMA) is a widely adopted optimization strategy in datacenter networking that surpasses traditional kernel-based TCP/IP networking through mechanisms such as kernel bypass and hardware offloading. However, RDMA also faces a scalability challenge with regard to connection management due to limited on-chip memory capacity in the RDMA Network Interface Card (RNIC). This necessitates the storage of connection context within RNIC's memory and induces considerable performance degradation when maintaining a large number of connections. In this paper, we propose a novel RNIC microarchitecture design that achieves peak performance and scales well with the number of connections. First, we model RNIC and identify two key factors that degrade performance when the number of connections grows large: head-of-line blocking when accessing the connection context and connection context dependency in transmission processing. To address the head-of-line blocking problem, we then combine a non-blocking connection requester and connection context management module to process prepared connections first, which achieves peak message rate when the number of connections grows large. Besides, to eliminate connection context dependency in RNIC, we deploy a latency-hiding connection context scheduling strategy, maintaining low latency when the number of connections increases. We implement and evaluate our design, demonstrating its successful maintenance of peak message rate (66.4 Mop/s) and low latency (3.89 µs) while scaling to over 50,000 connections with less on-chip memory footprint. [ABSTRACT FROM AUTHOR]

Aiming at the specific target search and controllable angle guidance of unmanned surface ships in uncertain waters, this paper explores the target detection method based on YOLO and the guidance control method based on side angle constraint. On the basis of analyzing the uncertain conditions such as sea fog, the paper designs the correlation filter with im- proved YOLOv5 algorithm to extract the target features, combines depth information to realize the detection and positioning of water surface targets, sliding mode variable structure guidance control to achieve the high maneuverability target side angle constraint guidance. TCP/IP combined with ROS is used to create a comer constrained terminal guidance system for information processing. Two-dimensional simulation experiment is completed with Autolabor platform, and the result of target guidance error is 1.54%, which proves the effectiveness of the method proposed. [ABSTRACT FROM AUTHOR]

In this paper we derive mathematical description of TCP (Transmission Control Protocol) retransmission probability based on Jacobson’s smoothing algorithm that belongs to EWMA (Exponentially Weighted Moving Average) category. This description is parametrized on the probability density function (pdf) of RTT (Round Trip Time) samples and α, β – two primary parameters of Jacobson’s algorithm. Although it is not a close form expression, it is formulated as an effective algorithm that let us to explicitly calculate the values of RTO (Retransmission Time Out) probability as a function of α, β and the pdf of RTT samples. We achieve the effectiveness of this approach by applying smart discretization of the state space and replacement of continuous functions with discrete approximate equivalents. In this way, we mitigate the cardinality of discrete distributions we deal with that results in linear (n+m) instead of multiplicative (n⋅m) growth of computational complexity. We provide the evaluation of RTO probability for a wide set of α, β parameter values and differently shaped Normal and Laplace pdfs the RTT samples are taken from. The obtained numerical results let us to draw some conclusions regarding the choice of optimal values of α, β parameters as well as the impact of pdf the RTT samples are taken from. [ABSTRACT FROM AUTHOR]

Traditionally, reading of energy meters is done by human operators who move from house to house collecting readings. This exercise requires huge labor operator numbers and a lot of time to achieve complete reading of meters in a particular area. This paper endeavors to do away with this problem by using a telemetering system. With this system, power can be measured from a remote site. To achieve this, readings from an energy meter on site are processed by a microcontroller device that then sends the energy consumption information to a Global System Mobile (GSM) module. The GSM module then sends this information using microwaves to a particular mobile subscriber who receives it in the form of an Short Message Service (SMS). The reading is also transmitted to a web based telemetering system through a server. In the remote site, a remote computer which can access the internet is able to obtain data from the server through the internet. The microcontroller is developed in such a way that it achieves communication between the energy meter and the particular server using Transmission Control Protocol(TCP) protocol. Software programs are also developed to facilitate transfer of data to the user at remote site. With the web based telemetering system connected to the internet, electrical energy measurements can be accessed globally. The efficiency of the transmission channel is important for the success of both SMS and web based telemetering systems. [ABSTRACT FROM AUTHOR]

This paper presents the development and implementation of a remote user interface for the ABB robot using the TCP/IP protocol. The study focuses on building a user-friendly interface in Matlab environment that enables precise and secure control of the robot's operation with an educational support role in teaching the basics of robotics. The remote application offers a simple and intuitive controlling mode, providing users with a firsthand experience of the robot's capabilities through predetermined actions. Additionally, the advanced mode allows users to test the robot's functionality and perform simple tasks. The use of asynchronous communication contributes to the stability and performance of the remote control application. [ABSTRACT FROM AUTHOR]

Indoor human action recognition, essential across various applications, faces significant challenges such as orientation constraints and identification limitations, particularly in systems reliant on non-contact devices. Self-occlusions and non-line of sight (NLOS) situations are important representatives among them. To address these challenges, this paper presents a novel system utilizing dual Kinect V2, enhanced by an advanced Transmission Control Protocol (TCP) and sophisticated ensemble learning techniques, tailor-made to handle self-occlusions and NLOS situations. Our main works are as follows: (1) a data-adaptive adjustment mechanism, anchored on localization outcomes, to mitigate self-occlusion in dynamic orientations; (2) the adoption of sophisticated ensemble learning techniques, including a Chirp acoustic signal identification method, based on an optimized fuzzy c-means-AdaBoost algorithm, for improving positioning accuracy in NLOS contexts; and (3) an amalgamation of the Random Forest model and bat algorithm, providing innovative action identification strategies for intricate scenarios. We conduct extensive experiments, and our results show that the proposed system augments human action recognition precision by a substantial 30.25%, surpassing the benchmarks set by current state-of-the-art works. [ABSTRACT FROM AUTHOR]

Since Transmission Control Protocol (TCP) is the dominant protocol on the Internet and optical burst switching (OBS) networks represent the optical transmission solution that can meet future high bandwidth requirements, TCP and OBS networks represent a possible combination for the next-generation Internet. However, a problem with this combination model is that operations at the OBS layer need to be controlled so that false congestion detection at the TCP layer is minimised. Considering the combination of TCP Vegas and OBS, congestion detection at the TCP layer is based on the round-trip time (RTT), where congestion is detected if the current RTT exceeds a given RTTmax. The extra delay may be due to some actual loss, but it may also be due to the extended execution time caused by some OBS layer operations. Therefore, reducing the time of operations at the OBS layer will reduce false congestion detection at the TCP layer. This paper investigates the impact of reducing the buffering time at the ingress node on the false congestion detection rate at the TCP layer. The reduction of the burst buffering time is accomplished by nesting the offset time in the assembly time. The simulation results and analysis show that the transmission efficiency in TCP Vegas over OBS networks is significantly improved; the throughput remains high, and the delivery success rate is significantly increased compared to the conventional buffering mode. [ABSTRACT FROM AUTHOR]

In the recent past, Distributed Denial of Service (DDoS) attacks have become more abundant and present one of the most serious security threats. In a DDoS attack, the attacker controls a botnet of daemons residing in vulnerable hosts that send a significant amount of traffic to flood the victim or the network infrastructure. In this paper, a common type of DDoS attacks known as "TCP SYN-Flood" is studied. This type of attack uses spoofed Internet Protocol (IP) addresses for SYN packets by exploiting the weakness in Transmission Control Protocol (TCP) 3-Way handshake used by the TCP/IP suite of protocols, which make the web servers unreachable for legitimate users or even worse, it might lead to server crash. In this paper, a resilient, efficient, lightweight, and robust IP traceback algorithm is proposed using an IP tracing packet for each attack path. The proposed algorithm suggests that edge routers—where the attack starts from—observe the traffic pattern passing through, and if the observed traffic carries the signature of TCP SYN-Flood DDoS attack and a high percentage of it is destined to a particular web server(s), it starts the tracing process by generating an IP trace packet, which accompanies the attack path recording the routers' IP addresses on the path between the attacker/daemon and the victim, which can extract the path and react properly upon receiving it by discarding any SYN packets originating from that attacker/daemon. To our knowledge, this is the first research that efficiently traces these kinds of attacks while they are running. The proposed solution has low computation and message overhead, efficient detection and tracing time, and converges in near optimal time. The results are validated using extensive simulation runs. [ABSTRACT FROM AUTHOR]

Nowadays, various systems were developed in the telecommunications field which make use of technologies for the transmission and reception of information. One of these technologies is the Internet, which was developed in tandem with scientific growth. Therefore, its application in the control of various industrial processes has a notable influence. In this context, there are industrial processes that, due to the potential danger they represent to human beings, must be controlled by means of a remote control system. Such systems can be implemented through client–server communication schemes, which form a network of computers to exchange information. In the exchange of information, delay times are generated. These inactivity times have a close relationship with the latency in the communication network and have a negative impact on the performance of closed-loop control systems. In this sense, for physical implementation, it is essential to measure and mathematically characterize their magnitudes in order to know their variability and thus be able to design control strategies that compensate for their effects. Hence, this research paper presents the reconstruction of the communication times measured from a telecontrol system, where it is assumed that only one subsystem acts as the controller and the other one acts as the controlled. In other words, this paper addresses a control scheme type of single-input-single-output system (SISO). This reconstruction is based on the Kalman filter, which estimates the communication times that are measured on an experimental test bench with a client–server communication scheme. Communication times are characterized as stochastic processes. So, in order to validate the reconstruction presented, the level of dependence between the random processes is evaluated by analyzing their moments of probability as well as their covariance moments. Finally, an analysis based on the mean square error is presented, through which it can be concluded that the reconstruction technique used allows one to know the dynamics of the communication times generated by the remote control process presented in this research. [ABSTRACT FROM AUTHOR]

MQ Telemetry Transport (MQTT) has been designed and developed for an ultra-low bandwidth communication and has been applied to used in Internet of Things (IoT). Recently, MQTT has been used in traditional TCP/IP networks. Yet, the ultra-low bandwidth and long-range communication of MQTT have been considerably increased. Previous proposed techniques still struggle to make MQTT compatible with Long-Range (LoRa) networks. In this paper, we have design and implement the Telemetry Media Access Control (TMAC). Our TMAC helps increase ranges of MQTT's data communications. We have experimented our TMAC using a network testbed. Experimental results have illustrated that our TMAC can transfer data over 5 kilometers with low network overhead. [ABSTRACT FROM AUTHOR]

Today, Internet of things (IoT), Cloud and Fog networks have spread out around the world. The more these networks grow, the more their energy consumption comes to attention. Many efforts have been made during recent years to decrease this energy consumption, mainly focused on utilizing low‐power devices. Green algorithms are recently proposed to reduce energy consumption by modifying the structure of many algorithms employed in the network and its protocols. This paper proposes a new green reliability algorithm for Transmission Control Protocol/Internet Protocol (TCP/IP protocol) in Fog computing. The proposed algorithm does not require extensive TCP/IP protocol changes or relevant hardware. It is based on transferring less number of packets in the network by using the advantage of differences between TCP and User Datagram Protocol (UDP). TCP and User Datagram Protocol (UDP) are different in nature as the number of total packets in UDP is half that of TCP. As a result, the number of complete packets in UDP is half that of TCP. The proposed method is built around the loss of some packets in applications, such as voice and online video, does not severely degrade the end results. Therefore, the UDP protocol can substitute TCP in such situations. The criterion to switch between the two is the minimum acceptable Quality of Service (QoS) of the overall network. In other words, the UDP protocol will be used as long as QoS requirements are met. The switching process between UDP and TCP is dynamic, optimized by estimating network noise in the period. Additionally, we evaluated the proposed method based on several QoS functions, including delay, throughput, and energy usage. [ABSTRACT FROM AUTHOR]

This study illustrates the utility and effectiveness of machine learning algorithms in identifying dependencies in data transmitted in industrial networks. The analysis was performed for two different algorithms. The study was carried out for the XGBoost (Extreme Gradient Boosting) algorithm based on a set of decision tree model classifiers, and the second algorithm tested was the EBM (Explainable Boosting Machines), which belongs to the class of Generalized Additive Models (GAM). Tests were conducted for several test scenarios. Simulated data from static equations were used, as were data from a simulator described by dynamic differential equations, and the final one used data from an actual physical laboratory bench connected via Modbus TCP/IP. Experimental results of both techniques are presented, thus demonstrating the effectiveness of the algorithms. The results show the strength of the algorithms studied, especially against static data. For dynamic data, the results are worse, but still at a level that allows using the researched methods to identify dependencies. The algorithms presented in this paper were used as a passive protection layer of a commercial IDS (Intrusion Detection System). [ABSTRACT FROM AUTHOR]

The TCP protocol is a connection-oriented and reliable transport layer communication protocol which is widely used in network communication. With the rapid development and popular application of data center networks, high-throughput, low-latency, and multi-session network data processing has become an immediate need for network devices. If only a traditional software protocol stack is used for processing, it will occupy a large amount of CPU resources and affect network performance. To address the above issues, this paper proposes a double-queue storage structure for a 10G TCP/IP hardware offload engine based on FPGA. Furthermore, a TOE reception transmission delay theoretical analysis model for interaction with the application layer is proposed, so that the TOE can dynamically select the transmission channel based on the interaction results. After board-level verification, the TOE supports 1024 TCP sessions with a reception rate of 9.5 Gbps and a minimum transmission latency of 600 ns. When the TCP packet payload length is 1024 bytes, the latency performance of TOE's double-queue storage structure improves by at least 55.3% compared to other hardware implementation approaches. When compared with software implementation approaches, the latency performance of TOE is only 3.2% of the software approaches. [ABSTRACT FROM AUTHOR]

Among the recent network infrastructure proliferations, distributed denial of service (DDoS) attack continues to be one of the most severe security threats. It becomes difficult to detect and demarcate the high volume of data and a huge number of users in any conventional network. The network randomness, physical attacks, and DDoS attacks leave their imprint through bandwidth profile (throughput), latency (time duration), and network traffic information (metadata). These three parameters form the crux of any detection setup. In this paper, we propose a fast, cost-efficient, open-source, and effective real-time entropy-based DDoS detector that uses entropy variations of Transmission Control Protocol-Synchronize packets as a base for attack detection. The attack traffic is self-generated through a compromised Bot-System controlled by a Command and Control Server. This way, we analyze the actual representative characteristics of the attack pattern. Our DDoS detector not only detects the attack but also sends the contextual information to a registered email ID. The attack information provides required network traffic characterization for the threshold-entropy calculations and its mathematical modelling, all that in real time. We code the whole architecture in python. It provides an optimal detection sensitivity and enhances predicting an attack with less resource utilization. [ABSTRACT FROM AUTHOR]

Nowadays expectations against modern communication services involve not just Quality of Service (QoS) enhancement for real-time applications but also increased transmission rate between the storing and processing of Big Data nodes. Transmission Control Protocol (TCP) has strict flow control of the data stream providing automatic adaptation to the path load of the process-to-process communication. User Datagram Protocol (UDP) based solutions are proposed to settle the communication efficiency. In this paper, we analyse the effect of three independent communication parameters on the efficiency of looped UDP communication: the size of the Maximum Transfer Unit (MTU), the bandwidth of the end-to-end session, and the segment size of the UDP protocol data unit. The usage of nonstationary multi-resolution methods helps to identify three characteristic patterns offering identification of the objective qualitative features of the looped datagram communication services. [ABSTRACT FROM AUTHOR]

In this paper, we find the optimal transmission of messages in computer networks. This problem has been formulated as a nondelayed optimal control problem in several recent papers on TCP (transmission control protocol). Since the actual transmission of messages from origins to destinations should consist of both forward transmission delays of the buffers and latency of the links, we remodel the problem as a time-delayed optimal control problem consisting of both control-dependent time-delayed arguments and discrete time-delayed arguments. We then develop a modified control parameterization method for solving this time-delayed optimal control problem. The gradients of the new objective function and constraint functions generated by this modified control parametrization method are derived. A numerical example is solved by using the time-delayed version of the problem that we formulate, as well as the nondelayed version of the problem in the literature. Numerical results clearly illustrate the efficiency of the modified control parameterization method for solving both versions of this optimal transmission problem. Comparison of results of the two versions concerning the optimal transmission rates at the origins, the optimal output flow rates at the destination, and the queue sizes at the buffers are obtained. These comparison results clearly reflect how the optimal transmission of messages in computer networks in real life can be affected by both the forward transmission delays of the buffers and the latency of the links. [ABSTRACT FROM AUTHOR]

This paper proposes an extension of the model predictive control framework for switching continuous‐time linear systems. The switching times follow a stochastic process with limited statistical information. At each switching time, the controller knows the system state, but it is blind with respect to the switching continuous‐time subsystems. In this setting, the paper's main contribution is to show how to compute the model predictive control gain. The paper also illustrates the implications of our approach for applications. The approach was used in practice to control an electric current source that supplied a switching load. The experimental data support the usefulness of our approach. [ABSTRACT FROM AUTHOR]

The Flying Ad hoc Network (FANET) is a special type of mobile ad hoc network (MANET) that provides communications among Unmanned Aerial Vehicles (UAVs). These UAVs can reduce human intervention to a great extent by giving numerous applications under different domains such as transportation, military, healthcare, traffic monitoring, surveillance, etc. In FANET, communication is relatively challenging due to its complex infrastructure, unspecified architecture and rapid mobility of nodes. The work embodied in this paper is focused on traffic surveillance of highways using UAVs. UAVs can help to reduce the number of accidents by sharing real-time as well as the accurate status of highways among vehicles and the control station. On the other hand, they can also be used to track specific vehicles on the road. In FANET, both routing protocols and mobility models play a crucial role in the process of information exchange. In this paper, the comparison and performance evaluation of two well-known reactive routing protocols viz. Ad hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR) have been carried out using highway mobility model for traffic surveillance in FANET environment. Implementation of both protocols has been tested on several traffic patterns, mobility and varying network loads. Both AODV and DSR enable significant performance variations; however, they share on-demand behavior. Packet delivery fraction, average end-to-end delay, normalized routing load, packet loss, routing overhead and throughput are used to analyze the performance of both protocols. Based on experimental analysis using NS-2 under constant bit rate (CBR) and TCP traffic sources, it can be stated that AODV outperforms DSR in almost every aspect. [ABSTRACT FROM AUTHOR]

Connectivity between ground vehicles can be utilized and expanded to include aerial vehicles for coordinated missions. Using Vehicle-to-Everything (V2X) communication technologies, a communication link can be established between Connected and Autonomous vehicles (CAVs) and Unmanned Aerial vehicles (UAVs). Hardware implementation and testing of a ground-to-air communication link are crucial for real-life applications. In this paper, the V2X communication and coordinated mission of a CAV & UAV are presented. Four methods were utilized to establish communication between the hardware and software components, namely Dedicated Short Range communication (DSRC), User Datagram Protocol (UDP), 4G internet-based WebSocket and Transmission Control Protocol (TCP). These communication links were used together for a real-life use case scenario called Quick Clear demonstration. In this scenario, the first aim was to send the accident location information from the CAV to the UAV through DSRC communication. On the UAV side, the wired connection between the DSRC modem and Raspberry Pi companion computer was established through UDP to get the accident location from CAV to the companion computer. Raspberry Pi first connected to a traffic contingency management system (CMP) through TCP to send CAV and UAV location, as well as the accident location, information to the CMP. Raspberry Pi also utilized WebSocket communication to connect to a web server to send photos that were taken by the camera that was mounted on the UAV. The Quick Clear demonstration scenario was tested for both a stationary test and dynamic flight cases. The latency results show satisfactory performance in the data transfer speed between test components with UDP having the least latency. The package drop percentage analysis shows that the DSRC communication showed the best performance among the four methods studied here. All in all, the outcome of this experimentation study shows that this communication structure can be utilized for real-life scenarios for successful implementation. [ABSTRACT FROM AUTHOR]

The dropping function mechanism is known to improve the performance of TCP/IP networks by reducing queueing delays and desynchronizing flows. In this paper, we study yet another positive effect caused by this mechanism, i.e., the reduction in the clustering of packet losses, measured by the burst ratio. The main contribution consists of two new formulas for the burst ratio in systems with and without the dropping function, respectively. These formulas enable the easy calculation of the burst ratio for a general, non-Poisson traffic, and for an arbitrary form of the dropping function. Having the formulas, we provide several numerical examples that demonstrate their usability. In particular, we test the effect of the dropping function's shape on the burst ratio. Several shapes of the dropping function proposed in the literature are compared in this context. We also demonstrate, how the optimal shape can be found in a parameter-depended class of functions. Finally, we investigate the impact of different system parameters on the burst ratio, including the load of the system and the variance of the service time. The most important conclusion drawn from these examples is that it is not only the dropping function that reduces the burst ratio by far; simultaneously, the more variable the traffic, the more beneficial the application of the dropping function. [ABSTRACT FROM AUTHOR]

To provide a low-cost methodical way for inference-driven insight into the assessment of SDN operations, a behavioral study of key network parameters that predicate the proper functioning and performance of software-defined networks (SDNs) is presented to characterize their alterations or variations, given various emulated SDN scenarios. It is standard practice to use simulation environments to investigate the performance characteristics of SDNs, quantitatively and qualitatively; hence, the use of emulated scenarios to typify the investigated SDN in this paper. The key parameters studied analytically are the jitter, response time and throughput of the SDN. These network parameters provide the most vital metrics in SDN operations according to literature, and they have been behaviorally studied in the following popular SDN states: normal operating condition without any incidents on the SDN, hypertext transfer protocol (HTTP) flooding, transmission control protocol (TCP) flooding, and user datagram protocol (UDP) flooding, when the SDN is subjected to a distributed denial-of-service (DDoS) attack. The behavioral study is implemented primarily via univariate and multivariate exploratory data analysis (EDA) to characterize and visualize the variations of the SDN parameters for each of the emulated scenarios, and linear regression-based analysis to draw inferences on the sensitivity of the SDN parameters to the emulated scenarios. Experimental results indicate that the SDN performance metrics (i.e., jitter, latency and throughput) vary as the SDN scenario changes given a DDoS attack on the SDN, and they are all sensitive to the respective attack scenarios with some level of interactions between them. [ABSTRACT FROM AUTHOR]

Yarn education is a crucial step in producing high-quality textile end products. By offering quick insights into yarn quality, online yarn testing can reduce latency in critical process control, resulting in the manufacture of higher-quality yarns. This paper proposes the development and application of information resources for the education and teaching of yarn history based on fifth-generation (5G) network technologies. Firstly, the yarn database is preprocessed using greyscale transformation and image filtering methods. Secondly, yarn segmentation is implemented using a Multiresolution Markov Random Field (MRMRF) model. Fourier transform and two-scale attention models are used to extract statistical and relative characteristics, respectively. For classifying the yarn photos, we propose using Improved Support Vector Machine (ISVM) classification. The 5G network has been set up, and data is transferred using the Transmission Control Protocol. To enhance the performance, we propose an Improved Particle Swarm Optimization (IPSO) algorithm. The performance of the suggested methodology is analyzed and compared with existing methodologies using the MATLAB simulation tool. The suggested algorithm's classification performance suggests that the 5G framework could provide an accurate, rapid, reliable, and cost-effective solution to industrial automation. [ABSTRACT FROM AUTHOR]

The QUIC protocol, which was originally proposed by Google, has recently gained a remarkable presence. Although it has been shown to outperform TCP over a wide range of scenarios, there exist some doubts on whether it might be an appropriate transport protocol for IoT. In this paper, we specifically tackle this question, by means of an evaluation carried out over a real platform. In particular, we conduct a thorough characterization of the performance of the MQTT protocol, when used over TCP and QUIC. We deploy a real testbed, using commercial off-the-shelf devices, and we analyze two of the most important key performance indicators for IoT: delay and energy consumption. The results evince that QUIC does not only yield a notable decrease in the delay and its variability, over various wireless technologies and channel conditions, but it does not hinder the energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, the leader‐following consensus problem of general linear multi‐agent systems with distributed dynamic event‐triggered control is studied. A distributed controller with estimated states is designed and a dynamic event‐triggered communication protocol with an auxiliary variable is proposed for each agent to update its triggering threshold. Under this control strategy, the systems only need the states in triggering instants as a result of the utilisation of estimated states. The existence of a dynamic threshold guarantees fewer triggering times, in contrast to the conventional static one. Meanwhile, the estimator is designed between the triggering instants to reduce the state shift, the next state of each agent depends on the local information of itself and its neighbours rather than global information. Then, the multi‐agent systems can achieve consensus without Zeno behaviour. Finally, a simulation example is offered to verify the effectiveness and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Active queue management techniques have been proposed to mitigate serious congestion issues caused by transmission control protocol flows. Active queue management controllers based on control theory are superior in terms of control performance. Such a controller utilizes a target queue length as a control input, and the congestion control system attempts to maintain the actual queue length close to the target value. However, the specific setting of the target queue length has not been discussed sufficiently. For example, raising or lowering the target queue length may increase goodput or reduce queueing delay, respectively. Therefore, the target queue length should be appropriately generated according to the required quality of services and buffer status. This paper proposes a quality of services–aware adaptive target queue length generation algorithm for an active queue management controller based on control theory. The proposed algorithm comprises two modes (loss‐aware and delay‐aware modes) and attempts to raise or lower the target queue length by considering the buffer status to increase the goodput or reduce the queueing delay. Simulation results revealed that the proposed algorithm could increase goodput or reduce queueing delay on each mode by adapting to the buffer status, which is in contrast to conventional methods. [ABSTRACT FROM AUTHOR]

This paper presents a scalable IoT architecture based on the edge–fog–cloud paradigm for monitoring the Indoor Environmental Quality (IEQ) parameters in public buildings. Nowadays, IEQ monitoring systems are becoming important for several reasons: (1) to ensure that temperature and humidity conditions are adequate, improving the comfort and productivity of the occupants; (2) to introduce actions to reduce energy consumption, contributing to achieving the Sustainable Development Goals (SDG); and (3) to guarantee the quality of the air—a key concern due to the COVID-19 worldwide pandemic. Two kinds of nodes compose the proposed architecture; these are the so-called: (1) smart IEQ sensor nodes, responsible for acquiring indoor environmental measures locally, and (2) the IEQ concentrators, responsible for collecting the data from smart sensor nodes distributed along the facilities. The IEQ concentrators are also responsible for configuring the acquisition system locally, logging the acquired local data, analyzing the information, and connecting to cloud applications. The presented architecture has been designed using low-cost open-source hardware and software—specifically, single board computers and microcontrollers such as Raspberry Pis and Arduino boards. WiFi and TCP/IP communication technologies were selected, since they are typically available in corporative buildings, benefiting from already available communication infrastructures. The application layer was implemented with MQTT. A prototype was built and deployed at the Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), using the existing network infrastructure. This prototype allowed for collecting data within different academic scenarios. Finally, a smart sensor node was designed including low-cost sensors to measure temperature, humidity, eCO2, and VOC. [ABSTRACT FROM AUTHOR]

This paper investigates the nonlinear dynamics of Transmission Control Protocol and Active Queue Management (TCP/AQM) networks, including the local stability and periodic bifurcation. The parameter of transportation delay affects the stability of the dynamical systems. One of the purposes of our work is to determine the delay stable interval of the transportation network. It is found that there is only one critical value of network delay by the τ decomposition technique. When the delay passes the critical point, the system performs Hopf bifurcation with a pair of symmetry with purely imaginary roots (PIR). In addition, the other purpose is to consider the stability of bifurcating periodic solutions. Combining with τ -decomposition strategy and central manifold theory, the issues of delay stable interval and stability of Hopf bifurcation are all tackled. Finally, numerical examples are illustrated to show the accuracy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Active queue management techniques have been proposed to mitigate serious congestion issues caused by transmission control protocol flows. Active queue management controllers based on control theory are superior in terms of control performance. Such a controller utilizes a target queue length as a control input, and the congestion control system attempts to maintain the actual queue length close to the target value. However, the specific setting of the target queue length has not been discussed sufficiently. For example, raising or lowering the target queue length may increase goodput or reduce queueing delay, respectively. Therefore, the target queue length should be appropriately generated according to the required quality of services and buffer status. This paper proposes a quality of services–aware adaptive target queue length generation algorithm for an active queue management controller based on control theory. The proposed algorithm comprises two modes (loss‐aware and delay‐aware modes) and attempts to raise or lower the target queue length by considering the buffer status to increase the goodput or reduce the queueing delay. Simulation results revealed that the proposed algorithm could increase goodput or reduce queueing delay on each mode by adapting to the buffer status, which is in contrast to conventional methods. [ABSTRACT FROM AUTHOR]

Free-space optics (FSO)-based, low-earth orbit (LEO) satellite-assisted Internet of vehicles (IoVs) has recently attracted research efforts worldwide. For the majority of Internet applications, transmission control protocol (TCP) is one of the most widely deployed protocols. Nevertheless, a complete understanding of the TCP performance over FSO-based satellite-assisted IoVs networks is still lacking in the literature. This is a highly challenging issue, as a consequence of the non-trivial interdependencies between transmission losses caused by the dynamics/uncertainty of atmospheric last-mile channels and the buffer overflows on the Internet, as well as their joint impact on the TCP congestion control mechanisms. This paper offers a comprehensive analytical framework that allows assessing the TCP throughput performance under the joint impact of congestion losses occurred in the Internet and transmission errors at the last-mile link from the satellite-to-vehicle. Internet access for emerging unmanned aerial vehicles (UAVs) is considered while the analysis can be also applied to other kinds of vehicles, which, in fact, require simpler channel models. The link-layer incremental redundancy hybrid automatic repeat request (IR-HARQ) protocol is employed at satellite-to-UAV channels to further improve the TCP throughput performance. Numerical results provide non-trivial findings and insights for the TCP performance in satellite/FSO-based IoVs, in which optimal UAV’s parameters are chosen to maximize the TCP throughput. [ABSTRACT FROM AUTHOR]

To support cloud services, Data Centre Networks (DCNs) are constructed to have many servers and network devices, thus increasing the routing complexity and energy consumption of the DCN. The introduction of optical technology in DCNs gives several benefits related to routing control and energy efficiency. This paper presents a novel Packet Classification based Optical interconnect (PCOI) architecture for DCN which simplifies the routing process by classifying the packet at the sender rack and reduces energy consumption by utilizing the passive optical components. This architecture brings some key benefits to optical interconnects in DCNs which include (i) routing simplicity, (ii) reduced energy consumption, (iii) scalability to large port count, (iv) packet loss avoidance, and (v) all-to-one communication support. The packets are classified based on destination rack and are arranged in the input queues. This paper presents the input and output queuing analysis of the PCOI architecture in terms of mathematical analysis, the TCP simulation in NS2, and the physical layer analysis by conducting simulation in OptiSystem. The packet loss in the PCOI has been avoided by adopting the input and output queuing model. The output queue of PCOI architecture represents an M/D/32 queue. The simulation results show that PCOI achieved a significant improvement in terms of throughput and low end-to-end delay. The eye-diagram results show that a good quality optical signal is received at the output, showing a very low Bit Error Rate (BER). [ABSTRACT FROM AUTHOR]

In this paper, buffer dynamic modeling for wireless sensor networks as a highly nonlinear system is accomplished in discrete time, different subsystems are achieved based on delay, and the overall model is gained by blending them. According to nonlinear dynamics point of view, considering delay in the analysis of congestion control schemes is of paramount importance. In this paper, an adaptive back-off interval selection works with the proposed robust controller. Based on queue utilization and channel estimation algorithm, congestion is detected and a suitable rate is selected by adaptive back-off interval selection. An augmented form of our proposed system is utilized for controller synthesis. A new approach is proposed for controller synthesis based on non-quadratic and common quadratic Lyapunov candidates where the former is generalized to be more relaxed. Also, the monotonicity requirement of Lyapunov's theorem is relaxed. The closed-loop systems are globally asymptotically stable in case of delay changes resulted from queue size changes. Extended simulation results confirm the effectiveness of our proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we aim to propose a novel transmission control protocol (TCP) congestion control method from a cross-layer-based perspective and present a deep reinforcement learning (DRL)-driven method called DRL-3R (DRL for congestion control with Radio access network information and Reward Redistribution) so as to learn the TCP congestion control policy in a superior manner. In particular, we incorporate the RAN information to timely grasp the dynamics of RAN, and empower DRL to learn from the delayed RAN information feedback potentially induced by several consecutive actions. Meanwhile, we relax the implicit assumption (that the feedback to one specific action returns at a round-trip-time (RTT) after the action is applied) in previous researches, by redistributing the rewards and evaluating the merits of actions more accurately. Experiment results show that besides maintaining a reasonable fairness, DRL-3R significantly outperforms classical congestion control methods (e.g., TCP Reno, Westwood, Cubic, BBR and DRL-CC) on network utility by achieving a higher throughput while reducing delay in various network environments. [ABSTRACT FROM AUTHOR]

In ultra-dense cellular networks (UDNs) with user/control plane(U/C) splitting, frequent handovers in user planes are unavoidable, which seriously degrades the transmission control protocol (TCP) throughput of mobile station (MS). To enhance the TCP throughput in UDNs, this paper proposes an intelligent recommendation-based user plane handover scheme. Firstly, based on intelligent recommendation algorithms, a mobility prediction algorithm called content-based collaborative hybrid filters (CCHF) is proposed to predict the target small base station (SBS). When the MS moves into the cell-edge of the source SBS, it can pre-access the predicted target SBS and set up connections to the predicted target SBS and the source SBS simultaneously. This is the proposed CCHF-dual-handover scheme. With an accurate prediction and a simultaneous connection, CCHF-dual-handover can present enhanced signal to interference and noise ratio (SINR) at cell-edge, reduced handover interruption ratio (HIR), and improved MS’s TCP throughput. Moreover, TCP throughput of CCHF-dual-handover is analyzed to show the impact of various key parameters (such as MS’s velocity and pre-access threshold). Finally, simulations are carried out to evaluate the performance of the proposed CCHF-dual-handover. Given random trajectory, the prediction accuracy using CCHF is increased by more than 100% compared with existing prediction algorithms. Given accurate prediction, the CCHF-dual-handover can improve the TCP throughput by up to 150% compared with that of existing handover schemes. [ABSTRACT FROM AUTHOR]

The article lists the topics on which papers can be submitted for publication in the journal's new issue "IEEE Wireless Communications Letters (WCL)" including articles on TCP/IP protocols, Multiple Input, Multiple Output (MIMO) systems and orthogonal frequency division multiplexing.

Apache Storm is a scalable fault-tolerant distributed real time stream-processing framework widely used in big data applications. For distributed data-sensitive applications, low-latency, high-throughput communication modules have a critical impact on overall system performance. Apache Storm currently uses Netty as its communication component, an asynchronous server/client framework based on TCP/IP protocol stack. The TCP/IP protocol stack has inherent performance flaws due to frequent memory copying and context switching. The Netty component not only limits the performance of the Storm but also increases the CPU load in the IPoIB (IP over InfiniBand) communication mode. In this paper, we introduce two new implementations for Apache Storm communication components with the help of RDMA technology. The performance evaluation on Mellanox QDR Cards (40 Gbps) shows that our implementations can achieve speedup up to 5 × compared with IPoIB and 10 × with Gigabit Ethernet. Our implementations also significantly reduce the CPU load and increase the throughput of the system. [ABSTRACT FROM AUTHOR]

Provisioning of Internet of Things/machine-to-machine (M2M) services over satellite has been experiencing a continuous growth in the last few years, which is expected to further increase in the near future so as to meet the demands of users and enterprises. The design of a suitable network architecture is, hence, of paramount importance to properly take into account the requirements imposed by the technology available nowadays and to properly consider the interaction of the so-defined physical layer with transport and application layers. In this light, this paper analyzes the use case of TCP-based M2M services operating over DVB-RCS2 satellite links, where a contention resolution diversity slotted ALOHA access scheme is applied. The main goal of this paper is to provide a thorough understanding of the interactions of TCP and random access schemes, recognized as key elements to enable efficient M2M services over satellite. In this regard, this paper also develops a novel TCP throughput model, which has been validated through extensive simulation campaigns, proving the value of the proposed theoretical framework and its applicability to study the performance of M2M services in more general satellite scenarios. [ABSTRACT FROM AUTHOR]

Named data networking (NDN), as a future Internet architecture that is a promising alternative to TCP/IP networks, has the new features of connectionless, in-network cache, and hop-by-hop forwarding, which makes the congestion control algorithms of traditional TCP/IP networks unable to be directly applied to NDN. In addition, since the optimal size of the sending window cannot be determined, the existing window-based congestion control algorithms generally use the AIMD-like window adjustment algorithm, which cannot achieve the optimal throughput. In this paper, we propose a precise feedback-based, multipath-aware congestion control algorithm PFECC, which is inspired by Accel-Brake Control algorithm. PFECC considers the influence of Interest flows, uses a fair queuing algorithm at the intermediate node to calculate the target rate of each flow, and gives accurate feedback on each dequeued data packet. The consumer changes the size of the sending window according to the feedback to quickly converge to the target bandwidth. To fully exploit the hop-by-hop adaptive forwarding feature of NDN, each downstream node timely senses the congestion trend of the upstream link to split the forwarding rate of Interest to avoid congestion. Simulation results show that PFECC can effectively reduce transmission delay, treat each flow fairly, and converge to the best throughput faster. [ABSTRACT FROM AUTHOR]

When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service, i.e., the user’s quality of experience (QoE). However, the two are not independent from each other and their relationship has to be studied through metrics that go beyond the typical network parameters. To better explore the value of assessing QoE alongside QoS in high-speed, lossy networks, this paper presents an experimental methodology to understand the relation between network QoS onto service QoE, with the aim to perform a combined network-service assessment. Using video streaming services as the test-case (given their extended usage nowadays), in this paper, we provide studies on three network-impaired video-sets with the aim to provide a comprehensive evaluation of the effects of networks on video quality. First, the ReTRIeVED video set provides the means to understand the most impairing effects on networks. Furthermore, it triggered the idea to create our own sets, specialized in the most impairing conditions for 2-D and 3-D: the LIMP Video Quality Database and the 3-D-HEVC-Net Video Quality Database. Our study and methodology are meant to provide service providers with the means to pinpoint the working boundaries of their video-sets in face of different network conditions. At the same time, network operators may use our findings to predict how network control policies affect the user’s perception of the service. [ABSTRACT FROM AUTHOR]

In this paper, we explore on a comparative basis the performance suitability of meta-heuristic, sometime denoted as random search algorithms, and greedy-type heuristics for the energy-saving joint dynamic scaling and consolidation of the network-plus-computing resources hosted by networked virtualized data centers when the target is the support of real-time streaming-type applications. For this purpose, the energy and delay performances of Tabu Search (TS), Simulated Annealing (SA) and Evolutionary Strategy (ES) meta-heuristics are tested and compared with the corresponding ones of Best-Fit Decreasing-type heuristics, in order to give insight on the resulting performance-versus-implementation complexity trade-offs. In principle, the considered meta-heuristics and heuristics are general formal approaches that can be applied to large classes of (typically, non-convex and mixed integer) optimization problems. However, specially for the meta-heuristics, a main challenge is to design them to properly address the real-time joint computing-plus-networking resource consolidation and scaling optimization problem. To this purpose, the aim of this paper is: (i) introduce a novel Virtual Machine Allocation (VMA) scheme that aims at choosing a suitable set of possible Virtual Machine placements among the (possibly, non-homogeneous) set of available servers; (ii) propose a new class of random search algorithms (RSAs) denoted as consolidation meta-heuristic, considering the VMA problem in RSAs. In particular, the design of novel variants of meta-heuristics, namely TS-RSC, SA-RSC and ES-RSC, is particularized to the resource scaling and consolidation (RSC) problem; (iii) compare the results of the obtained new RSAs class against some state-of-the-art heuristic approaches. A set of experimental results, both simulated and real-world ones, support the effectiveness of the proposed approaches against the traditional ones. [ABSTRACT FROM AUTHOR]

As a promising candidate for future Internet architecture, Named Data Networking (NDN) can achieve significant potential advantages over current TCP/IP based Internet in content distribution and mobility support, etc. However, the communication mode in NDN that one Interest packet for pulling one data packet is likely to incur Interest packets flooding and to cause extremely large-scale Pending Interest Table (PIT) of the NDN router, which may substantially degrade the performance of NDN. Moreover, the absence of predefined connections also induces another challenge for NDN to manage the successive and concurrent requests from consumers efficiently. In this paper, we propose flow-based NDN ($f$ -NDN) architecture capable of supporting flow transmission mode for addressing the aforementioned challenges. In the context of $f$ -NDN, a data flow is defined as an aggregate of data packets with the same name prefix, and a flow Interest packet is introduced to pull a data flow rather than a single data packet. The PIT, CS, and FIB are re-designed to enable $f$ -NDN to operate at the granularity of flows. Bitmap structure aided error handling mechanism is further presented for $f$ -NDN to deal with the flow transmission’s uncertain failures. The built-in flow support in $f$ -NDN allows us to conceive a flow-level multi-path transmission regime for balancing the traffic in NDN network and reducing the time consumed for pulling the entire content. Weight-based flow Interest splitting algorithm and optimal rate control algorithm are both proposed for optimizing multi-path transmission. We illustrate the capability of the proposed architecture in supporting flow transmission and multi-path by implementing it in both simulator and prototype systems. The evaluation results are also presented to show its achievable performance. [ABSTRACT FROM AUTHOR]

Software-defined networking (SDN) has evolved as an approach that allows network administrators to program and initialize, control, change and manage networking components (mostly at L2-L3 layers) of the OSI model. SDN is designed to address the programmability shortcomings of traditional networking architectures commonly used in cloud datacenters (CDC). Deployment of SDN solutions have demonstrated significant improvements in areas such as flow optimization and bandwidth allocation in a CDC. However, the benefits are significantly less explored when considering Software-Defined Wide Area Networks (SD-WAN) architectures in the context of delivering solutions by networking multiple CDCs. To support the testing and bench-marking of data-driven applications that rely on data ingestion and processing (e.g., Smart Energy Cloud, Content Delivery Networks) across multiple cloud datacenters, this paper presents the simulator, IoTSim-SDWAN. To the best of our knowledge, IoTSim-SDWAN is the first simulator that facilitates the modeling, simulating, and evaluating of new algorithms, policies, and designs in the context of SD-WAN ecosystems and SDN-enabled multiple cloud datacenters. Finally, IoTSim-SDWAN simulator is evaluated for network performance and energy to illustrate the difference between classical WAN and SD-WAN environments. The obtained results show that SD-WAN surpasses the classical WAN in terms of accelerating traffic flows and reducing power consumption. • Proposing a novel framework that simulates and models the SD-WAN and SDN-enabled data centers. • Accurate modeling of TCP and UDP protocols in addition to network delays in IoTSim-SDWAN. • Proposing an SD-WAN routing technique to dynamically compute the best route for every network flow. • proposing a coordination scheme for SD-WAN and SDN controllers. • Empirically validating IoTSim-SDWAN with a real-world network environment. [ABSTRACT FROM AUTHOR]

Geolocation of covert communication entity is significantly important for the forensics of the crime but has significant challenges when the steganalyst locks the guilty actor IP and wants to know the physical location of the actor. This kind of post-steganalysis involves not only the stegos transmitted on the Internet but the IP package head and content. This paper presents a geolocation method for the location of the covert communication entity based on hop-hot path coding. The method estimates the location of the covert communication entity by combining the path and delay between probes and the covert communication entity IP, which improves the deficiency that similar delays do not necessarily mean close geographical locations of the IPs. Moreover, the similarity between the IPs' paths can be measured by coding the paths between IPs and probes. The results of a series of experiments show that the median error of the proposed method is within 6.16 km using different thresholds. [ABSTRACT FROM AUTHOR]

In this paper, a Virtex-7-based video chaotic secure communication scheme is investigated. First, the network sending and receiving controller Intellectual Property (IP) cores are designed. Next, the chaotic encryption and decryption IP cores are implemented using fixed-point algorithm, pipeline operation, and state machine control. Thus, video capturing, video displaying, network sending, network receiving, chaotic encrypting, and chaotic decrypting can be achieved via IP core integration design. An improved 7D chaotic stream cipher algorithm for resisting divide-and-conquer attack is then designed and realized on a Virtex-7 high-end FPGA platform. Hardware experimental results are also given to verify the feasibility of the scheme. [ABSTRACT FROM AUTHOR]

A fast retransmit, which reduces the sender’s waiting time before retransmitting a lost segment, is applied to guarantee data integrity with no data loss in transmission. Based on fast retransmit, many application protocols have been enhanced and evolved to ensure quality of service and reduce data transmission time. One of application protocols is the multipath transmission control protocol which is catholically applied in modern computer networks. Communication lines used in this kind of network have different states, namely, failure, partial failure, and maintenance. Therefore, a computer network with a fast retransmit can be classified as stochastic and is called a stochastic-flow computer network with a fast retransmit (SCNFR). This paper assesses the system reliability of SCNFR for the successful transmission of demand d through ${k}$ (${k} \,\, >1$) separate minimal paths (${k}$ SMiP) under the latency. An algorithm is proposed to find all minimal capacity vectors (MCVs) that satisfy the demand and latency. Then, the system reliability is computed based on all MCVs. We adopt two practical cases of the pan-European research and education network and the Taiwan academic network to explore the effectiveness of the algorithm. The results show that the system reliability can be classified as decision reference while the manager decides the better ${k}$ SMiP with higher system reliability. [ABSTRACT FROM AUTHOR]

Abstract test cases (ATCs) have been widely used in practice, including in combinatorial testing and in software product line testing. When constructing a set of ATCs, due to limited testing resources in practice (e.g., in regression testing), test case prioritization (TCP) has been proposed to improve the testing quality, aiming at ordering test cases to increase the speed with which faults are detected. One intuitive and extensively studied TCP technique for ATCs is $\lambda$ -wise Level-combination Coverage based Prioritization ($\lambda$ LCP), a static, black-box prioritization technique that only uses the ATC information to guide the prioritization process. A challenge facing $\lambda$ LCP, however, is the necessity for the selection of the fixed prioritization strength $\lambda$ before testing—testers need to choose an appropriate $\lambda$ value before testing begins. Choosing higher $\lambda$ values may improve the testing effectiveness of $\lambda$ LCP (e.g., by finding faults faster), but may reduce the testing efficiency (by incurring additional prioritization costs). Conversely, choosing lower $\lambda$ values may improve the efficiency, but may also reduce the effectiveness. In this paper, we propose a new family of $\lambda$ LCP techniques, Repeated Small-strength Level-combination Coverage-based Prioritization (RSLCP), that repeatedly achieves the full combination coverage at lower strengths. RSLCP maintains $\lambda$ LCP's advantages of being static and black box, but avoids the challenge of prioritization strength selection. We have performed an empirical study involving five different versions of each of five C programs. Compared with $\lambda$ LCP, and Incremental-strength LCP (ILCP), our results show that RSLCP could provide a good tradeoff between testing effectiveness and efficiency. Our results also show that RSLCP is more effective and efficient than two popular techniques of Similarity-based Prioritization (SP). In addition, the results of empirical studies also show that RSLCP can remain robust over multiple system releases. [ABSTRACT FROM AUTHOR]

The energy consumption of wireless interface is critical to power-constrained mobile devices. To improve energy efficiency for WLAN stations, power saving mode (PSM) is proposed, to manage the time spent in idle listening (IL) state. The hurdle is that the receiver has no knowledge about when the pending data will arrive under end-to-end communication protocols (TCP/IP), making each station spend enormous time in IL to wait for the pending data. To overcome this limitation, in this paper, we propose a named data networking (NDN) enabled PSM, namely, NDN-PSM, which leverages NDN communication architecture to cut down unnecessary IL time. In particular, we devise two new power states in NDN-PSM, i.e., light doze and deep doze, to precisely map to the underlying data arriving states. The inherent receiver-driven pattern of NDN can effectively drive the stations to the deep doze state for power saving, and to light doze state for timely data reception. Considering the IL time waste during channel contention, we further design a channel contention control mechanism in NDN-PSM, in which stations will switch to the light doze state if the channel is perceived to be busy. The power consumption model of the proposed NDN-PSM is theoretically analyzed and verified via numerical results. At last, we implement NDN-PSM in NS-3 by adopting the ndnSIM module and conduct extensive simulations to demonstrate the efficacy of NDN-PSM. Specifically, compared to the existing PSM mechanism, NDN-PSM reduces 56% power consumption by cutting down unnecessary IL time, and meanwhile enables low-delay transmission. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-level additive Schwarz method for a kind of tensor complementarity problem (TCP). The method is proved to be convergent monotonically and can reach the solution within finite steps. We report some preliminary numerical results to test the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Periodic beacon messages are one of the building blocks that enable the operation of vehicular ad hoc networks (VANETs) applications. In vehicular networks environments, congestion and awareness control mechanisms are key for a reliable and efficient functioning of vehicular applications. In order to control the channel load, a reliable mechanism allowing real-time measurements of parameters like the local density of vehicles is a must. These measurements can then serve as an input to perform a fast adaptation of the transmit parameters. In this paper, considerable efforts have been directed in the recent years toward designing flexible yet robust protocols solving this problem; yet, very few have considered a proactive adaptation of the transmit parameters as a preventive measure from channel load peaks. To this end, we take the opportunity to introduce prediction and adaptation algorithm (P&A-A), a new congestion control protocol that performs a joint adaptation of the transmit rate and power, relying on an altruistic short-term prediction algorithm that estimates the vehicular density around a given vehicle within the next short while. Additionally, P&A-A adapts the transmit parameters in a way that guarantees the strict beaconing requirements and satisfies the level of awareness required for the operation of most critical VANET applications. The results of the simulations performed in a realistic scenario justify our theoretical considerations and confirm the efficiency and the effectiveness of our protocol by showing significant improvements in terms of network performance (up to 8% and 14% improvement in collision rate; and up to 10% and 20% increase in busy ratio compared to our previous scheme and the ETSI schemes, respectively) as well as the achieved level of awareness (higher coverage with higher transmission rate and power in dense scenarios, and up to 8% and 55% improvement in density perception accuracy compared to our previous scheme and the ETSI schemes, respectively). [ABSTRACT FROM AUTHOR]

Intellectual Property (IP) core protection of Digital Signal Processing (DSP) kernels is an important subject of research for Consumer Electronics (CE) systems. An IP core may be prone to piracy, forgery and counterfeiting. The need of the hour is developing effective technique that is robust and incurs low overhead to detect IP core infringement. This paper presents a novel ‘IP core steganography’ methodology for DSP kernels that is capable of detecting IP piracy. The proposed methodology is capable of implanting concealed information into the existing IP core design of DSP datapath without using any external signature, to reflect the IP core ownership. The presented ‘IP core steganography’ methodology is non-intuitive in nature indicating that the intended secret information does not attract attention to itself from an adversary’s perspective. The implanted information incurs almost no design overhead and yields lower design cost than signature-based IP core protection techniques. Further, in the presented approach the amount of concealed information embedded is fully designer controlled through a ‘thresholding’ parameter, unlike signature-based techniques where signature pattern impacts the robustness and overhead. Results of proposed approach yielded lower cost and stronger proof of authorship compared to a signature-based approach. [ABSTRACT FROM AUTHOR]