Packet Rate Research Articles

Tuatara: Location-Driven Power-Adaptive Communication for Wireless Body Area Networks

Radio links in wireless body area networks (WBANs) suffer from both short-term and long-term variations due to the dynamic network topology and frequent blockage caused by body movements, making it challenging to achieve reliable, energy-efficient and real-time data communication. Through experiments with TelosB motes, we observe a strong positive relationship between the channel quality and the location of the sensor node relative to the gateway. Motivated by this observation, we design Tuatara, a novel power-aware communication protocol that allows each sensor node to dynamically adjust its transmission power based on the channel status inferred from its instant location, aiming to save energy, reduce interference, and improve communication reliability. Combining the orientations measured by motion sensors with the anatomical constraints of body movements, each sensor node can locally estimate its instant location relative to the gateway. Based on a probabilistic model, power level selection is converted to calculate the optimal probability of selecting each power level at a given location, with the objective of minimizing the transmission cost. A learning scheme is designed to adaptively update the power level selection probabilities, making Tuatara self-adaptable to changes in the signal propagation environment. Experimental results demonstrate that Tuatara outperforms the state-of-the-art protocols in various scenarios, with performance close to that of the optimal power selection solution even in scenarios where the packet rate is very low.

AODV routing protocol performance assessment for wireless sensor network scenarios

Emerging WSN applications include a wide selection of traditional situations with many nodes. The messages are propagated through intermediate nodes, in order to ensure correct contact between the network nodes with the base station, so that a path has many connexions. Generally speaking, the nodes on the sensor network are distinguished by their minimal resources, so protocols must be used that not only guarantee connectivity but also conserve the most energy while maintaining scalability. Different protocols for routing wireless sensor networks have been suggested, however, reactive routing algorithms have been shown to be energy efficient and adaptable to wireless sensor networks. In this paper, under the OMNeT + + simulation platform, the performance of the reactive protocol will be tested, evaluating different scripts. In contrast to the supplementary responsive protocols stated in literature, the AODV protocol has been selected for supremacy in performance. The following parameters have been evaluated: the transmission rate of packets, average delays, overhead routing and energy usage. The findings show that AODV decreases its efficiency with the growth in the number of nodes. As a result, its usability limits the network scalability and the outcomes demonstration that the spatial distribution of nodes affects protocol performance. The standardised delivery shows the best outcomes for our particular works.

IMPLEMENTATION OF CHORDAL RING NETWORK TOPOLOGY TO ENHANCE THE PERFORMANCE OF WIRELESS BROADBAND NETWORK

The expansion of networks involved higher jump on the users utilizing the networks resources, which may require extra higher bandwidth. Due to the development of technology especially those folded under the Internet of Things (IoT), the new demand of higher data rate is been witnesses among the users. In order to feed the demand of users with high data rate, broadband networks are required where high data rate can be ensured for each user. Broadband networks can be established using optical network that carries the data through wide broadband. Areas such as rural and forests sides which are witnessing plenty of natural obstacles such as mountains, trees, seas, etc. are forming big challenge for propagating a cable (wire) or optical network.
 Due to the limitations of the wire network, World Interoperability for Microwave Access (WiMAX) technology has been introduced as substitution for the broadband network. Such kind of alternative can be deployed through any geographical area without concerning on the wire paths. WiMAX preserved large coverage area and hence it may not suffer from the signal hand-off as in the case of another wireless network. In this project, Chordal Ring network topology is implemented to enhance the performance of wireless broadband network. With different routing protocols such as Destination Sequenced Distance Vector Protocol (DSDV) and Ad hoc On Demand Distance Vector (AODV), the network performance was examined for various Chordal Ring degree (e.g. fourth degree and fifth degree). Performance metrics such as number of transmitted packets, number of received packers, delivered packet rate (PDR), total number of drop packers (DP) and average queuing delay (been measured). Finally, the obtained results had been shown that fifth-degree Chordal Ring network is outperforming through DSDV routing protocol

Power Line Communications for Automotive High Voltage Battery Systems: Channel Modeling and Coexistence Study with Battery Monitoring

As electric vehicles are gaining increasing worldwide interest, advances in driving range and safety become critical. Modern automotive battery management systems (BMS) compete with challenging performance and safety requirements and need to monitor a large amount of battery parameters. In this paper, we propose power line communications (PLC) for high voltage (HV) traction batteries to reduce the BMS wiring effort. By modeling a small-scale battery pack for frequencies up to 300 MHz, we predict the PLC channel transfer characteristics and validate the results using a PLC hardware demonstrator employing a narrowband single-carrier modulation. The results demonstrate that battery PLC is a demanding task due to low access impedances and cell coupling effects, yet transfer characteristics can be improved by optimal impedance matching. PLC for HV BMS not only saves weight and cost, but also improves flexibility in BMS design. PLC enables single-cell monitoring techniques such as online electrochemical impedance spectroscopy (EIS) without additional wiring. Online EIS can be used for in-situ state and temperature estimation saving extra sensors. This work unveils possible coexistence issues between PLC and battery monitoring. In particular, we demonstrate that certain PLC data or packet rates have to be avoided not to interfere with EIS measurements.

DATA TRAFFIC TRUST MODEL FOR CLUSTERED WIRELESS SENSOR NETWORK

Trust is an essential parameter among sensor nodes to provide secured and successful communication. Many trust management schemes have been proposed earlier for large scale Wireless Sensor Network (WSN) however not cooperates well in terms of low dependability, memory overheads, large communication etc, therefore a system called Data Traffic Trust Scheme (DTTS) for clustered WSN is proposed here. Here the trust nodes are identified through the data traffic sampling rate. The trust rate is identified through the number of sent and receive data packets and the malicious packets are diagnosed through the un-matching packet rate. The simulation results are evaluated to show the efficiency for the proposed scheme.

The Realistic 3D Group Mobility Model Based on Spiral Line for Aerial Backbone Network

For search and rescue (SAR), the group unmanned aerial vehicle (GUAV) can rapidly cover the disaster area, and it can provide reliable connectivity to victim by aerial backbone network (ABN). However, existing 3D aerial mobility model (3D AMM) cannot capture unique features of GUAV in SAR, especially smooth 3D trajectory and collision avoidance. In this paper, we develop realistic 3D aerial group mobility model based on spiral line (3D SLGM) for SAR. Firstly, we review some related works. Then, we introduce the mechanism of 3D SLGM, such as Z-Or-SLGM and Z-Non-SLGM. Furthermore, we analyze some mathematical features of 3D SLGM. In addition, we investigate key mobility features of 3D SLGM. Finally, we evaluate the network performance under 3D SLGM. The result shows that 3D SLGM has smooth 3D trajectory and uniform distribution of spatial nodes in 3D space. With the collided rate of 0%, 3D SLGM merely takes about 1.4 minutes to cover 100% of the target area of 200 m*200 m. Besides, the network under 3D SLGM can approach the throughput of 0.45 Mb/s, the end-to-end delay of 3.2 ms and the loss packets rate of 0%. We believe that 3D SLGM, as a significant supplement of 3D AMM, can provide many helpful guidelines in the design and analysis of authentic ABN.

A geographic routing protocol based on trunk line in VANETs

A Trunk Line Based Geographic Routing(TLBGR) protocol in Vehicular Ad-hoc Networks (VANETs) is proposed in this paper to solve the problem of data acquisition in the traditional trunk coordinated control system. Because of the characteristics of short communication time and high packet loss among vehicles, the vehicles entering the trunk lines can not transmit their information to the trunk coordinated control system stably. To resolve this problem, the proposed protocol uses the trunk lines’ traffic flow and the surrounding road network to provide a real-time data transmission routing scheme. It takes into account the data congestion problem caused by the large traffic flow of the main roads, which leads to the corresponding increase of the information flow of the section and the package loss, and the link partition problem caused by the insufficient traffic flow, which makes the vehicles have to carry and relay information thus increasing the transmission delay. The proposed TLBGR protocol can be divided into two stages: the next-intersection selection, and the next-hop selection in the chosen path between the current and next intersections. Simulation results show that, compared with other IoT routing protocols including Greedy Perimeter Stateless Routing (GPSR), Ad-hoc On Demand Vector (AODV), and Q-AODV, the TLBGR protocol has better performance in aspects of end-to-end delay, delivery rate, and routing cost under the scenario of urban traffic trunk lines. The TLBGR protocol can effectively avoid data congestion and local optimum problems, increase the delivery rate of data packets, and is therefore suitable for the routing requirements in this application scenario.

Performance Analysis of Packet Sniffing Techniques Applied to Network Monitoring

Network monitoring based on packet sniffing is one of the most useful techniques applied by system administrators and security analysts in order to identify threats within a local network. Despite being supposedly a simple task, it could sometimes be a highly resource consuming process. In this paper, the use of two sniffing techniques, raw sockets and scapy, to achieve better performance in terms of maximum capture packet rate are analyzed and compared. Furthermore, both techniques are optimized by using BSD Packet Filtering to improve packet capture, and a multicore architecture in order to reduce the exposition to denegation of service attacks. Finally, a system based on those techniques that is able to automatically detect layers 2 and 3 common vulnerabilities and attacks within the scope of corporative networks is developed. The result is an enhanced system focused on link and network layers that can be deployed in corporative environments.

Comparison of Performance Among Forwarding Strategies in CCN: Disaster Scenarios

Content-Centric Networking (CCN) is a novel modern architecture for the Internet in the future. This architecture concentrates on content retrieval and dissemination solution for communication models. Forwarding strategies are decision-making strategies whose aim is to define the forwarding destination, i.e., where and when request packets will be redirected. They are considered as the most crucial component in a network environment because of their contribution to determining which strategy is suitable to adopt in accordance with the environment and the applications. These strategies have not been initially designed to support complex applications and interactions that require Interest packet send rate, CCN table sizing, refreshing Pending Interest Table (PIT), and Content Store (CS), such as disaster scenarios, social network, and smart applications. The goal of this work is to evaluate the performance of CCN forwarding strategies in disaster scenarios. A network simulator (i.e., ndnSIM) is utilized to measure the performance in many scenarios by modifying Interest packet rate, PIT size, and CS size. Evaluation results achieved after performing the study on the selected strategies are considerably enhanced for the metrics cache hit, PIT size, Interest retransmissions, number of hops, delay, and Interest delivery. The main significance of this work is that it formulates a universal rule as the main function, which can adopt a suitable forwarding strategy accurately in accordance with the PIT and CS conditions and Interest packet rate, thus leading to increased Interest packet satisfaction utilization without increasing Interest packet retransmission and response delay.

Interest flooding attack mitigation in a vehicular named data network

Vehicular named data network (VNDN) is the next-generation network architecture for intelligent transportation system. Contrary to the conventional transmission control protocol/internet protocol (TCP/IP) communication model, VNDN follows a data-centric approach where the user is interested in ‘WHAT’ instead of ‘WHERE’. Interest flooding attack (IFA) is one of the prominent security concerns in VNDNs. In IFA, attackers request for non-existent content to exhaust network resources and cause Interest packet flooding across the network. A novel attack mitigation scheme to counter IFA in VNDN has been proposed in this study. The proposed priority-based per-flow Interest rate monitoring (PP-FIRM) scheme determines the suspicious flow of malicious incoming Interest packets in attacked vehicles. A priority flag is assigned to the incoming flow of Interest packets that detects the occurrence of an attack. The priority of incoming Interest packet flow is calculated using a collaborative or neighbour-assisted approach. A comparison with another attack mitigation scheme validates that the proposed scheme performs better in terms of an improved cache hit ratio and Interest satisfaction ratio during the attack window. Besides this, pending Interest table utilisation, packet collisions rate, Interest packets retransmission count, end-to-end delay, and the ratio of timed out Interest packets have also been reduced. Furthermore, the scalability of the proposed research strategy is also evaluated by changing the density of attackers in real time. Moreover, in the proposed attack mitigation model, the rate of incoming legitimate Interest packets increases by reducing the drop rate of valid Interest packets.

Software Packet-Level Network Analytics at Cloud Scale

As networks grow in speed, scale, and complexity, operating them reliably requires continuous monitoring and increasingly sophisticated analytics. Because of these requirements, the platforms that support analytics in cloud-scale networks face demands for both higher throughput (to keep up with high packet rates) and increased generality and programmability (to cover a wider range of applications). Recent proposals have worked toward these goals by offloading analytics application logic to line-rate programmable data plane hardware, as scaling existing software analytics platforms is prohibitively expensive. The rigid design and constrained resources of data plane devices, however, fundamentally limit the types of analysis and the number of tasks that can run concurrently. In this article, we demonstrate that generality need not be sacrificed for high performance. Rather than offloading entire analytics applications to hardware, the core idea of our work is to offload only critical preprocessing tasks that are shared among applications (e.g., load balancing) to a line-rate hardware frontend while optimizing the core analytics software to exploit properties of network analytics workloads. Based on this design, we present Jetstream, a hybrid platform for network analytics that can run custom software-based analytics pipelines at throughputs of up to 250 million packets per second on a 16-core commodity server. Jetstream makes sophisticated, network-wide packet analytics feasible without compromising on generality or performance.

A Proposed Linear Multi-Controller Architecture to Improve the Performance of Software Defined Networks

In the last few years, there has been a growing interest in the rise of demand for moving from traditional networks towards software-defined networks, this has raised a lot of challenges. Software-defined networks are continually evolving, which include the need to address issues such as scalability, and packet loss, transmission delay and network congestion. accordingly, researchers introduced the concept of multi-controller architectures, although it will not assist to balance the load between them, it will tackle the network congestion issue through the distribution of load between them. the present study proposes a linear multi-controller architecture to explore the impact of increasing the number of controllers connected in a linear style on network performance. The study was based on the generation of simultaneous multi-flows with different sizes using Distributed Internet Traffic Generator(D-ITG). From the outcomes of our investigation, it is possible to conclude that the performance-enhanced uniformly with the number of controllers while preserving the same number of Open Vswitches. as the number of controllers reached four, The Quad-controller architecture recorded the best results related to improving the reduction of average delay and average jitter to 62% and 64% as well as increasing the throughput, bytes received, average packet rate to 32%, 32% and 31.8%.

An Exact Analytical Model for an IoT Network with MMPP Arrivals

Analytical modeling of the Internet of Things (IoT) networks is challenging. This is due to the presence of a large number of devices in these networks and the complexity of the priorities between different types of traffic. Taking these aspects into account, the objective of this paper is to analyze the performance of an IoT network where the IoT devices work independently of one another. To this end, we developed a novel multi-dimensional Continuous-Time Markov Chain (CTMC) model with threshold-based preemption. In this model, each IoT device is modeled as a Markov Modulated Poisson Process (MMPP) that can transmit regular and alarm packets. Alarm packets have higher priority over regular packets. To measure access to the channel between alarm and regular packets, we introduced a threshold parameter where the threshold is the number of packets in the alarm queue that indicates when preemption starts. The performance measures include blocking probability, the average delay of regular packets and alarm packets, discard rate , and success probability of regular packets. Comprehensive numerical analysis was conducted. Our results indicate that impact of the threshold on performance measures is higher on the boundary values of the threshold. The model was proven to be efficient in analyzing the performance of IoT networks on a wide range of parameter values. These results may be used in the future to develop and assess a protocol that utilizes a scheduling algorithm with a dynamic preemption threshold to optimize the performance of the IoT network.

Fuzzy queue based switch efficiency measures for optical network

In the optical network, researchers face the major challenges and issues like improper packet scheduling, inadequate number of packet switching, less response time of switch and routing efficiency. In this paper a satisfactory model replacing the existing unsatisfactory stream of packet transmission in optical network switching for performance analysis investigation using the fuzzy queuing theory with M/M/2/∞ queuing system based on optical fuzzy queue based switch (OFQS) with a view to improve the performance of the efficiency of the novel OFQS switch design. The investigation uses the uncertainty rate of packet arrival ( $$\lambda$$ ) and rate of service (µ) of the switch and applies the Robust ranking technique to convert the fuzzy values into crisp values for trapezoidal fuzzy analysis. Simulation result shows that the proposed novel switch gives better performance in terms of low conversion switching complexity and packet loss probability as compared to the conventional switch model.

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

In wireless sensor networks (WSN), data aggregation is a widely used method. Security issues like data integrity and data confidentiality became a significant concern in data aggregation when the sensor network is deployed in a hostile environment. Many researches may carry out several works to tolerate these security issues. However, there were some limitations like delay, the arrival rate of packets, and so on. Hence, to overcome the existing problems, this approach offers a blockchain-dependent data aggregation scheme in WSN. The main intention of the proposed work is to generate a certificateless key generation so that the proposed system's secrecy rate is improved. The use of blockchain is employed for security purposes, and it enables the user to acquire the information stored internally in an effortless manner. Initially, deployment of sensor and base station (BS) is carried out, followed by node registration at which the public/private keys are generated. The computation of private hash values is carried by performing certificateless key generation. After that, the formation of blockchain is made using the PoW (Proof of Work) detection algorithm followed by the aggregation of data. In the data aggregation process, Elgammal based cryptographic approach is introduced to acquire member data, perform aggregation logic, and transfer the aggregated data. Finally, cluster-based routing is established with the use of Knapsack based cluster routing strategy. The performance investigation of the proposed system is estimated and the outcomes attained are compared with the existing techniques in terms of arrival rate, average delay, and the delay ratio of the packets. The investigation illustrates that the suggested approach is better than the traditional techniques.

Средства захвата и обработки высокоскоростного сетевого трафика

Network stacks currently implemented in operating systems can no longer cope with the packet rates offered by 10 Gbit Ethernet. Thus, frameworks were developed claiming to offer a faster alternative for this demand. These frameworks enable arbitrary packet processing systems to be built from commodity hardware handling a traffic rate of several 10 Gbit interfaces, entering a domain previously only available to custom-built hardware. In this paper, we survey various frameworks for high-performance packet IO and their interaction with a modular frameworks and specialized virtual network functions software for high-speed packet processing. We introduce a model to estimate and assess the performance of these packet processing frameworks. Moreover, we analyze the performance of the most prominent frameworks based on representative measurements in packet capturing scenarios. Therefore, we provide a comparison between them and select the area of applicability.

Is Multichannel Access Useful for Timely Information Update?

This paper investigates information freshness of multichannel access in information update systems. Age of information (AoI) is a fundamentally important metric to characterize information freshness, defined as the time elapsed since the generation of the last successfully received update. When multiple devices share the same wireless channel to send updates to a common receiver, an interesting question is whether dividing the whole channel into several subchannels will lead to better AoI performance. Given the same frequency band, dividing it into different numbers of subchannels lead to different transmission times and packet error rates (PER) of short update packets, thus affecting information freshness. We focus on a multichannel access system where different devices take turns to transmit with a cyclic schedule repeated over time. We first derive the average AoI by estimating the PERs of short packets. Then we examine bounded AoI, for which the instantaneous AoI is required to be below a threshold a large percentage of the time. Simulation results indicate that multichannel access can provide low average AoI and uniform bounded AoI simultaneously across different received powers. Overall, our investigations provide insights into practical designs of multichannel access systems with AoI requirements.

Effective Timer Count Scheduling with Spectator Routing Using Stifle Restriction Algorithm in Manet

Mobile nodes are provides unstable communication among mobile nodes, since nodes energy levels are abnormally changed. So, difficult to manage those node activities, packets are missed to collect by target node. Multi packet is broadcasted by sender node is not easy to manage frequently, since it does not have high capacity nodes. It reduces packet integrity rate, and network lifetime. In proposed algorithm is Timer count scheduling with spectator routing (TCSSR) scheme. Spectator monitors the packet transmission use of timer count. Clustering method is used to main stability for all mobile nodes available in coverage area. Stifle restriction algorithm is used to maintaining information about communication nodes, continuous sequence used to limiting sharing of the residence state of a communicate shields. Effective path selects for communication with the support of timer count report is analyzed. It enhances packet integrity rate, and network lifetime.

Energy Proficient Hybrid Secure Scheme for Wireless Sensor Networks

One way hash chain with a new key indicating the performance of the node as well to isolate malicious nodes from the network. Public key cryptography is derived using elliptical curve cryptography (ECC) have couple of key for decryption and encryption. Public key cryptography provides protection and verification using numerous algorithms. In addition secret session key is generated for secured data transmission and improve energy efficiency in WSN. Advanced encryption standard (AES) is applied for message cipher text once the key validation process gets finished. Energy proficient hybrid secure scheme (EPHSS) is proposed to provide secured and energy efficient data transmissions in WSN. To utilise the node energy in a proper way node clustering process is carried out. Clustering process efficiently reduces unnecessary energy wastage during node communication. Graded co-prime keys are generated for public and private keys, also encrypting functions are performed for providing security mechanisms. This mechanism improves security measures and simultaneously reduces energy consumption among nodes. The route should be undetectable by malicious nodes and the data should not be lacerate by the opponent node even it gets to know the public key. Identifying private key component [B, n] is difficult for malevolent; thus building it computationally infeasible for discovering decryption type at receiver side. Simulation presentations of the networks are analysed by network simulator tool. Efficiency of the proposed scheme is computed by taking delivery rates of packets which results in 18% better than the conventional ECCSAS scheme.

A Generative Adversarial Network Enabled Deep Distributional Reinforcement Learning for Transmission Scheduling in Internet of Vehicles

The Cognitive Internet of Vehicles (CIoV) is an intelligent network that embeds the cognitive mechanism in the Internet of Vehicles (IoV) to sense the environment and observe the network states to learn the optimal policies adaptively. However, one of the key challenges in CIoV systems is to design a smart agent that can smartly schedule the packet transmission for ultra-reliable low latency communication (URLLC) under extreme random and noisy network conditions. We propose a software defined network (SDN) based scheduling algorithm that leverages generative adversarial network (GAN) based deep distributional Q-network (GAN-DDQN) for learning the action-value distribution for intelligent transmission scheduling. A reward-clipping technique is proposed for stabilizing the training of GAN-DDQN against the effect of broadly spanning utility values. The extensive simulation results verify that GAN-Scheduling achieves higher spectral efficiency (SE), service level agreement (SLA), system throughput, transmission packet rate with lower transmission delay, and power consumption compared to the existing reinforcement learning algorithms.