Data Dissemination Protocol Research Articles

A smart surveillance system utilizing modified federated machine learning: Gossip‐verifiable and quantum‐safe approach

SummaryEdge computing has the capability to process data closer to its point of origin, leading to the development of critical autonomous infrastructures with frequently communicating peers. The proposed work aims to evaluate the effectiveness of security and privacy mechanisms tailored for distributed systems, particularly focusing on scenarios where the nodes are closed‐circuit television (CCTV) systems. Ensuring public safety, object tracking in surveillance systems is a vital responsibility. The workflow has been specifically crafted and simulated for the purpose of weapon detection within public CCTV systems, utilizing sample edge devices. The system's primary objective is to detect any unauthorized use of weapons in public spaces while concurrently ensuring the integrity of video footage for use in criminal investigations. The outcomes of prior research on distributed machine learning (DML) techniques are compared with modified federated machine learning (FML) techniques, specifically designed for being Gossip verifiable and Quantum Safe. The conventional federated averaging algorithm is modified by incorporating the secret sharing principle, coupled with code‐based McEliece cryptosystem. This adaptation is designed to fortify the system against quantum threats. The Gossip data dissemination protocol, executed via custom blockchain atop the distributed network, serves to authenticate and validate the learning model propagated among the peers in the network. It provides additional layer of integrity to the system. Potential threats to the proposed model are analyzed and the efficiency of the work is assessed using formal proofs. The outcomes of the proposed work demonstrate that the trustworthiness and consistency are meticulously preserved for both the model and data within the DML framework on the Edge computing platform.

SCIDP–Secure cloud-integrated data dissemination protocol for efficient reprogramming in internet of things

SCIDP–Secure cloud-integrated data dissemination protocol for efficient reprogramming in internet of things

Energy efficient data dissemination in wireless sensor network enabled IoT using domain‐adaptive message passing graph neural network

SummaryIn the past few years, restricted wireless sensor networks (WSNs) enabled the Internet of Things (IoT) have attracted significant attention and expansion to enhance service delivery and resource efficiency. Dissemination is a service offered by WSN that uses radio transmission and over‐the‐air programming for updating the deployed sensor nodes through online. The centralized data dissemination methods are replaced by the distributed approaches because they affect the drawbacks of a single point of failure, no scalability, and insecurity. Therefore, an Energy Efficient Protocol for Data Dissemination in Wireless Sensor network‐enabled IoT using Domain‐Adaptive Message Passing Graph Neural Network (EEP‐WSN‐IoT‐DMPGNN) is proposed in this paper. The nodes are formed as clusters utilizing the Deep Fuzzy Curriculum Clustering (DFCC) technique that rewards nodes belonging to a given cluster. By using the Crayfish Optimization Algorithm (COA), the Cluster Head (CH) selection optimally chose the ideal CH and satisfies the multiple objective functions, such as energy, delay, traffic density, and distance. Afterward, domain‐adaptive Message Passing Graph Neural Network (DMPGNN) based routing protocol is developed, the input given to the routing protocol includes a sink, action history, future node, and maximum‐distance node, which attains enhanced data transfer in the chosen path. The proposed technique attains a lower no. of dead nodes, lower energy consumption, and higher Network Lifetime while analyzed with existing techniques, such as routing technique depending on deep learning for effectual data transmission in 5G WSN communication (DL‐RPDT‐WSN), Reinforcement‐Learning base energy effectual optimized routing protocol in WSN (RL‐EERP‐WSN), and Energy‐efficient intellectual routing method for IoT‐enabled WSN (EIR‐IoT‐WSN), respectively.

Understanding Concurrent Transmissions: The Impact of Carrier Frequency Offset and RF Interference on Physical Layer Performance

The popularity of concurrent transmissions (CT) has soared after recent studies have shown their feasibility on the four physical layers specified by BLE 5, hence providing an alternative to the use of IEEE 802.15.4 for the design of reliable and efficient low-power wireless protocols. However, to date, the extent to which physical layer properties affect the performance of CT has not yet been investigated in detail. This article fills this gap and provides an extensive study on the impact of the physical layer on CT-based solutions using IEEE 802.15.4 and BLE 5. We first highlight through simulation how the impact of errors induced by relative carrier frequency offsets on the performance of CT highly depends on the choice of the underlying physical layer. We then confirm these observations experimentally on real hardware and with varying environmental conditions through an analysis of the bit error distribution across received packets, unveiling possible techniques to effectively handle these errors. We further study the performance of CT-based data collection and dissemination protocols in the presence of RF interference on a large-scale testbed, deriving insights on how the employed physical layer affects their dependability.

Data dissemination protocol for VANETs to optimize the routing path using hybrid particle swarm optimization with sequential variable neighbourhood search

Data dissemination protocol for VANETs to optimize the routing path using hybrid particle swarm optimization with sequential variable neighbourhood search

Reliable and Efficient Message Dissemination by Adaptive Relay Selection in Vehicular Networks

Successful message reception of an emergency event is the key objective of emergency message dissemination protocols in vehicular networks. This research paper proposes a new multi-hop data dissemination protocol for relay node selection for emergency events in vehicular networks. The proposed protocol is dynamically adaptive to vehicular density and link quality during the data dissemination process. Thus making it a viable solution for both practical scenarios. The protocol is evaluated by considering different vehicle density and network size. Simulation outputs confirm considerable performance improvements over existing distance-dependent protocols. In urban traffic density scenarios, over 20% improvements are achieved in delay performance to the furthest distance-based protocol with increased reliability and scalability in vehicular networks.

Employing a UAV Unit for the Data Dissemination Protocol in Vanet

Employing a UAV Unit for the Data Dissemination Protocol in Vanet

Comprehensive survey on data dissemination protocols for efficient reprogramming in Internet of Things

SUMMARYThe Internet of Things (IoT) is a wide network of interconnected intelligent objects which can recognize the natural phenomenon of the deployed environment with the help of sensors and transmit the sensed information to other devices via internet as a backbone. Data dissemination is one of the important activities in IoT. Data dissemination is the process of updating the design framework of the sensor nodes to make the sensor nodes in IoT device to perform the intended services. Reprogramming is the process of entire change in the configuration parameters of the nodes and reconfiguration is the process of minor modification in the configuration parameter. In data dissemination, the design framework is typically disseminated through the sensor nodes to the base station using multi‐hop communication. In this article, a comprehensive survey on various dissemination approaches such as topology, reliability, scalability, structure, centralized, and de‐centralized are carried out to highlight with their advantages and limitations. Moreover, the proposed survey provides a detailed analysis on both reprogramming–related to data dissemination and reconfiguration‐related to data dissemination in order to improve the efficiency of data dissemination.

Blockchain-Integrated Multiagent Deep Reinforcement Learning for Securing Cooperative Adaptive Cruise Control

Connected and Autonomous Vehicles (CAVs) are an emerging solution to the issues of safe and sustainable transportation systems in the future. One major transport technology for CAVs is Cooperative Adaptive Cruise Control (CACC), for which unsignalized autonomous intersection crossing is a growing use case. CACC relies heavily on inter-vehicular communication and is thus vulnerable to message forgery and jamming attacks. Most solutions for CACC focus exclusively on enhancing efficiency or security but do not offer an integrated framework for achieving both on a large scale. In this paper, we propose a Blockchain-integrated Multi-Agent Deep Reinforcement Learning (Block-MADRL) architecture for enhancing the efficiency of CACC while cooperatively detecting attacks, reducing the fuel efficiency of identified attackers and securely notifying the overall network. Our approach uses multi-agent deep reinforcement learning to find fuel and throughput optimizing solutions for CACC and a cooperative verification mechanism based on Extended Isolation Forest (EIF) for attack detection. Attacker data is securely stored in a Road Side Unit (RSU) level blockchain, and we design a low-latency, high throughput consensus protocol for speedy and secure data dissemination. Simulation results indicate over 29.5% better lane throughput with our approach during acceleration forgery attack, up to 23% induced reduction in fuel efficiency of malicious vehicles, 17.6% higher blockchain throughput through our consensus protocol and over 8% improvement in attack detection rate compared to the state-of-the-art.

Simulation of IoT-based Vehicular Ad Hoc Networks (VANETs) for Smart Traffic Management Systems

Nowadays, traffic congestion and increasing road accidents have become a major concern for both developed and developing countries. To overcome this challenge, an internet of things- (IoT-) based Vehicular Ad Hoc Network (VANET) system is proposed in which vehicles interact with other vehicles and infrastructure. These self-organized ad hoc vehicle networks not only boost traffic safety but also enhances the efficiency of traffic management systems. The VANET systems are beneficial in busy locations, where improved data dissemination protocols are used to categorize a vehicle’s transmission. However, the performance of these VANETs is also hampered by network splits and insufficient connections. Under these situations, the proposed simulation model reduces broadcast storms by minimizing redundancies, which is equally beneficial for both rural and urban settings. The suggested Next Forwarder Vehicle (NFV) protocol is based on three factors: position, distance, and orientation. Moreover, the DDP4V technique is used to analyse each of these features. Results indicate that DDP4V is compatible with 96% of all traffic scenarios and simulation durations. It can transport data packets 60% faster due to its broadcast suppression capabilities. Also, in comparison to AID and DBRS, DDP4V has fewer dispersed packets, which results into reduced retransmissions. For 200 automobiles/km2, all these techniques accomplish 35–40% of the needed cars. However, the coverage also faces some restrictions since data packets only reach vehicles on the same side as the originating vehicle. Similarly, DDP4V delivers 90% coverage for 400 vehicles/km2, which is 30% greater than prior techniques. It is observed that the proposed protocol reduces broadcast storms by employing a waggon wheel to choose the next forwarding vehicle. In high-traffic areas, it outperforms standard techniques. Similarly, it employs a patchwork of vehicles outside of the impacted region to convey data. The industrial IoT-based VANETs provide an effective tool to monitor and control traffic besides reducing the number of traffic accidents.

Security Improvements for Connected Vehicles Position-Based Routing

The constant growing on the number of vehicles is increasing the complexity of traffic in urban and highway environments. It is paramount to improve traffic management to guarantee better road usage and people’s safety. Through efficient communications, Vehicular Ad hoc Networks (VANETs) can provide enough information for traffic safety initiatives, daily traffic data processing, and entertainment information. However, VANETs are vulnerable to malicious nodes applying different types of net-work attacks, where an attacker can, for instance, forge its position to receive the data packet and drop the message. This can lead vehicles and authorities to make incorrect assumptions and decisions, which can result in dangerous situations. Therefore, any data dissemination protocol designed for VANET should consider security issues when selecting the next-hop forwarding node. In this paper, we propose a security scheme designed for position-based routing algorithms, which analyzes nodes position, transmission range, and hello packet interval. The scheme deals with malicious nodes performing network attacks, faking their positions forcing packets to be dropped. We used the Simulation of Urban MObility (SUMO) and Network Simulator-version 3 (NS-3) to compare our proposed scheme integrated with two well-known position-based algorithms. The results were collected in an urban Manhattan grid environment varying the number of nodes, the number of malicious nodes, as well as the number of source-destination pairs. The results show that the proposed security scheme can successfully improve the packet delivery ratio while maintaining low average end-to-end delay of the algorithms.

Efficient Next-Hop Selection in Multi-Hop Routing for IoT Enabled Wireless Sensor Networks

The Internet of Things (IoT) paradigm allows the integration of cyber and physical worlds and other emerging technologies. IoT-enabled wireless sensor networks (WSNs) are rapidly gaining interest due to their ability to aggregate sensing data and transmit it towards the central or intermediate repositories, such as computational clouds and fogs. This paper presents an efficient multi-hop routing protocol (EMRP) for efficient data dissemination in IoT-enabled WSNs where hierarchy-based energy-efficient routing is involved. It considers a rank-based next-hop selection mechanism. For each device, it considers the residual energy to choose the route for data exchange. We extracted the residual energy at each node and evaluated it based on the connection degree to validate the maximum rank. It allowed us to identify the time slots for measuring the lifetime of the network. We also considered the battery expiry time of the first node to identify the network expiry time. We validated our work through extensive simulations using Network Simulator. We also implemented TCL scripts and C language code to configure low-power sensing devices, cluster heads and sink nodes. We extracted results from the trace files by utilizing AWK scripts. Results demonstrate that the proposed EMRP outperforms the existing related schemes in terms of the average lifetime, packet delivery ratio, time-slots, communication lost, communication area, first node expiry, number of alive nodes and residual energy.

Toward an Efficient Data Dissemination Protocol for Vehicular Ad-Hoc Networks

Data Dissemination protocols are used for several vehicular applications, varying from warning messages to real-time video delivery. The majority of literature solutions consider the distance from the sender to choose the vehicle to forward the message. Basically, the solutions introduce a delay in the forwarding procedure, which is inversely proportional to the distance from the sender vehicle. In order to improve the forwarding procedure, this work introduces the concept of Road Covered Area to improve the overall data dissemination process and we describe how to calculate the road covered area by a node transmission.We present the D&RCA, the combination of Distance and Road Covered Area strategies to enhance the re-transmission during communication. Instead of considering the distance, we propose a function to combine the distance and road covered area to introduce a small delay before re-transmissions. We compare the proposed protocol with literature solutions considering the metrics of number of collisions, network coverage and communication latency for different density of vehicles in the network. When the network has 700 vehicles/km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the data dissemination latency and number of collisions of the proposed D&RCA is, respectively, 1.24 and 1.32 times smaller than the literature solutions. When we increase the density of vehicles, all evaluated solutions present a network coverage above 90%.

Red deer optimization algorithm inspired clustering-based routing protocol for reliable data dissemination in FANETs

Flying ad hoc Networks (FANETs) are considered to possess dynamic topology due to the uncertain and rapidly changing mobility of Unmanned Aerial Vehicles (UAVs). The routing in FANET is determined to be unstable due to the restricted battery resources and the constantly changing mobility characteristics of UAVs. In this situation, topology table maintenance and iterative estimation of new routes in this dynamic environment incurs high delays and communication overhead. This dynamically changing topology also wastes the restricted battery source and reduces the network throughput of UAVs. Clustering is a type of routing, which is identified as the suitable candidate ideal for resolving the issues for limited resources in order to enhance network performance with improved throughput, scalability and minimized communication overhead. In this paper, Red Deer Optimization Algorithm Inspired Clustering-based Routing Protocol (RDOAICRP) for minimizing the issue of instability and mobility during the process of reliable data dissemination in FANETs. This proposed RDOAICRP included the benefits of a Red Deer Optimization Algorithm for cluster head selection and energy-aware cluster formation. It utilized a function for path detection based on the distance between the UAVs, number of neighbors and weighted residual energy for achieving efficient communication. It inherits significant cluster maintenance by a continuous monitoring process that estimates the energy level associated with each individual UAVs in a cluster. The potential of the proposed RDOAICRP is explored based on the cluster lifetime, packet delivery success probability, energy consumptions and cluster construction time with the benchmarked clustering-based routing protocols.

Security Improvements for Connected Vehicles Position-Based Routing

The constant growing on the number of vehicles is increasing the complexity of traffic in urban and highway environments. It is paramount to improve traffic management to guarantee better road usage and people’s safety. Through efficient communications, Vehicular Ad hoc Networks (VANETs) can provide enough information for traffic safety initiatives, daily traffic data processing, and entertainment information. However, VANETs are vulnerable to malicious nodes applying different types of net-work attacks, where an attacker can, for instance, forge its position to receive the data packet and drop the message. This can lead vehicles and authorities to make incorrect assumptions and decisions, which can result in dangerous situations. Therefore, any data dissemination protocol designed for VANET should consider security issues when selecting the next-hop forwarding node. In this paper, we propose a security scheme designed for position-based routing algorithms, which analyzes nodes position, transmission range, and hello packet interval. The scheme deals with malicious nodes performing network attacks, faking their positions forcing packets to be dropped. We used the Simulation of Urban MObility (SUMO) and Network Simulator-version 3 (NS-3) to compare our proposed scheme integrated with two well-known position-based algorithms. The results were collected in an urban Manhattan grid environment varying the number of nodes, the number of malicious nodes, as well as the number of source-destination pairs. The results show that the proposed security scheme can successfully improve the packet delivery ratio while maintaining low average end-to-end delay of the algorithms.

A Markov chain-based data dissemination protocol for vehicular ad hoc networks

Enhancing road safety and offering infotainment services are of utmost importance to today’s Intelligent Transport System (ITS). Technically speaking, an ITS is based on self-organizing wireless networks, known as vehicular ad hoc networks (VANETs). In the latter, mobile vehicles can track, compile and share reports on-road travel, driving conditions, and threats, for example, road accidents, in real-time. The spread of such data in VANET would actually improve road safety and driving comfort. In this regard, designing efficient data dissemination protocols in VANET has become a pivotal issue, attracting the interest of academic researchers, networking experts, and automotive companies. This paper introduces a new adaptive geocast data dissemination protocol called Markov Chain-based data Dissemination Protocol (MCDP). MCDP relies on the forward-if-relevant principle to dynamically determine the Zone Of Relevance (ZOR) of the event. We consider the event worth enough for a vehicle whenever there is a high probability that it will meet the event location shortly. Indeed, we introduce a mathematical model to manage vehicle mobility in the road network. Besides, we design a new method for accurately assessing the event relevance to the receiving vehicle. Simulation results underscore MCDP outperforms the pioneering baseline protocols in terms of effectiveness and efficiency.

A robust and efficient adaptive data dissemination protocol based on smart relay selection in vehicular networks

A robust and efficient adaptive data dissemination protocol based on smart relay selection in vehicular networks

BlueFlood

Bluetooth is an omnipresent technology, available on billions of devices today. While it has been traditionally limited to peer-to-peer communication and star networks, the recent Bluetooth Mesh standard extends it to multi-hop networking. In addition, the Bluetooth 5 standard introduces new modes to allow for increased reliability. In this article, we evaluate the feasibility of concurrent transmissions (CT) in Bluetooth via modeling and controlled experiments and then devise an efficient network-wide data dissemination protocol, BlueFlood, based on CT for multi-hop Bluetooth networks. First, we model and analyze how CT distorts the received waveform and characterize the Bit Error Rate of a Frequency-Shift Keying receiver to show that CT is feasible over Bluetooth. Second, we verify our analytic results with a controlled experimental study of CT over Bluetooth PHY. Third, we present BlueFlood, a fast and efficient network-wide data dissemination in multi-hop Bluetooth networks. In our experimental evaluation, in two testbeds deployed in university buildings, we show that BlueFlood achieves 99.9% end-to-end delivery ratio with a duty-cycle of 0.4% for periodic dissemination of advertising packets of 38 bytes with 200 milliseconds intervals at 2 Mbps. Moreover, we show that BlueFlood can be received by off-the-shelf devices such as smartphones, paving a seamless integration with existing technologies.

Hybrid communication architecture in VANETs via named data network

SummaryThe limitations of the transmission control protocol/Internet protocol (TCP/IP) model have given birth to a new futuristic trend called named data networking (NDN), focusing on retrieving the desired data by using content names instead of host addresses. In this context, we proposed another NDN architecture named hybrid communication in vehicular ad hoc networks (VANETs) via named data network (HCIV‐NDN) to reduce packet loss, eliminate the unnecessary message exchange, and to assume that in one cluster not all receivers nodes rebroadcast. Also, it investigates the NDN concept to vehicle to road side unit (V2R), vehicle‐to‐vehicle (V2V), and road side unit to infrastructure (R2I) plus vehicle‐to‐infrastructure (V2I) communications to enlarge the connectivity of vehicles. The vehicles are clustered and can communicate with the base station, with road side unit (RSU), and among them to define a new data dissemination protocol. Hence, the HCIV‐NDN mechanism applies two types of timers to select some farthest nodes as forwarder to rebroadcast packets at different times. Thus, we study the performance of our HCIV‐NDN with node density effects for smart cities and then we compare it with the existing location‐based deferred broadcast (LBDB) scheme. Simulation results exhibited that HCIV‐NDN scheme achieves more than 90% in terms of the cache‐hit ratio when the percent of consumers interested in the same data is about 50%. Then it performs better than LBDB in terms of satisfaction ratio, packet loss ratio, and the average delay in a suburban scenario.

A D2D assisted multi‐hop data dissemination protocol for inter‐UAV communication

SummaryUnmanned aerial vehicles (UAVs) are key components of future Internet of Things as they facilitate efficient data sensing and transmission. However, UAVs will be sparsely placed and data dissemination among UAVs is a challenge. In this regard, cellular users can help to propagate the data between UAVs by using multi‐hop device‐to‐device (D2D) communication. A key challenge for multi‐hop D2D communication to support inter‐UAV communication is to select optimal forwarding D2D nodes that reduce the communication delay. In this paper, we propose a multi‐hop data dissemination protocol for inter‐UAV communication using D2D‐enabled user equipment (UEs). We consider factors such as channel quality and queuing delay to find suitable forwarding D2D nodes. To improve reliability of transmission, the proposed protocol selects forwarding nodes within a forwarding area where packets can be successfully received. Simulation results verify that the proposed protocol can reduce end‐to‐end delay and improve reliability of multi‐hop UAV data dissemination.