Neighbor Discovery Research Articles

EASND: Energy Adaptive Secure Neighbour Discovery Scheme for Wireless Sensor Networks

Wireless Sensor Network (WSN) is defined as a distributed system of networking, which is enabled with set of resource constrained sensors, thus attempt to providing a large set of capabilities and connectivity interferences. After deployment nodes in the network must automatically affected heterogeneity of framework and design framework steps, including obtaining knowledge of neighbor nodes for relaying information. The primary goal of the neighbor discovery process is reducing power consumption and enhancing the lifespan of sensor devices. The sensor devices incorporate with advanced multi-purpose protocols, and specifically communication models with the pre-eminent objective of WSN applications. This paper introduces the power and security aware neighbor discovery for WSNs in symmetric and asymmetric scenarios. We have used different of neighbor discovery protocols and security models to make the network as a realistic application dependent model. Finally, we conduct simulation to analyze the performance of the proposed EASND in terms of energy efficiency, collisions, and security. The node channel utilization is exceptionally elevated, and the energy consumption to the discovery of neighbor nodes will also be significantly minimized. Experimental results show that the proposed model has valid accomplishment.

Research on the Security of IPv6 Communication Based on Petri Net under IoT.

The distribution of wireless network systems challenges the communication security of Internet of Things (IoT), and the IPv6 protocol is gradually becoming the main communication protocol under the IoT. The Neighbor Discovery Protocol (NDP), as the base protocol of IPv6, includes address resolution, DAD, route redirection and other functions. The NDP protocol faces many attacks, such as DDoS attacks, MITM attacks, etc. In this paper, we focus on the communication-addressing problem between nodes in the Internet of Things (IoT). We propose a Petri-Net-based NS flooding attack model for the flooding attack problem of address resolution protocols under the NDP protocol. Through a fine-grained analysis of the Petri Net model and attacking techniques, we propose another Petri-Net-based defense model under the SDN architecture, achieving security for communications. We further simulate the normal communication between nodes in the EVE-NG simulation environment. We implement a DDoS attack on the communication protocol by an attacker who obtains the attack data through the THC-IPv6 tool. In this paper, the SVM algorithm, random forest algorithm (RF) and Bayesian algorithm (NBC) are used to process the attack data. The NBC algorithm is proven to exhibit high accuracy in classifying and identifying data through experiments. Further, the abnormal data are discarded through the abnormal data processing rules issued by the controller in the SDN architecture, to ensure the security of communications between nodes.

Three‐dimensional scan‐based algorithm for directional neighbor discovery in ad hoc networks

SummaryIn recent years, neighbor discovery techniques using directional antennas have attracted widespread attention. Most currently available directional neighbor discovery techniques are designed based on two‐dimensional (2D) space. Although these algorithms can accomplish the discovery between nodes, the algorithm portability is poor for three‐dimensional (3D) platforms, and the application scenarios are limited since new communication scenarios such as unmanned aerial vehicle (UAV) groups and maritime fleets emerge where information needs to be delivered in real time and nodes are located in 3D space. This paper proposes a new deterministic directional neighbor discovery algorithm in 3D space named 3D scan‐based algorithm (3D‐SBA) to meet the needs of the line‐of‐sight (LOS) scenes. Four existing neighbor discovery algorithms, namely, SBA‐based random mode selection (SBA‐R), quorum, complete random algorithm (CRA), and SBA‐based leader election algorithm (LE), have been extended to our proposed 3D algorithm model for simulation and comparative analysis with 3D‐SBA. The simulation results show that the 3D‐SBA algorithm consumes 51.15%, 180.20%, 9.48%, and 17.49% of the time slots compared with the four existing algorithms mentioned above. However, the quorum algorithm has a very high node collision rate, up to 92.11%. Ultimately, the 3D‐SBA algorithm has the best performance considering the conflicts and the density of network nodes.

Reinforcement-Learning-Based Adaptive Neighbor Discovery Algorithm for Directional Transmission-Enabled Internet of Underwater Things

Reinforcement-Learning-Based Adaptive Neighbor Discovery Algorithm for Directional Transmission-Enabled Internet of Underwater Things

OCI-OLSR: An Optimized Control Interval-Optimized Link State Routing-Based Efficient Routing Mechanism for Ad-Hoc Networks

MANET (Mobile Ad hoc Networks) functionality is determined by routing protocols’ ability to adjust to atypical changes in information and communication technologies, topological systems, and connection status. Due to interference, node migration, the growth of several pathways, security, and propagation loss, MANET network configurations are dynamic. The proactive routing protocol enhances the message flow utilized in the neighborhood discovery process by using the multipoint relays (MPR) approach. In order to increase the protocol’s effectiveness and efficiency while maintaining the OLSR protocol’s reliability, the research presented in this paper proposed an improved OCI-OLSR (Optimized Control Interval-Optimized Link State Routing) that focuses on better control interval management, an advanced MPR selection process, reducing neighbor hold time as well as decreasing flooding. The suggested proposed protocol was examined using the NS3 simulator, and it was compared to the standard OLSR version and AODV(Ad-hoc On-Demand Routing) routing protocol. According to the analysis’s findings, the suggested system has a lot of promise in terms of a variety of performance metrics under diverse conditions. Overall, the article makes the case that the OCI-OLSR protocol may enhance the performance of the regular OLSR protocol in wireless ad hoc networks by addressing a number of the protocol’s flaws.

Research on personalized recommendation algorithm for micromechanical sensors based on cloud model

Abstract In order to improve the ability of micromechanical sensors to update data-matching nodes in real-time and speed up the establishment of a neighbor relationship between nodes, this paper proposes a personalized recommendation algorithm for micromechanical sensors based on the cloud model to improve the stability and real-time performance of micromechanical sensors. The algorithm uses the service attribute values of the cloud computing model and cloud clustering method to set feature term labels and establish a cloud service similarity matrix so as to meet the user-matched manufacturing service requirements. The intra-class clustering technique is applied to measure the clustering effect, and the evaluation function of each clustering number is calculated on the basis of considering the time sequence to determine the best clustering result to complete the personalized recommendation path for micromechanical sensors. To verify the application effect of the personalized recommendation algorithm for micromechanical sensors based on the cloud model, experiments are conducted. The results show that the recommendation algorithm in this paper can always control the node energy consumption below 2.5×103, and the average discovery delay is stable between 41-43 seconds. And the sensor response time is 12.1 seconds, and the average absolute deviation value is 0.23, which is nearly 1.3 times smaller than 0.53 and 0.52 of the collaborative recommendation algorithm and hybrid recommendation algorithm. It can be seen that the recommendation algorithm in this paper solves the problem of excessive neighbor discovery delay in the communication process of micromechanical sensors and effectively improves the personalized recommendation performance of micromechanical sensors.

End-to-end communication protocol in IoT-enabled ZigBee network: Investigation and performance analysis

ZigBee is the prominent technology on the Internet of Things that enables smart applications and services. However, this technology forms personal area networks, which will not directly communicate with internet end users. The IoT-enabled Zigbee devices cannot handle the IPv6 packets, which have a maximum packet size of 1280 bytes, and the transmission of IPv6 packets over ZigBee-based IEEE 802.15.4 networks, which will be performed using a gateway. via the ZigBee coordinator. The gateways and the ZigBee coordinator must complete the neighbor discovery process, which increases the coordinator’s complexity. Additional ZigBee devices suffer from header size problems, routing structures, and data forwarding issues. This paper presents an efficient end-to-end communication protocol for IoT-enabled ZigBee devices and with an Internet host using the 6LoWPAN protocol. This 6LoWPAN connects IP-based infrastructures with a collection of Zigbee devices that provide end-to-end communication to route the IPv6 packets into ZigBee-enabled IoT networks. Next, we proposed the RPL-AODV routing protocol, which refers to the capacity to forward or route the data packets from one Zigbee device to the 6LoWPAN Boarder Router (6BR) via several hops. This proposed routing protocol combines the advantages of RPL and AODV routing protocols in ZigBee devices of IoT networks that establish the path from the origin node to the target node on an on-demand basis. Finally, we evaluated the performance of this protocol with various metrics and found improved results compared to existing protocols.

Multichannel Neighbor Discovery in Bluetooth Low Energy Networks: Modeling and Performance Analysis

Bluetooth Low Energy (BLE) has become one of the enabling wireless technologies to facilitate the Internet of Things. Neighbor discovery is critical in BLE communications. BLE uses multiple (three) channels in neighbor discovery. It is challenging to achieve low-latency and low-energy-consumption BLE neighbor discovery due to the lack of analytical models for multichannel neighbor discovery. In this paper, we study BLE multichannel neighbor discovery for two advertising modes specified by BLE: periodic deterministic advertising (PDA) and pseudo-random delay advertising (RDA). We build two generic models, BLE 3-Circle model and BLE 1-Circle model, for characterizing BLE multichannel neighbor discovery. For PDA mode, we present a necessary and sufficient condition for BLE multichannel neighbor discovery, and provide a guideline for parameter setting. With the guideline, we derive the expected discovery latency in closed form, and demonstrate that the expected discovery latency is very close to a theoretical lower bound. For RDA mode, we build an analytical model based on Markov chain to accurately compute the expected discovery latency. Simulation and experimental results show accuracy of our analytical works. Interestingly, our parameter setting guideline works well for both PDA and RDA mode.

Asynchronous Massive Access and Neighbor Discovery Using OFDMA

The fundamental communication problem in the wireless Internet-of-Things (IoT) is to discover a massive number of devices and to provide them with reliable access to shared channels. Oftentimes these devices transmit short messages randomly and sporadically. This paper proposes a novel signaling scheme for grant-free massive access, where each device encodes its identity and/or information in a sparse set of tones. Such transmissions are implemented in the form of orthogonal frequency-division multiple access (OFDMA). Under some mild conditions and assuming device delays to be bounded unknown multiples of sampling intervals, sparse OFDMA is proved to enable arbitrarily reliable asynchronous device identification and message decoding with a codelength that is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(K(\log K+\log S + \log N))$ </tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> denotes the device population, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> denotes the actual number of active devices, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\log S$ </tex-math></inline-formula> is essentially equal to the number of information bits each device can send. The computational complexity for discovery and decoding can be made to be <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(K(\log K)(\log K+\log S+\log N)+K^{2}\log K)$ </tex-math></inline-formula> . As a proof of concept, a specific design is proposed to identify up to 200 active devices out of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N=2^{96}$ </tex-math></inline-formula> possible devices with up to 20 samples of delay, moderate signal-to-noise ratios, and fading. If the device population is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N=2^{48}$ </tex-math></inline-formula> instead, each active device can also transmit 48 bits to the access point at the same time. The codelength compares much more favorably with those of standard slotted ALOHA and carrier-sensing multiple access (CSMA) schemes.

Intersection-Based Unicast Routing Using Ant Colony Optimization in Software-Defined Vehicular Networks

A vehicular ad hoc network (VANET) is a mobile ad hoc network composed of communication between vehicles, between vehicles and roadside units, and between vehicles and pedestrians, in order to achieve traffic safety and entertainment services. The design of the routing protocol is very important for the realization of the service function of VANET. Local optimum and network congestion problems are restraints of traditional geographic routing protocols for VANET. In this paper, a software-defined network (SDN) based unicast routing scheme in an urban traffic environment is proposed, which uses Dijkstra’s algorithm to find a global optimal anchor path. The RSU neighbor discovery protocol is proposed, through which each RSU can discover its neighbor RSUs, and then each RSU periodically sends ant packets to its neighbor RSUs, evaluates the communication connection quality of each street segment according to the statistical data of the ant packets received, and sends the evaluation value to the SDN server in time. The SDN server has the connection quality evaluation values of all street segments in the global scope, from which an optimal anchor path can be calculated. The simulation results show that the proposed scheme has better packet delivery ratio than other related schemes.

An Efficient Neighbor Discovery Approach using HTTA Sequence Based Channel Rendezvous in CRN

An Efficient Neighbor Discovery Approach using HTTA Sequence Based Channel Rendezvous in CRN

Euclidean-Division-Based Low-Complexity Precise Analytical Approach of BLE-Like Neighbor Discovery Latency

Neighbor discovery is the procedure to establish a first contact between two wireless devices. For duty-cycled low-power devices, energy consumption is closely related to neighbor discovery latency. Actually, in recent protocols, such as Bluetooth low energy (BLE) or ANT+, neighbor discovery latency is determined by the parameters used by the devices, such as advertising interval, scan window, scan interval, and so on. A fundamental problem of the BLE-like protocol is that the exact relation between parameters and discovery latency has not been fully analyzed. In this article, we propose a Euclidean-division-based low-complexity precise analytical approach that can derive the mathematical expressions of both worst-case latency and average latency for any parameter groups. It is confirmed by simulation results that our solution can make highly accurate predictions about the value of latencies. Simulation results also show that the proposed solution has an extremely low complexity. Moreover, we derive the lower bound of latency for given duty cycles, which provides useful guidelines for the choice of energy-efficient parameter groups for BLE.

On Softwarization of Intelligence in 6G Networks for Ultra-Fast Optimal Policy Selection: Challenges and Opportunities

The emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gbps rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial Intelligence (AI) capability to support a myriad of services, such as Holographic Type Communications (HTC), tactile Internet, remote surgery, etc. However, these services require ultra-reliability, which is highly impacted by the dynamically changing environment of 6G heterogeneous tiny cells, whereby static AI solutions fitting all scenarios and devices are impractical. Hence, this article introduces a novel concept called the softwarization of intelligence in 6G networks to select the most ideal, ultra-fast optimal policy based on the highly varying channel conditions, traffic demand, user mobility, and so forth. Our envisioned concept is exemplified in a Multi- Armed Bandit (MAB) framework and evaluated within a use case of two simultaneous scenarios (i.e., Neighbor Discovery and Selection (NDS) in a Device-to-Device (D2D) network and aerial gateway selection in an Unmanned Aerial Vehicle (UAV)- based under-served area network). Furthermore, our concept is evaluated through extensive computer-based simulations that indicate encouraging performance. Finally, related challenges and future directions are highlighted.

FCPP+Miosix: Scaling Aggregate Programming to Embedded Systems

As the density of nodes capable of sensing, computing and actuation increases, it becomes increasingly useful to model an entire network of physical devices as a single, continuous space-time computing machine. The emergent behaviour of the whole software system is then induced by local computations deployed within each node and by the dynamics of the information diffusion. A relevant example of this distribution model is given by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aggregate programming</i> and its minimal set of functional constructs used to manipulate distributed data structures evolving over space and time, and resulting in robustness to changes. In this paper, we propose the first implementation of the aggregate computing paradigm targeting microcontrollers, by integrating FCPP, a C++ implementation of the paradigm, with Miosix, a modern operating system for microcontrollers with full C++ support. To the best of the author's knowledge, we are the first to present results on the effectiveness of FCPP in an embedded operating system setting as opposed to a simulation environment, thus considering tight memory and computational constraints and accounting for packet losses due to nonidealities of the radio channel. We implemented and tested on a network of WandStem nodes two benchmark applications: a network connectivity checker for network planning and preventive maintenance, and a decentralised contact tracing application. Additionally, we show that common problems in sensor networks such as neighbour discovery, construction of a graph of the network topology, coarse grain clock synchronisation as well as network monitoring and the collection of statistics (such as memory occupation data) can be easily performed thanks to the expressive semantics of aggregate programming.

An Early Wake-up and Access Barring Scheme for Improving the Probability of NDP in BLE Networks

IoT (Internet of Things) has become attractive and ubiquitous in recent years. BLE (Bluetooth Low Energy) is a protocol widely used in IoT. For BLE, it has low cost, low energy consumption, and is supported on most types of mobile phones. BLE Beacon which is widely applied in many situations, such as shopping malls and indoor navigation, is an application based on the BLE network. This paper is aimed at proposing a feasible scheme to enhance the performance of the BLE Beacon application. communications in BLE networks involve the neighbor discovery process (NDP) in the first phase to create a connection or exchange information with neighbors. When more people with mobile devices simultaneously send requests to the BLE Beacon, the success probability of the NDP decreases and then the latency of the NDP increases. It leads to poor customer experience. Therefore, we propose an Early Wake-Up and Access Barring (EWAB) scheme to improve the NDP performance among an advertiser and multiple scanners. The scheme makes good use of the information that can be contained in the advertising packet to adjust the scan interval and the backoff window dynamically. The results show that EWAB provides better performance in terms of the probability of successful discovery, the mean discovery latency, and power consumption in the BLE networks.

Deep debiased contrastive hashing

Hashing has achieved great success in multimedia retrieval due to its high computing efficiency and low storage cost. Recently, contrastive-learning-based hashing methods have achieved decent retrieval performance in label-free scenarios by learning distortion-invariant representations with Siamese networks. Their learning principle, i.e., instance discrimination, maximizes the correlation between self-augmented views and treats all others as negative samples. However, it may learn with false negative samples that are naturally similar, resulting in biased hash learning. To bridge this flaw, we reveal the between-instance similarity of naturally similar samples by exploring the latent structure of the training data. As a result, we propose the Deep Debiased Contrastive Hashing (DDCH) algorithm, using the neighborhood discovery module to explore the intrinsic similarity relationship that can help contrastive hashing reduce false negatives for superior discriminatory ability. Furthermore, we elucidate the rationale for incorporating the module into the contrastive hashing framework and explain our hashing process from an Expectation-Maximization (EM) perspective. Extensive experimental results on three benchmark image datasets demonstrate that DDCH significantly outperforms the state-of-the-art unsupervised hashing methods for image retrieval.

SADetection: Security Mechanisms to Detect SLAAC Attack in IPv6 Link-Local Network

Neighbour Discovery Protocol (NDP) attacks are a serious security concern for IPv6. Attackers utilise the Stateless Address Auto-configuration (SLAAC) NDP attack type to target the SLAAC process. SLAAC attacks can compromise an IPv6 link-local network and expose private data. Attack detection mechanisms including RA-Guard, Snort IPv6 Plugin, SLAAC detection method by Buenaventura et al., and SLAAC Security Method by Massamba et al. have been proposed by researchers to address this issue. However, the detection algorithms have a number of shortcomings, including a complete reliance on preconfigured router databases. Additionally, fragment packets and packets with Hop-by-Hop Options and Destination Options extension headers are not detectable by the detection techniques for hidden RA messages. In this study, a rule-based detection method called SADetection is proposed for use in IPv6 link-local networks to identify SLAAC attacks. Both an illegal Router Advertisement (RA) message and a concealed RA message in a packet with an extension header have been found by SADetection. SADetection has demonstrated a detection accuracy of 98\% percent and the capacity to defend an IPv6 link-local network from SLAAC attacks.

A Hybrid Approach to Neighbour Discovery in Wireless Sensor Networks

In the contemporary era of unprecedented innovations such as Internet of Things (IoT), modern applications cannot be imagined without the presence of Wireless Sensor Network (WSN). Nodes in WSN use neighbour discovery (ND) protocols to have necessary communication among the nodes. Neighbour discovery process is crucial as it is to be done with energy efficiency and minimize discovery latency and maximize percentage of neighbours discovered. The current ND approaches that are indirect in nature are categorized into methods of removal of active slots from wake-up schedules and intelligent addition of new slots. The two methods are found to have certain drawbacks. The first category disturbs original integrity of wake-up schedules leading to reduced chances of discovering new nodes in WSN as neighbours. When second category is followed, it may have inefficient slots in the wake-up schedules leading to performance degradation. Therefore, the motivation behind the work in this paper is that by combining the two categories, it is possible to reap benefits of both and get rid of the limitations of the both. Making a hybrid is achieved by introducing virtual nodes that help maximize performance by ensuring original integrity of wake-up schedules and adding of efficient active slots. Thus a Hybrid Approach to Neighbour Discovery (HAND) protocol is realized in WSN. The simulation study revealed that HAND outperforms the existing indirect ND models.

Fedab: A Low-Latency Energy-Efficient Proactive Neighbor Discovery Protocol in MLDC-WSN

Mobile Low-Duty-Cycle Wireless Sensor Network (MLDC-WSN) is a new type of wireless multi-hop network composed of sensor nodes that have mobility and sleep for a long time in a wireless self-organizing manner. Neighbor discovery protocols are used for sensor nodes to discover neighbor nodes within their communication range and can provide neighbor information to other protocols. MLDC-WSN uses low duty cycle technology to reduce energy consumption, and captures dynamic environmental information through the movement of nodes. However, the random mobility and long dormancy of nodes lead to frequent changes in the network topology, and nodes need to consume a lot of energy and time to discover all their neighbors. The sensor nodes are often powered by energy-limited batteries, and battery replacement is difficult. How to implement efficient neighbor discovery with low-latency and low-energy is a challenge of current research. Different from the previous slot model that couples the listening and transmitting of beacons in one slot, this paper proposes a new discovery schedule based on the slot model that separates the listening and transmitting of beacons. The discovery schedule can guarantee unidirectional discovery. And the node proactively transmits the beacon to accelerate bidirectional discovery after unilaterally discovering its neighbor nodes. On this basis, a proactive asynchronous neighbor discovery protocol called Fedab is proposed in this paper. Ignoring beacon collisions and other realistic interference factors, Fedab can enable neighbor discovery within the theoretical worst-case discovery latency. Moreover, Fedab is extended to the scenario where nodes perform different duty cycles, i.e., asymmetric scenarios. After experimental simulations and numerical analysis, the Fedab protocol has better performance compared to other existing neighbor discovery protocols.

A survey on network admission control solution in 6LoWPAN using cryptographic mechanism

This paper introduces a robust network admission control (NAC) solution tailored specifically for 6LoWPAN Wireless Sensor Networks (WSN), aiming to enhance the overall security infrastructure. By implementing stringent measures, this solution not only safeguards legitimate nodes but also fortifies the network against potential security threats originating from unauthorized nodes attempting to communicate with both legitimate nodes and the Internet. The solution enhances security through innovative features for administrative nodes, including node presence detection and robust authentication. It incorporates data filtering to swiftly identify and discard unauthorized frames, strengthening network resilience. Established protocols like Neighbor Discovery and DSDV facilitate seamless integration. This strategic utilization minimizes the reliance on additional control messages, thereby optimizing the network's efficiency and resource utilization. The solution utilizes cryptographic methods, particularly the XOR algorithm, to enhance data security in wireless sensor networks. This algorithm ensures authenticity, integrity, and freshness of transmitted data frames, providing robust protection against manipulation and bolstering network security. The proposed network admission control solution addresses security risks in 6LoWPAN WSN and integrates advanced features for a strong and efficient overall security infrastructure in wireless sensor networks.