Neighbor Discovery Research Articles

SDN-MCHO: Software Define network based Multi-criterion Hysteresis Optimization based for reliable device routing in Internet of Things for the smart surveillance application

Internet of Things (IoT) is a sophisticated communication paradigm that is capable of integrating diverse elements from humans to interactive machines. This kind of integration provides seamless and ubiquitous communication support for mobile users. The infrastructure of IoT environment endorses multiple technologies and networks where, selecting a precise neighbor/ device becomes mandatory for the extreme surveillance application. It determines the reliability is service discovery and resource access. The process of request processing through reliable neighbor discovery is leveraged using multi-criterion hysteresis optimization (MCHO) based on SDN aided routing that is discussed in this article. The introduced routing optimization method is capable of identifying reliable IoT neighbors for request handling and delivery. This routing process depends on the activation function that classifies neighbors on the basis of three metrics namely Received Signal Strength (RSS), Rank, and Expected Transmission Count (ETX)for differentiating the neighbors on the basis of their consistency. Through differentiated hysteresis analysis, the neighbors are segregated and hence optimal devices are integrated to form a request friendly route to the access layer. The introduced routing optimization method is evaluated through appropriate experiments and the results are verified using the metrics: throughput, request delivery ratio, delay, response time, request loss and average ETX.

Auxiliary beam pair enabled initial access for mmWave D2D networks

In this paper, we propose two auxiliary beam pair (ABP) schemes, i.e., auxiliary-half (AH) and auxiliary-full (AF) to improve the initial access (IA) mechanism in a millimeter wave (mmWave) device-to-device (D2D) network. In AH, a uniform linear array (ULA) is split equally to form two simultaneous beams at both transmitter (TX) and receiver (RX) for device detection. The detection process takes place through the generation of antenna scan sequences. On the other hand, AF utilizes the full antenna array to form one beam at a time at RX and TX and searches the same sector twice in a time division manner. We also employ beamforming (BF) technique in the already existing schemes in literature, i.e., oblivious directional neighbor discovery (ODND) and Polya’s Necklaces. We compare all the schemes and it is shown that both AH and AF exhibit a high dependence on the separation between the beam pair. We also prove the dependence of discovery delay (DD) on the signal-to-noise ratio (SNR) which is contrary to the worst-case DD upper-bound given by ODND. For a reasonable value of beam separation, high SNR threshold and high TX–RX separation, AH achieves a lower DD than all other schemes. Moreover, AF outperforms all other schemes in terms of probability of miss detection (PMD) and for a considerable beam separation, low SNR threshold and low RX–TX separation, it also achieves a lower DD than ODND, Polya’s Necklaces and AH.

A Neighbor Discovery Algorithm for UAV Networking Based on Directional Antennas

Using directional antennas in Unmanned Aerial Vehicle (UAV) swarm has many advantages, such as longer transmission range, spatial reuse, anti-jamming and low probability of intercept. Neighbor discovery is a crucial step in the initialization of UAV networking. We introduce a neighbor discovery algorithm based on iterative common neighbors (ICN-ND), which can reduce the time of neighbor discovery process and the networking delay. To avoid the huge exchange-data quantity, we use the orientation and distance to represent the neighbor's location instead of latitude and longitude. Compared with the scan-based algorithm, the ICN-ND has better performance on the time to complete the neighbor discovery process and the convergence speed, which is validated the practicality by QualNet simulations.

A citizen science approach to determine perceived barriers and promoters of physical activity in a low-income South African community

ABSTRACTThe study’s objective was to assess the feasibility of using citizen science to identify and address physical activity (PA) barriers in a low-income South African community. We purposively selected as citizen scientists, eleven participants (21–45 years) from a cohort study who expressed interest in becoming physically active or were already active. They used the Stanford Neighborhood Discovery Tool mobile application to take photos and provide audio narratives of factors in their community that were barriers to or facilitated PA. Thereafter, in a facilitated workshop, citizen scientists thematically reviewed their findings, prioritised issues and proffered potential solutions. Researchers also thematically coded these data. PA levels were measured using standard questionnaires. None of the citizen scientists owned a car, and their PA was either work- or transport-related. Themes identified as priorities that hindered citizen scientists’ PA were dirt, sidewalks appropriated by vendors or homeowners, parks and gym vandalisation, and personal safety fears. Access to stadiums and parks enabled PA. Citizen scientists identified their local councillors and street committee chairpersons as fundamental for advocacy for a PA-friendly environment. Low-income community members can be empowered to gather meaningful data using mobile technology and work together to identify potential solutions for promoting PA-friendly environments.

A Low-Latency and Energy-Efficient Neighbor Discovery Algorithm for Wireless Sensor Networks.

Wireless sensor networks have been widely adopted, and neighbor discovery is an essential step to construct the networks. Most existing studies on neighbor discovery are designed on the assumption that either all nodes are fully connected or only two nodes compose the network. However, networks are partially connected in reality: some nodes are within radio range of each other, while others are not. Low latency and energy efficiency are two common goals, which become even more challenging to achieve at the same time in partially connected networks. We find that the collision caused by simultaneous transmissions is the main obstruction of achieving the two goals. In this paper, we present an efficient algorithm called Panacea to address these challenges by alleviating collisions. To begin with, we design Panacea-NCD (Panacea no collision detection) for nodes that do not have a collision detection mechanism. When n is large, we show the discovery latency is bounded by for any duty cycle (the percentage time to turn on the radio), where each node has n neighbors on average. For nodes that can detect collisions, we then present Panacea-WCD which also bounds the latency within slots. Finally, we conduct extensive evaluations and the results also corroborate our analyses.

Self-Adaptive Neighbor Discovery in Wireless Sensor Networks with Sectored-Antennas

Integration of sectored antenna in wireless networks improves network performance through increased network capacity and extended transmission range. However, incorporating sectored antenna makes the trivial process of discovering neighbors even more challenging and complicated. Moreover, due to the duty-cycled nature of Wireless Sensor Networks (WSNs), self-adaptive and distributed neighbor discovery mechanisms are highly sought-after. In this paper, we present a Neighbor Discovery with Sectored Antenna (NDSA) protocol for WSNs with the sectored antenna. NDSA distinguish itself from other protocols in four distinct ways. Firstly, the introduction of super-frame like structure to support the duty-cycled operation of WSNs. Secondly, the protocol adapts its operation according to the network dynamics by leveraging the in-network information. Thirdly, a cooperative mechanism through which nodes utilize the information about their discovered neighbors to avoid an excessive exchange of control messages. Finally, handling the channel access details to discover neighbors faster with fewer message collisions. Through a comprehensive simulation-based study, the results show that the proposed protocol outperformed the random and serialized approaches to neighbor discovery in terms of discovery latency while significantly minimizing the communication overhead.

Performance Model for Advanced Neighbor Discovery Process in Bluetooth Low Energy 5.0-Enabled Internet of Things Networks

The neighbor discovery process (NDP) plays a key role in Bluetooth low energy (BLE)-enabled applications. However, when a massive number of BLE devices are involved in the NDP, signal collisions become severer, which degrade the NDP performance seriously. To solve the problem, BLE 5.0 specifies some extended features such as advanced NDP (A-NDP). The previous works on the performance models for the NDP have focused on the basic NDP (B-NDP). Though some works considered the performance evaluations on A-NDP, they have done on simulations or testbed-based experiments. Likewise, so far, the performance analysis for A-NDP has been insufficient. In this article, we propose an analytical model to evaluate A-NDP performances, such as the signal collision probability, the discovery delay, the energy consumption, and so on. With the proposed analysis model, the performances of A-NDP are analyzed from the viewpoint of various operational environments for BLE-enabled Internet-of-Things services, and compared to those of B-NDP with extended features of Bluetooth 5.0. Besides, it showed that A-NDP is not always better than B-NDP, and we discuss the operational conditions where A-NDP or B-NDP operate effectively, respectively.

Multiple token‐based neighbor discovery for directional sensor networks

Multiple token‐based neighbor discovery for directional sensor networks

Towards a Secure IPv6 Autoconfiguration

ABSTRACTStateless Address Autoconfiguration (SLAAC) is one of the novel features introduced in IPv6 Neighbor Discovery Protocol (NDP) providing for self-configuration of nodes and supplementing the reduction of operational and deployment cost of networks. Although self-configuration elevates the idea of autonomy for network, it has also introduced vulnerabilities that require substantial solutions. The SLAAC is pivoted on the presumption that network consists of authentic and entrusted nodes, however with inception of public sector wireless networks; any node can affix to the link with trivial authentication and situation changes radically. Although some security extensions like IPsec or SeND have been proposed, but these security protocols have been reported to have serious limitations like complex cryptographic algorithms which negate their adoption. This paper revisits the stateless auto configuration process and discusses its inherent vulnerabilities. The paper surveys existing research and available defense mechanisms available to protect SLAAC. The paper also suggests some guidelines from existing literature which can further promote and supplement the research to secure the auto configuration process. Finally, a novel technique is proposed for securing IPv6 link layer communication against DoS and Man-in-the-Middle attack which can be used as an alternate approach for CGA and SeND protocol.

Accurate Analysis on Bluetooth Low Energy Neighbor Discovery

The basic concept of Bluetooth Low Energy (BLE) is short packet transmission and transient connection. It can quickly establish a connection, send data, and quickly disconnect, so that neighbor discovery is frequent and becomes an important issue. In the neighbor discovery which includes advertising and scanning, the BLE specification defines several important parameters. The parameters on the advertiser side include advertising interval, advertising duration, etc. On the scanner side, there are scan interval, scan window, etc. How to configure these parameters for quick neighbor discovery has been troublesome for BLE implementers. Prior analyses on BLE discovery process also showed some disagreements or made some incorrect assumptions. In this paper, we use rigorous probability-theory based derivations to obtain different kinds of successful discovery probabilities. We clarify disagreements in prior works and also provide insights on how to configure parameters for maximizing discovery probability. In particular, we prove that the discovery probabilities on each of the three channels are correlated. We also find that, when the advertising duration is set close to some multiples of the scan interval, an ill-fated synchronization problem will occur. To have a high discovery probability, both scan window and scan interval should be set at a large value, though it might not be good for energy saving.

ICMPv6-Based DoS and DDoS Attacks Detection Using Machine Learning Techniques, Open Challenges, and Blockchain Applicability: A Review

Although the launch of Internet Protocol version six (IPv6) addressed the issue of IPv4's address depletion, but also mandated the use of Internet Control Message Protocol version six (ICMPv6) messages in newly introduced features such as the Neighbor Discovery Protocol (NDP). This has exacerbated existing network attacks including ICMPv6-based Denial of Service (DoS) attacks and its variant form Distributed Denial of Service (DDoS) attack. Intrusion Detection Systems (IDS) aimed at tackling security issues raised by ICMPv6-based DoS and DDoS attacks have been reviewed by researchers and a general classification of existing IDSs was proposed as anomaly-based and signature-based. However, it is incredibly hard to see the overall picture of IDSs based on Machine Learning (ML) techniques with such a classification, as there is a lack of a more detailed view of the ML approach, classifiers, feature selection techniques, datasets, and different evaluation metrics. Nevertheless, recent developments in this relatively new field have not been covered such as ML-based IDSs using flow-based traffic representation. Therefore, this article specifically reviews and classifies IDSs based on ML techniques to detect ICMPv6-based DoS and DDoS attacks as single and hybrid classifiers. In addition, blockchain applicability in Collaborative IDS (CIDS) architecture based on the ensemble framework has been proposed as a solution to one of the open challenges for ICMPv6-based DoS and DDoS attacks detection problem. Moreover, this review also provides a classification of ICMPv6 vulnerabilities to DoS and DDoS attacks which would provide a reference resource for future researchers in this domain. To the best of the author's knowledge, this is the first review paper specifically focusing on IDSs based on ML techniques in this domain, as well as blockchain applicability as a possible research direction has been proposed to attract researcher's focus on building ensemble learning-based IDS models.

Denial of Service Attack on Neighbor Discovery Protocol Processes in the Network of IPv6 Link- Local

Denial of Service Attack on Neighbor Discovery Protocol Processes in the Network of IPv6 Link- Local

Match-Prevention Technique Against Denial-of-Service Attack on Address Resolution and Duplicate Address Detection Processes in IPv6 Link-Local Network

Address Resolution (AR) and Duplicate Address Detection (DAD) are considered the most important processes in Neighbour Discovery Protocol (NDP), which occurs frequently from each Internet Protocol version 6 (IPv6) host communicating with other neighbouring hosts. Two NDP messages are used during AR and DAD to communicate with one another in the same IPv6 link-local network, namely Neighbour Solicitation (NS) and Neighbour Advertisement (NA) messages. However, NDP messages have non-secure designs and lack verification mechanisms for authenticating whether incoming messages originate from a legitimate or illegitimate node. Therefore, any node in the same link can manipulate NS or NA messages and then launch a Denial-of-Service (DoS) attack. Techniques proposed to secure AR and DAD include Secure NDP (SeND) and Trust-NDP (Trust-ND); however, these techniques either entail high processing time and bandwidth consumption or are vulnerable to DoS attacks because of their designs. Therefore, to secure AR and DAD, this study aims to introduce a prevention technique called Match-Prevention, which secures target IP addresses and exchange messages (i.e. NS and NA). The processing time, bandwidth consumption and DoS prevention success rate of Match-Prevention in different scenarios are evaluated, and its performance is compared with those of existing techniques, including Standard-Process (i.e., Standard-AR and Standard-DAD), SeND and Trust-ND. Results show that Match-Prevention requires less processing time during AR and DAD processes and less bandwidth consumption compared with other existing techniques. In terms of DoS prevention success rate, the experiments show that Standard-Process and Trust-ND are unable to secure AR and DAD from DoS attacks, whilst SeND is vulnerable to flooding attacks. By contrast, Match-Prevention allows IPv6 nodes to verify the incoming message, discard the fake message before further processing and prevent a DoS attack during AR and DAD in an IPv6 link-local network.

Self-organization and Autonomous Network Survey

Purpose: The autonomic network gathers several aspects of Self-organization, which is depicted, into different autonomous function such as the Self- configuration, the Self-optimization, the Self-repair, the Self-protection, and the Self-cure. The latter is considered as one of the autonomous functions wished of a system network, which could be described by autonomous behavior is realized by structures of the control loops and loop of control. Issue: These various aspects require an architectural framework, which integrates several protocols of telecommunication as well as programs proactive and reagents for the prevention and the resolution of the unforeseen problems. To ensure a reduction of the loops of the operator, we need good management per policy. An autonomic vision must guarantee the safety and the availability of the resources for the end-users by respecting the constraints of QoS and the deadlines for replies. Goals: Depict the challenges, the interests, and the anomalies and compare the autonomic approaches of the networks which consist of discovering neighbor's in the self-organizing wireless network. These points are considered the cornerstone of extending autonomous coverage and improving performance. However, the objective is to detect the hidden node in the neighbor discovery procedure based on the simple flood caused by the uncoordinated transmission, which can cause an unnecessary loss of energy.

A middleware approach for reliable resource selection on Internet‐of‐Things

SummaryDecision making plays a vital role in the selection of resources so that they actively participate for communication and computation on the Internet‐of‐Things platform. For the same, they require the elimination of the challenges related to knowledge representation, discovery, trust, and security due to continuously changing mobility patterns, heterogeneity, interoperability, and scalability on the network. To address the challenges, a novel three‐layered approach, namely, middleware approach for reliable resource selection on Internet‐of‐Things (MARRS‐IoT), is proposed. It performs a search through neighbor discovery algorithm and evaluates trust score of the discovered resources, both locally and globally using fuzzy‐decision algorithm and performs efficient communication among resources via hybrid M‐gear protocol. The approach is simulated and compared against algorithms, namely, particle swarm optimization, ants colony optimization, and binary genetic to evaluate its performance. The obtained results support the efficacy of the MARRS‐IoT with respect to throughput and execution time.

Proposed an Algorithm for Preventing IP Spoofing DoS Attack on Neighbor Discovery Protocol of IPv6 in Link Local Network

Duplicate Address Detection (DAD) is one of the most interesting features in IPv6. It allows nodes to connect to a network by generating a unique IP address. It works on two Neighbor Discovery (ND) messages, namely, Neighbor Solicitation (NS) and Neighbor Advertisement (NA). To verify the uniqueness of generating IP, it sends that IP address via NS message to existing hosts. Any malicious node can receive NS message and can send a spoof reply, thereby initiates a DoS attack and prevents auto configuration process. In this manner, DAD is vulnerable to such DoS attack. This study aims to prevent those malicious nodes from sending spoof reply by securing both NS and NA messages. The proposed Advanced Bits Security (ABS) technique is based on Blake2 algorithm and introducing a creative option called ABS field that holds the hash value of tentative IP address and attached to both NA and NS message. We expect the ABS technique can prevent spoof reply during DAD procedure in link local network and can prevent DoS attack

Proposed an Algorithm for Preventing IP Spoofing DoS Attack on Neighbor Discovery Protocol of IPv6 in Link Local Network

Duplicate Address Detection (DAD) is one of the most interesting features in IPv6. It allows nodes to connect to a network by generating a unique IP address. It works on two Neighbor Discovery (ND) messages, namely, Neighbor Solicitation (NS) and Neighbor Advertisement (NA). To verify the uniqueness of generating IP, it sends that IP address via NS message to existing hosts. Any malicious node can receive NS message and can send a spoof reply, thereby initiates a DoS attack and prevents auto configuration process. In this manner, DAD is vulnerable to such DoS attack. This study aims to prevent those malicious nodes from sending spoof reply by securing both NS and NA messages. The proposed Advanced Bits Security (ABS) technique is based on Blake2 algorithm and introducing a creative option called ABS field that holds the hash value of tentative IP address and attached to both NA and NS message. We expect the ABS technique can prevent spoof reply during DAD procedure in link local network and can prevent DoS attack

CHIRRUP: a practical algorithm for unsourced multiple access

Abstract Unsourced multiple access abstracts grantless simultaneous communication of a large number of devices (messages) each of which transmits (is transmitted) infrequently. It provides a model for machine-to-machine communication in the Internet of Things, including the special case of radio-frequency identification, as well as neighbour discovery in ad hoc wireless networks. This paper presents a fast algorithm for unsourced multiple access that scales to ${\mathscr{C}}=2^{100}$ (active or non-active) devices (arbitrary $100$ bit messages). The primary building block is multiuser detection of binary chirps, which are simply codewords in the second-order Reed–Muller code. The chirp detection algorithm originally presented by Howard et al. (2008, 42nd Annual Conference on Information Sciences and Systems) is enhanced and integrated into a peeling decoder designed for a patching and slotting framework. In terms of both energy per bit and number of active devices (number of transmitted messages), the proposed algorithm is within a factor of $2$ of state-of-the-art approaches. A significant advantage of our algorithm is its computational efficiency. We prove that the worst-case complexity of the basic chirp reconstruction algorithm is ${\mathscr{O}}[nK(\log _2^2 n + K)]$, where $n$ is the codeword length and $K$ is the number of active users. Crucially, the complexity is sublinear in ${\mathscr{C}}$, which makes the reconstruction computationally feasible—a claim we support by reporting computing times for our algorithm. Our performance and computing time results represent a benchmark against which other practical algorithms can be measured.

A Neighbor Discovery Method Based on Probabilistic Neighborship Model for IoT

Neighbor discovery, meaning that a node receives other nodes’ radio frequency (RF) signals to be aware of their existence, is an indispensable procedure in Internet of Things (IoT)-oriented peer-to-peer (P2P) networks with energy-limited nodes. The main objective of neighbor discovery methods is to improve the energy efficiency, since node energy is usually very limited. As the neighborship maintaining time is very short in the mobile networks, neighbor discovery should be achieved in a very energy-efficient manner. The existing neighbor discovery methods only consider the received RF signals from other nodes (or neighbor table information derived from the received RF signals) as the basis of neighborship evaluation. The neighborship evaluation is inaccurate when the single source of neighbor information is employed. Inaccurate neighborship causes incorrect active slot scheduling and low energy efficiency of neighbor discovery. This paper proposes a generalized and probabilistic neighborship evaluation model to unify a variety of neighborship information in IoT-oriented P2P networks into neighborship probability values. Based on the model, we propose an energy-efficient neighbor discovery middle-ware algorithm by carefully replanning active slots of nodes according to the neighborship probability. The simulation evaluation results show that our proposed method decreases the average discovery delay by up to 11.46%, approximately, compared with other methods at the same energy budget.

Line-of-Sight Discovery in 3D Using Highly Directional Transceivers

Directional Radio Frequency (RF) / Free-Space-Optical (FSO) transceivers have the potential to play a significant role in future generation wireless networks. They are advantageous in terms of improved spectrum utilization, higher data transfer rate, and lower probability of interception from unwanted sources. Despite these advantages, communications using directional transceivers require establishment and maintenance of line-of-sight (LOS). Thus, establishment of the communication link or neighbor discovery plays an important role in mobile ad hoc networks with RF/FSO directional transceivers. We consider two nodes (Unmanned Aerial Vehicles (UAVs) or quadcopters) hovering in 3D space, each with one directional transceiver mounted on a mechanically steerable spherical structure/head, with which they can scan 360 degrees in the horizontal plane and 360 degrees in the vertical plane. We propose a novel scheme that deals with the problem of automatic discovery and establishment of LOS alignment between these nodes. We performed extensive simulations to show the effectiveness of the proposed neighbor discovery method. We also developed a proof-of-concept prototype and conducted experiments with it. The results obtained from both simulations and experiments show that, using such mechanically steerable directional transceivers, it is possible to establish communication links to similar neighboring nodes within several seconds without using GPS support.