Neighbor Discovery Research Articles

Performance Analysis of Software-Defined Multihop Wireless Sensor Networks

In this article, we propose a model-based characterization of energy consumption in a software-defined wireless sensor network (SD-WSN) architecture in an effort to examine the implications for network performance when making the WSN reprogrammable. The proposed model consists of breaking down all key functions involved in the correct functioning of an SD-WSN, namely; neighbor discovery, neighbor advertisement, network configuration, and data collection. The model is analyzed from a multihop network perspective. We consider two static SD-WSN scenarios to examine scalability, and one scenario to assess the performance implications in a pseudo-dynamic SD-WSN. Extensive simulation results are presented regarding the control overhead introduced, the percentage of alive nodes and remaining energy, and the impacts on network lifetime. We show that the accumulated control overhead is inversely proportional to the interaction period with the controller, whereas the remaining energy and the network lifetime are directly proportional to this parameter. Results show that the control overhead, for static SD-WSNs, can take up to 10%-29% of the total data flowing to the controller for the large SD-WSN and 6-19% for the small SD-WSN. For a pseudo-dynamic network, the control overhead can take up to two-thirds of the total data sent to the controller, and the network lifetime was reduced by up to 80% compared with the static scenarios.

Energy Modeling of Neighbor Discovery in Bluetooth Low Energy Networks.

Given that current Internet of Things (IoT) applications employ many different sensors to provide information, a large number of the Bluetooth low energy (BLE) devices will be developed for IoT systems. Developing low-power and low-cost BLE advertisers is one of most challenging tasks for supporting the neighbor discovery process (NDP) of such a large number of BLE devices. Since the parameter setting is essential to achieve the required performance for the NDP, an energy model of neighbor discovery in BLE networks can provide beneficial guidance when determining some significant parameter metrics, such as the advertising interval, scan interval, and scan window. In this paper, we propose a new analytical model to characterize the energy consumption using all possible parameter settings during the NDP in BLE networks. In this model, the energy consumption is derived based on the Chinese remainder theorem (CRT) for an advertising event and a scanning event during the BLE NDP. In addition, a real testbed is set up to measure the energy consumption. The measurement and experimental results reveal the relationship between the average energy consumption and the key parameters. On the basis of this model, beneficial guidelines for BLE network configuration are presented to help choose the proper parameters to optimize the power consumption for a given IoT application.

Energy-Efficient Neighbor Discovery for the Internet of Things

Internet of Things (IoT) networks are usually distributed in nature. Due to the possible mobility of IoT devices, it is common and critical for each IoT device to keep discovering who is in its neighborhood, referred to as neighbor discovery. Due to the limited battery capacity of IoT devices, it is challenging to design a neighbor discovery protocol (NDP) that can achieve both low duty cycle and low discovery latency. In this article, we build a model called Circle to characterize the process of neighbor discovery in IoT networks. Then, we give a necessary and sufficient condition for neighbor discovery and theoretically prove its correctness. This is the first time in the research community that a necessary and sufficient condition is given for neighbor discovery. According to the necessary and sufficient condition, we analytically derive a lower bound of the worst case discovery latency and demonstrate when the lower bound can be achieved. The analytical model is generic as it can be used to analyze existing NDPs. Based on the Circle model and the analysis, we propose an NDP, which is also called Circle. We compare Circle with the state-of-the-art NDPs in a real testbed, and experimental results show that Circle is superior to the existing state-of-the-art NDPs.

VN-NDP: A Neighbor Discovery Protocol Based on Virtual Nodes in Mobile WSNs.

As an indispensable part of Internet of Things (IoT), wireless sensor networks (WSNs) are more and more widely used with the rapid development of IoT. The neighbor discovery protocols are the premise of communication between nodes and networking in energy-limited self-organizing wireless networks, and play an important role in WSNs. Because the node energy is limited, neighbor discovery must operate in an energy-efficient manner, that is, under the condition of a given energy budget, the neighbor discovery performance should be as good as possible, such that the discovery latency would be as small as possible and the discovered neighbor percentage as large as possible. The indirect neighbor discovery mainly uses the information of the neighbors that have been found by a pairwise discovery method to more efficiently make a re-planning of the discovery wake-up schedules of the original pairwise neighbor discovery, thereby improving the discovery energy efficiency. The current indirect neighbor discovery methods are mainly divided into two categories: one involves removing the inefficient active slots in the original discovery wake-up schedules, and the other involves adding some efficient active slots. However, the two categories of methods have their own limitations. The former does not consider that this removal operation destroys the integrity of the original discovery wake-up schedules and hence the possibility of discovering new neighbors is reduced, which adversely affects the discovered neighbor percentage. For the latter category, there are still inefficient active slots that were not removed in the re-planned wake-up schedules. The motivation of this paper is to combine the advantages of these two types of indirect neighbor discovery methods, that is, to combine the addition of efficient active slots and the removal of inefficient active slots. To achieve this goal, this paper proposes, for the first time, the concept of virtual nodes in neighbor discovery to maximize the integrity of the original wake-up schedules and achieve the goals of adding efficient active slots and removing inefficient active slots. Specifically, a virtual node is a collaborative group that is formed by nodes within a small range. The nodes in a collaborative group share responsibility for the activating task of one member node, and the combination of these nodes’ wake-up schedules forms the full wake-up schedule of a node that only uses a pairwise method. In addition, this paper proposes a set of efficient group management mechanisms, and the key steps affecting energy efficiency are analyzed theoretically to obtain the energy-optimal parameters. The extended simulation experiments in multiple scenarios show that, compared with other methods, our neighbor discovery protocol based on virtual nodes (VN-NDP) has a significant improvement in average discovery delay and discovered neighbor percentage performance at a given energy budget. Compared with the typical indirect neighbor discovery algorithm EQS, a neighbor discovery with extended quorum system, our proposed VN-NDP method reduces the average discovery delay by up to and increases the discovered neighbor percentage by up to .

Neighbor Discovery in ASN

Generally the hubs that are placed in a system of sensors remain in static condition. The availability condition of these hubs are also likely to change due to various conditions such as remote location, change of power due to transmitting procedure and also due to the lack of coordination between the hubs which are placed adjacently. The system should continuously track its components. This process should takes place without any gap. This work deals with nonstop tracking of the adjacent component present in the framework. This procedure should utilize power to the minimum level thereby upgrading the performance metrics

Dynamic minimum spanning tree construction and maintenance for Wireless Sensor Networks

In a wireless sensor network (WSN), finding the optimal route from each node to the sink is not a straightforward task because of the distributed and dynamic characteristics of the network. For instance, the network suffers frequent changes because the channel quality varies over time and the nodes can leave or join the network at any moment. In order to deal with this variability, we propose the Dynamic Gallager-Humblet-Spira (DGHS) algorithm that builds and maintains a minimum spanning tree for distributed and dynamic networks, and we have found that DGHS reduces the number of control messages and the energy consumption, at the cost of a slight increase in the memory size and convergence time. This paper presents a detailed description of the different stages of the DGHS algorithm (neighbor discovery, tree construction and data collection), an in-depth analysis of extensive results that validates our proposal, and an exhaustive description of the GHS limitations.

Underwater wireless optical communication multi-tokens random backoff neighbor discovery method.

The cooperation of multiple pieces of equipment can greatly improve the efficiency of work when performing tasks underwater. Networking communication is a crucial technology for underwater cooperation. Wireless optical communication technology has many advantages in underwater networking communication. Neighbor discovery is a key part of networking between nodes, and it is required to establish links quickly. This paper combines the token mechanism with the random backoff mechanism and proposes a multi-tokens random backoff (MTRB) neighbor discovery method for underwater wireless optical communication. Simulation and analysis of the MTRB method show that the method has high neighbor discovery efficiency. When the parameters are selected properly, the rate of neighbor discovery by the MTRB method is increased by about 50% compared with the single token and the random backoff algorithm.

Expedited Neighbor Discovery in Directional Terahertz Communication Networks Enhanced by Antenna Side-Lobe Information

Terahertz (THz)-band (0.1-10 THz) communication is envisioned as a key wireless technology of the next decade, able to support wireless Terabit-per-second links in 6G systems. THz communication exhibits an extremely large bandwidth (tens to hundreds of GHz) at the cost of a very high path loss (>100 dB for distances beyond a few meters). Therefore, highly directional antennas (DAs) are needed simultaneously in transmission and reception at all times to establish reliable communication links. The application of highly DAs introduces new challenges in the neighbor discovery process. In this paper, a time-efficient neighbor discovery protocol for THz-band communication networks is proposed. The protocol expedites the neighbor discovery process by leveraging the full antenna radiation pattern to detect a series of effective signals and map them to the universal signal patterns, which indicate the potential direction of the signal source. A mathematical framework is developed to compare the neighbor discovery protocols with and without the antenna side-lobes information in free space. The X60 testbed is utilized to validate the proposed neighbor discovery protocol. Furthermore, a feasibility analysis of the proposed protocol inside a bounded space (e.g., a square room) is conducted. Numerical results are presented to illustrate the performance improvements achieved by the proposed protocol when compared to the traditional neighbor discovery protocols with only main-lobe information.

Reducing neighbor discovery latency in docking applications

Neighbor discovery is important for docking applications, where mobile nodes communicate with static nodes situated at various rendezvous points. Among the existing neighbor discovery protocols, the probabilistic methods perform well in average cases but they have aperiodic, unpredictable, and unbounded discovery latency. Yet, deterministic protocols can provide bounded worst-case discovery latency by sacrificing the average-case performance. In this study, we propose a mobility-assisted slot index synchronization (MASS), which is a new synchronization technique that can improve the average-case performance of deterministic neighbor discovery protocols via slot index synchronization without incurring additional energy consumption. Furthermore, we propose an optimized beacon strategy in MASS to mitigate beaconing collisions, which can lead to discovery failures in situations where multiple neighbors are in the vicinity. We evaluate MASS with theoretical analysis and simulations using real traces from a tourist tracking system deployed at the Mogao Grottoes, which is a famous cultural heritage site in China. We show that MASS can reduce the average discovery latency of state-of-the-art deterministic neighbor discovery protocols by up to two orders of magnitude.

Locally weighted classifiers for detection of neighbor discovery protocol distributed denial‐of‐service and replayed attacks

AbstractThe Internet of things requires more internet protocol (IP) addresses than IP version 4 (IPv4) can offer. To solve this problem, IP version 6 (IPv6) was developed to expand the availability of address spaces. Moreover, it supports hierarchical address allocation methods, which can facilitate route aggregation, thus limiting expansion of routing tables. An important feature of the IPv6 suites is the neighbor discovery protocol (NDP), which is geared towards substitution of the address resolution protocol in router discovery and function redirection in IPv4. However, NDP is vulnerable to denial‐of‐service (DoS) attacks. In this contribution, we present a novel detection method for distributed DoS (DDoS) attacks, launched using NDP in IPv6. The proposed system uses flow‐based network representation, instead of a packet‐based one. It exploits the advantages of locally weighted learning techniques, with three different machine learning models as its base learners. Simulation studies demonstrate that the intrusion detection method does not suffer from overfitting issues and offers lower computation costs and complexity, while exhibiting high accuracy rates. In summary, the proposed system uses six features, extracted from our bespoke dataset and is capable of detecting DDoS attacks with 99% accuracy and replayed attacks with an accuracy of 91.17%, offering a marked improvement in detection performance over state‐of‐the‐art approaches.

Passive neighbor discovery with social recognition for mobile ad hoc social networking applications

Neighbor discovery is the cornerstone of the mobile social applications over mobile ad hoc networks. Most current neighbor discovery protocols adopt a carefully designed wake-up/sleep schedule. However, a well-designed wake-up/sleep neighbor discovery schedule still might miss those neighbor nodes in the sleep state or discover undesirable neighbors with different purposes. Either results in inevitable discovery latency and unnecessary energy consumption. In this paper, we propose a flexible neighbor discovery protocol with social recognition under a passive discovery framework. In this framework, each mobile device is equipped with a wake-up radio. When a mobile node, called sponsor node, launches a neighbor detection, it will broadcast a wake-up radio signal before the hello message. Within a certain distance, the node will be triggered by its wake-up radio for a hello message, which is integrated with the social information. Furthermore, a flexible self-adjustment strategy is designed for the sponsor node to improve discovery-efficiency. Our protocol shows higher efficiency in both discovery latency and energy consumption than the traditional deterministic neighbor discovery protocols in the simulation.

Compressed sensing algorithm for neighbour discovery in mobile ad hoc networks

Considering the neighbour discovery problem in mobile ad hoc networks (MANETS) with omnidirectional antennas, all nodes want to discover the nodes within a single hop and obtain their identities. However, many existing algorithms spend an extra overhead for neighbour discovery and there is a need of response from neighbours. In this study, a slot allocation scheme is introduced for duplex communication, making all nodes recognisable to each other with a unique codeword. Then, a novel neighbour discovery algorithm based on compressed sensing to apply in this scheme is proposed; it enables all nodes to update neighbour information through the received signal after one or several frames and spends no extra overhead. Furthermore, many algorithms cannot be applied in the overload networks, but the algorithm proposed here is suited for overload networks; the upper bound for its active neighbours is limited to the performance of the network. Finally, the algorithm is validated through simulation and the effect of the three main factors on the performance of the algorithm is researched. The result implies that this algorithm can adapt to various scenarios of the MANETS.

Neighbor Discovery Optimization for Big Data Analysis in Low-Power, Low-Cost Communication Networks

Big data analysis generally consists of the gathering and processing of raw data and producing meaningful information from this data. These days, large collections of sensors, smart phones, and electronic devices are all connected in the network. One of the primary features of these devices is low-power consumption and low cost. Power consumption is one of the important research concerns in low-power, low-cost communication networks such as sensor networks. A primary feature of sensor networks is a distributed and autonomous system. Therefore, all network devices in this type of network maintain the network connectivity by themselves using limited energy resources. When they are deployed in the area of interest, the first step for neighbor discovery involves the identification of neighboring nodes for connection and communication. Most wireless sensors utilize a power-saving mechanism by powering on the system if it is off, and vice versa. The neighbor discovery process becomes a power-consuming task if two neighboring nodes do not know when their partner wakes up and sleeps. In this paper, we consider the optimization of the neighbor discovery to reduce the power consumption in wireless sensor networks and propose an energy-efficient neighbor discovery scheme by adapting symmetric block designs, combining block designs, and utilizing the concept of activating nodes based on the multiples of a specific number. The performance evaluation demonstrates that the proposed neighbor discovery algorithm outperforms other competitive approaches by analyzing the wasted awakening slots numerically.

A Clustering Approach for Multiband Neighbor Discovery on 60 GHz WLAN

The 60 GHz mmWave unlicensed band has a very large spectrum available, divided into four orthogonal channels, which allows up to 7 Gbps data rate. On the other side, the propagation in the 60 GHz band is subject to severe path loss attenuation, which can be mitigated using highly directional antennas. This high directionality brings a new challenge to neighbor discovery; the devices now need to know the exact neighbors’ physical location to successfully communicate with them. In order to expedite the neighbor discovery process, multiband protocols have been proposed in the literature in which a separate band is used for the exchange of control messages in an omnidirectional mode. Nonetheless, these proposals suffer from the control channel bottleneck problem due to the numerous messages that need to be exchanged in this channel. In this work, we propose a scheme that divides the network nodes in clusters and for each cluster we allocate one separate control channel and also a separate mmWave channel for beamforming only. The former separation allows decreasing the number of control messages exchanged in each control channel, and the latter allows the simultaneously execution of multiple beamforming. In conjunction to this clustering scheme, we propose a multiband protocol in which only the cluster leader performs beamforming and uses the control channel to propagate the information obtained during this process. We compare the existing protocols with our proposed clustering protocol in terms of average transmission time, overhead, and accuracy of neighbor discovery information.

Using multi‐address generation and duplicate address detection to prevent DoS in IPv6

The Neighbour Discovery Protocol and the Address Resolution Protocol are important protocols in the data link layer. Their functions include Internet Protocol (IP) address configuration, resolving the correspondence between an IP address and a medium access control address, and duplicate address detection (DAD). In DAD, the new address that the node is going to use is public, and thus, it is vulnerable to malicious node attacks. Moreover, address configuration is inefficient because only one address is generated and detected each time. In this study, the authors propose a multi-address generation and DAD scheme called MAGD. MAGD generates a set of addresses each time, but only discloses a part of the set during DAD, thereby reducing the risk of being attacked. DAD will only fail when all the addresses are in conflict, and thus, the efficiency of node's address configuration is enhanced. Experiments show that the additional overhead in the CPU and memory caused by MAGD's multiple address configuration is within an acceptable range. When subjected to denial-of-service (DoS) attacks, MAGD performs better than traditional encryption schemes.

IEEMARP- a novel energy efficient multipath routing protocol based on ant Colony optimization (ACO) for dynamic sensor networks

In the past few years, research and development in Wireless Sensor networks (WSNs) have gained momentum due to its numerous applications in agriculture, industrial manufacturing, military surveillance, environmental monitoring, consumer electronics, medical & healthcare, disaster recovery operations etc. Dynamic WSNs offer a robust blend of distributed sensing, computing and communication. Dynamic sensor networks are characterized by large scale deployment, dynamic and unstructured topology, power limitations, less memory and limited computational capabilities. Sensor nodes deployed in real-time environment’s for sensing data have power-limitations which hampers the overall performance of WSNs. So, the only obvious solution is to propose an energy efficient routing protocol to optimize WSN real-time performance. Different specialists have proposed various directing conventions for WSNs dependent on Fuzzy Logic, Genetic Algorithms, Meta-Heuristics, and other improvement strategies. However, every solution suggested till date has its advantages and limitations. In this paper, our primary objective is to utilize Swarm-Intelligence based approach i.e. “Ant Colony Optimization (ACO)”, for routing protocol development. Ant colony optimization (ACO) based approach gives optimal solution in terms of efficient routing path determination, energy efficiency and delivering high performance in terms of packet delivery and throughput. In this paper, we propose a novel energy efficient ACO based multipath routing protocol for WSN i.e. IEEMARP (Improvised Energy Efficient Multipath ACO based Routing Protocol). The proposed protocol works in three phases (Neighbor Discovery via Link Knowledge, Packet Transmission via exponentially weighted moving average method and ACKR packet delivery for assuring end-to-end delivery. To validate the performance of the protocol proposed, extensive simulations were conducted using NS-2.35-allinone simulator on diverse parameters like (PDR), throughput, routing overhead, energy consumption and end-to-end delay. In addition to this, the performance of protocol is compared with traditional routing protocols like Basic ACO, DSDV and DSR and other ACO based WSN protocols like ACEAMR, AntChain, EMCBR, IACR, AntHQSeN, FACOR and ANTALG. Simulation based results, clearly states that as compared to Basic ACO, DSDV and DSR, the performance of WSN network is improvised to around 10% in all performance metrics via IEEMARP routing protocol. And as compared to ACEAMR, AntChain, EMCBR and IACR, IEEMARP performs 20% better in overall functionality and almost 10–12% better as compared to AntHQSeN, FACOR, ANTLAG routing protocols in varied WSN scenarios. It is also observed that IEEMARP protocol is highly efficient in TCP packet transmission from source to destination node.

A Bi-Directional Carrier Sense Collision Avoidance Neighbor Discovery Algorithm in Directional Wireless Ad Hoc Sensor Networks.

From the perspective of media protocol control and routing of directional wireless ad hoc sensors networks, neighbor discovery protocol is an important problem to be solved first. In the past period of time, some methods have been studied on neighbor discovery protocol, but they have a common defect of link collision. The collision is caused by mutual interference of multiple transmitting nodes which are in one reception beam of the receiving node. To solve this problem, we propose a neighbor discovery algorithm using a bi-directional carrier sense collision avoidance and multi subchannels based on a scan-based algorithm (BD-SBA). Based on a scan-based algorithm (SBA), bi-directional carrier sense of the BD-SBA algorithm is performed in the first broadcast step which can reduce the collision of broadcasting the scanning request (SREQ) frames. In the second step (the reply step), the mechanism of multiple subchannels and multiple slots is applied to reduce the collision of the scanning response (SRES) frames. From the analysis and simulation, we can see that nodes using proposed algorithm can discover their neighbor nodes in fewer time. Moreover, the proposed algorithm has better performance for different beamwidths and densely distributed scenes. So it has great significance in engineering application.

In-band LOS discovery using highly directional transceivers

Directional Radio Frequency (RF) / Free-Space-Optical (FSO) transceivers are envisioned to play a great role in future generation wireless networks. They provide benefits in terms of better throughput, enhanced spectrum utilization and lower interference from unwanted sources. However, the stringent requirement of line-of-sight (LOS) communication makes it tough for a mobile node to maintain a link without a-priori information about its neighbor’s position. Hence, neighbor discovery takes a very crucial role in mobile ad hoc networks with directional transceivers. In this paper, we focus on neighbor discovery using highly directional transceivers operating on the same communication channel. We consider two nodes that can discover each other by steering their transceivers with a randomly chosen angular speed and performing a simple three-way handshaking protocol. We provide a theoretical analysis of the proposed neighbor discovery method. Additionally, we propose an algorithm where each node chooses its transceiver’s angular speed and renews it if the neighbor is not discovered within an optimal time interval. We evaluate the proposed method via simulation as well as on a system prototype. Results from both simulations and experiments show the effectiveness of the proposed neighbor discovery protocol.

Impacts Evaluation of DoS Attacks Over IPv6 Neighbor Discovery Protocol

The Neighbor Discovery Protocol (NDP) is one of the main protocols in the Internet Protocol version 6 (IPv6) suite. It provides many basic functions for the normal operations of IPv6 in a Local Area Network (LAN), such as address auto-configuration and address resolution. However, NDP has several vulnerabilities that can be used by malicious nodes to launch attacks, because NDP messages are easily spoofed. Surrounding this problem many solutions have been proposed for securing NDP but these solutions either proposed new protocols that need to be supported by all nodes or built mechanisms that require the cooperation of all nodes. In this paper we overview NDP vulnerabilities and available solutions to overcome their impacts on IPv6 network. In addition a research test bed setup to implement these vulnerabilities was introduced. Moreover attacks that prove these vulnerabilities are implemented on different types of operating systems, Windows and Linux platforms. Three network metrics throughput, delay and resources consumption have been chosen to investigate, analyze and evaluate the impacts of NDP related attacks on IPv6 link-local communication. Overall, the results had shown that performance of Linux based operating system is better than Windows based operating system.

A Practical Neighbor Discovery Framework for Wireless Sensor Networks.

Neighbor discovery is a crucial operation frequently executed throughout the life cycle of a Wireless Sensor Network (WSN). Various protocols have been proposed to minimize the discovery latency or to prolong the lifetime of sensors. However, none of them have addressed that all the critical concerns stemming from real WSNs, including communication collisions, latency constraints and energy consumption limitations. In this paper, we propose Spear, the first practical neighbor discovery framework to meet all these requirements. Spear offers two new methods to reduce communication collisions, thus boosting the discovery rate of existing neighbor discovery protocols. Spear also takes into consideration latency constraints and facilitates timely adjustments in order to reduce the discovery latency. Spear offers two practical energy management methods that evidently prolong the lifetime of sensor nodes. Most importantly, Spear automatically improves the discovery results of existing discovery protocols, on which no modification is required. Beyond reporting details of different Spear modules, we also present experiment evaluations on several notable neighbor discovery protocols. Results show that Spear greatly improves the discovery rate from to , and prolongs the sensor nodes lifetime up to times.