Wireless Nanosensor Networks Research Articles

An Energy-Balance Clustering Routing Protocol for Intra-Body Wireless Nanosensor Networks

Aims and Background: Numerous sensor nodes spread out across the surveillance region form the Wireless-Sensor Network (WSN), a smart, self-organizing network. Since the lumps can typically only be motorized by batteries, creating a WSN while maintaining an optimal energy balance and extending the network's lifetime is the biggest issue. Methods: A novel network architecture that integrates nanotechnology with sensor networks is known as a Wireless-NanoSensor-Network(WNSN). A new area of focus in research is intra-bodyiWNSNs, which are WNSNs with promising potential applications in biomedicine, damage detection, and intra-body health monitoring. We suggest an energy-balance-clustering-routing protocol (EBCR) for iSN nodes that have limited energy storage, short communication range, and low computation and processing capabilities. The protocol uses a novel hierarchical clustering approach to lessen the communication burden on nano-nodes. Results: Cluster nano-nodes can use one-hop routing to send data directly to the Cluster-Head(CH) nodes, and the CH-nodes can utilize multi-hop routing to send data to the nano control node. In addition, selecting the next hop node to minimize energy usage while guaranteeing successful data packet delivery involves balancing distance and channel capacity. The protocol's strengths in energy efficiency, network-lifetime extension, and data-packet transmission success rate were highlighted by the simulation results. Conclusion: It is clear that the EBCR protocol is a viable option for iWNSNs' routing system.

Cooperative communication and relay node selection algorithm based on SWIPT

The development of nanotechnology and the emergence of new materials such as graphene make wireless nanosensor networks (WNSN) based on electromagnetic communication possible. Due to the energy, computing power and transmission distance carried by nano-nodes are extremely limited, nanonetworks are usually ultra-dense, so nanonetworks are usually cluster-managed. Aiming at the problem of data transmission failure caused by poor link quality or insufficient energy in inter-cluster transmission, a relay node selection algorithm (RNS-AHP) based on simultaneous wireless information and power transfer (SWIPT) and analytics hierarchy process (AHP) is proposed. The algorithm is based on the SWIPT cooperative communication model, and uses the AHP to calculate the weights of four factors: the distance of the relay node, the channel capacity, the remaining energy of the relay node and the signal-to-noise ratio of the relay node receiver in the process of relay node selection. According to the weight, the weight of the candidate relay node is obtained as the selection criterion of the relay node. The simulation results show that the RNS-AHP algorithm can improve the average throughput, the success rate of data packet transmission and the energy efficiency.

An Adaptive Distributed Broadcast Protocol for Wireless Nanosensor Networks

An Adaptive Distributed Broadcast Protocol for Wireless Nanosensor Networks

Hybrid FFBAT optimized multi-hop routing in Internet of Nano-Things

Wireless Nano-Sensor Networks (WNSNs) are molecular-level networks consisting of nano-machines that have very limited energy capacity. Due to the high energy consumption of the nodes in WNSNs during the data transmission, energy-efficient routing algorithms may help to reduce overall energy consumption. On the other hand, metaheuristics are useful for solving problems such as routing, energy, security and connectivity for traditional sensor networks. Therefore, this study proposes a hybrid Firefly and BAT Optimization based energy-efficient multi-hop routing algorithm, namely nanoFFBAT, between nano-sensor nodes and randomly placed convenient nano-routers for WNSNs-supported Internet of Nano-Things (IoNT) applications. In this hybrid approach, Firefly optimization is used for selecting the most energy-efficient neighbor by a nano-sensor node based on the flashing behavior of fireflies on the way for forming multi-hop paths and the BAT algorithm is adapted for building energy-efficient routing path discovery in WNSNs and also finding the optimal solution in solution space. In addition, nanoFFBAT detects redundant nodes on the energy-efficient multi-hop routing paths and shortens these paths if there exists any neighbor node already has been selected. The results of nanoFFBAT are compared with the shortest path from a nano-node to the convenient nano-router, a genetic algorithm-based energy-efficient routing algorithm for sensor networks and a WNSN routing protocol in the literature. According to the experimental simulation results, nanoFFBAT saves 306.929 nJ on a path on average and prolongs network lifetime 16.298 times more on average compared to the mentioned algorithms.

Distributed routing and self-balancing algorithm for Medical IoNT

Continuity of data flow from the body to the medical devices takes an important role in order to follow the results of the patients in real-time. The nano-sensors that undertake these tasks consume energy during the processes and become offline when they run out of energy. This causes disconnection of the nodes and interruption of the data flow. Therefore, the network connection should be provided by the remaining nodes. In this paper, a novel distributed routing and self-balancing Wireless Nano-Sensor Networks (WNSNs) algorithm for Medical Internet of Nano-Things (MIoNT)-based healthcare applications, namely SECAMENT, is proposed. The backbone of the network is built by clustering the nodes and selecting cluster heads (CHs) iteratively. For balancing the network, SECAMENT binds the nodes whose CHs become offline to the nearest available clusters or selects new CHs amongst them. According to the simulation results, SECAMENT provides connectivity of WNSNs up to 46.548% and longer network uptime up to 44.963% on average compared to a clustering-based distributed routing and coordinate algorithm for WNSNs and unbalanced networks in MIoNT healthcare applications.

Machine Learning Supported Nano-Router Localization in WNSNs

Sensing data from the environment is a basic process for the nano-sensors on the network. This sensitive data need to be transmitted to the base station for data processing. In Wireless Nano-Sensor Networks (WNSNs), nano-routers undertake the task of gathering data from the nano-sensors and transmitting it to the nano-gateways. When the number of nano-routers is not enough on the network, the data need to be transmitted by multi-hop routing. Therefore, there should be more nano-routers placed on the network for efficient direct data transmission to avoid multi-hop routing problems such as high energy consumption and network traffic. In this paper, a machine learning-supported nano-router localization algorithm for WNSNs is proposed. The algorithm aims to predict the number of required nano-routers depending on the network size for the maximum node coverage in order to ensure direct data transmission by estimating the best virtual coordinates of these nano-routers. According to the results, the proposed algorithm successfully places required nano-routers to the best virtual coordinates on the network which increases the node coverage by up to 98.03% on average and provides high accuracy for efficient direct data transmission.

An energy balance cluster network framework based on Simultaneous Wireless Information and Power Transfer

Wireless NanoSensor Network (WNSN) is a brand-new type of sensor network with broad application prospects. In view of the limited energy of nano-nodes and unstable links in WNSNs, we propose an energy balance cluster network framework (EBCNF) based on Simultaneous Wireless Information and Power Transfer (SWIPT). The EBCNF framework extends the network lifetime of nano-nodes and uses a clustering algorithm called EBACC (an energy balance algorithm for intra-cluster and inter-cluster nodes) to make the energy consumption of nodes more uniform. Simulation shows that the EBCNF framework can make the network energy consumption more uniform, reduce the error rate of data transmission and the average network throughput, and can be used as an effective routing framework for WNSNs.

Red Deer Algorithm based nano-sensor node clustering for IoNT

Node connectivity is a crucial issue for collecting and transmitting the values of the medium at nano-scale in Wireless Nano-Sensor Networks (WNSNs). This provides the network to be online when the sensor nodes maintain connectivity among themselves. Therefore, efficient connectivity methods need to be developed for permanent connection on the network. The basic way to provide connectivity over the network is clustering-based solutions which build efficient routing paths between the nodes. On the other hand, meta-heuristics are prominent methods to be preferred in order to select special nodes as cluster heads. In this paper, a modern meta-heuristic method, the Red Deer Algorithm (RDA) based distributed nano-sensor node clustering algorithm, namely nanoRDA, is proposed in order to provide efficient communication between nano-sensor nodes by selecting cluster heads on WNSNs in Internet of Nano-Things (IoNT) applications. nanoRDA is compared with two different Genetic Algorithm (GA) setups. According to the results, nanoRDA covers all non-cluster head nodes up to 99.38% on average all over the nano-scale networks while selecting fewer cluster heads than GA-based solutions.

RETRACTED ARTICLE: Terahertz fading model for wireless nanosensor networks in advanced medical manufacturing technologies

RETRACTED ARTICLE: Terahertz fading model for wireless nanosensor networks in advanced medical manufacturing technologies

Extending lifetime of Wireless Nano-Sensor Networks: An energy efficient distributed routing algorithm for Internet of Nano-Things

Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the nano-devices in applications of different fields operating at the molecular level such as health, industry, agriculture, robotics and military. These distributed devices interconnect over the Wireless Nano-Sensor Networks (WNSNs) in nano-scale which have limited energy and capacity. Therefore, these devices need to use their energy efficiently when communicating with each other to ensure network continuity and maintain all processes of IoNT applications. In this paper, a novel energy-efficient distributed routing algorithm, namely DEEPNT, is proposed in order to extend the lifetime of WNSNs in IoNT applications. The communication backbone of WNSNs constructed by DEEPNT by selecting cluster head nodes can be used in all types of IoNT applications in nano-scale in order to provide continuous data flow in critical areas such as healthcare running in vivo. This novel energy-efficient distributed protocol is compared with the traditional flooding based method and with an energy aware routing algorithm. According to the results, DEEPNT prolongs the WNSNs average lifetime respectively up to 10.78 and 5.95 times compared to mentioned algorithms despite the larger network sizes in nano-scale.

Application of Wireless Nano Sensors Network and Nanotechnology in Precision Agriculture: Review

Due to a series of global issues in recent years, such as the food crisis, the impact of fertilizer on climate change, and improper use of irrigation that’s way precision agriculture is the best solution for alleviating this problem. One of the most important and interesting information technology is the wireless Nanosensor network with the help of Nanotechnology will boost crop productivity, maintain the fertility status of the soil, save the water with precise application of irrigation in the field and minimize the loss of excess fertilizer through the precise application. In this paper, we have surveyed the importance of sensor networks in precision agriculture and the importance of Nanosensors with the help of Nanotechnology for remote monitoring in the various application of the agriculture field.

Topological Optimization of Lung Wireless Nanosensor Network

The early detection and prevention of lung disease is always a difficult point in the medical field, but it is of great significance. Some biological signals of the lung contain abundant information, especially the disease signals with great value. With the development of sensing technology, these specific biological signals are enough to be detected by sensors. However, if the information is to be transmitted from lung sensors to medical institutions in the macroworld, a suitable sensor network should be proposed. At the same time, the structure of lung is complex, and the channel in human body is special, so the construction of network is subject to many constraints. In order to construct an in vivo wireless nanosensor network (WNSN) that can meet the requirements of delay and energy, the model of lung WNSN is constructed in this article. On this basis, the performance of in vivo WNSNs (iWNSNs) with different equalization methods and different topologies is compared. Finally, a low-delay energy-efficient (LDEE) lung WNSN topology model is proposed. In this model, the total network delay and energy consumption of iWNSNs are taken as optimization objectives, the terahertz channel environment of lung and the properties of nanonodes are taken as constraint variables, and the topology model with the best performance is solved by MATLAB. The model can meet the necessary conditions of lung signal transmission, and has the characteristics of low network delay, high throughput, and long network lifetime.

A State of Art Survey of Nano Technology: Implementation, Challenges, and Future Trends

Nanotechnology is a field of study that aims to make our lives easier, safer, and more environmentally friendly. With current upgrades and alterations to available networking and communication paradigms, incorporating Wireless Nano Sensor Networks (WNSN) with various products, sensors, and devices would introduce new network paradigms. The Internet of Nano Things is a term for this concept (IoNT), To achieve seamless interconnection between Nano networks and existing communication networks and the Internet, many topologies and communication paradigms must be developed while technological hurdles are addressed. The amount of data accessible limits how much research and decision-making can be done. This research visualizes a wide range of nanotechnology applications. The goal of this project was to show in more than way this research method may be used to information recommendation services. The routing protocol is critical in WNSN and IoNT because of the many nanoscale constraints. While ensuring the flow of data and information, this routing protocol must take into account the specific features of nanoscale communication.This research aims to provide insight into the WNSN (Wireless Nano Sensor Networks) and IoNT (The Internet of Nano Things) paradigms, as well as a detailed assessment of a large number of current routing protocols that are tailored to the characteristics and features of nano communication. Big data applications with their features and characteristics in general also use cloud computing. This paper explains different hands based on neural networks and implemented on FPGAs (which is Field-Programmable Gate Array) and other genetic algorithms and neural networks. Many more approaches and models compare.

A multi-hop routing protocol based on link state prediction for intra-body Wireless Nanosensor Networks

As a network that communicates human health information, iWNSNs (in-vivo Wireless Nanosensor Networks) must be able to detect and report back to human health in real time, and low delay and high reliability are required in iWNSNs. In view of the unstable link state in iWNSNs, a multi-hop routing protocol based on link state prediction called MRLSP is proposed. The protocol proposes a link state estimation based on Kalman filtering. In addition, an ultrasonic energy harvesting system is introduced to intermittently charge nanonodes. In the routing process, the protocol first ensures the forwarding direction of the data packet by limiting the range of the next hop node, and uses the historical state and current information of the link to estimate the link state. Finally, a fuzzy system is established using the link state, the distance and the node’s remaining energy. We use the fuzzy logic output as the criterion to select the next hop node to ensure that fewer hops complete the forwarding and successful transmission of the packet. The simulation results verify that MRLSP has advantages in end-to-end delay and data packet transmission success rate, and can maximize network performance while ensuring sufficient node energy.

Performance Analysis of Transmission Rate and Decoding Rate Using Minimum Energy Channel Codes for Nanoscale Wireless Communication

An energy efficient communication system is required for the improvement of nanoscale wireless communication. In this paper, we defined minimum energy coding scheme (MEC) to achieve energy efficiency in wireless nanosensor network. MEC maintains the desire code distance to provide reliability and better decoding probability, while requiring less energy to transmit bits of information. We proposed a relationship between transmission rate and decoding rate which is significant for minimum energy channel codes in nanoscale wireless communication. We investigated the performance evaluation of code length limited and energy limited transmission rates on the source cardinality which ensures that for any value of code distance, code length limited transmission rate will be decreased in regard to increasing the value of source cardinality and vice versa for energy limited transmission rate. We studied the optimum value of transmission rate and decoding rate which confirms that if the number of carriers is increased n times, then the optimum transmission and decoding rate would also be increased n times. We also studied the performance evaluation of code distance which is inversely propotional to transmission distance and correct decoding probability. Further, we examined the dependance of average energy per bit which is proportional to symbol duration and bandwidth. On the contrary, spectral efficiency is inversely proportional to symbol duration. We strongly believe that our proposed relationship between transmission rate and decoding rate accompanied by the performance evaluation of various parameters will improve the nanoscale wireless communication system.

NEW ADAPTIVE REBROADCASTING USING NEIGHBOUR LEARNING FOR WIRELESS NANOSENSOR NETWORKS

Wirelesse Nanosensor Networks (WNSNs) contain a large number of independent and mobile nanodevices assembled with nanotransceivers and nanoantennas to work in Terahertz frequency band (0.1-10THz). These nanodevices exploit the properties of modern nanomaterials to recognize new varieties of events at the nanoscale, such as the presence of harmful viruses or bacteria and the detection of low concentrations of chemical and harmful gas molecules. Communication between nanonodes can be established by using molecular or electromagnetic communication approaches. One of the major problems of wireless nanosensor networks is the limited resources of nanodevices (e.g., computation, memory and power). On the other hand, such limited capacity cannot simply ensure communication between nanonodes using the flooding mechanism, which affects network performance and increases resource utilization. This paper considers the electromagnetic-based wireless nanosensor networks, and proposes a New Adaptive Probabilistic Based Broadcast Using Neighborhood Information. Simulations have been conducted using Nanosim simulator in order to compare our new schemes with the fixed probabilistic based broadcast. The experiments show that the proposed approach gives good results in terms of Packet Delivery Ratio (PDR reached 95%.), the amount of energy consumed (significantly reduced) for all the categories of density. No startup setup is required: the nanonodes adjust by themselves the broadcasting probability based on neighborhood collected information.

ECIGC-MWSN: Energy capable information gathering in clustered secured CH based routing in MWSN

One of essential difficulties in Mobile Wireless Nano sensor Networks is energy proficiency. In most recent decade MWSNs have discovered its application in wide scope of uses delivering colossal measure of information. Energy effectiveness of MWSNs can be enhanced with clustering, if range of information being transmitted in system is decreased. In this paper energy capable information gathering plan for clustered nano sensor arrangement for mobile wireless nano sensor network is introduced. It lessens intra-cluster connection by permitting cluster nodes to send minute amount frames by exhaustive from nodes preferred by clusterhead. Proposed work can join together with any clustering technique utilize it with LEACH with end goal of reenactment. The outcomes acquired are considerable in stipulations with network truthfulness, duration and existence.Selection and peer-review under responsibility of International Conference on Nanoelectronics, Nanophotonics, Nanomaterials, Nanobioscience, and Nanotechnology (5 NANO 2020).

Performance evaluation of Wireless Nanosensor Networks under interference

Nanonetworks are enhancing the long awaited claims of nanotechnology in many fields of our society. In continuum, Wireless Nanosensor Network (WNSN) is a key enabler for intra-body surveillance which in turn guaranteed accurate targeted drug delivery systems. The purpose of this manuscript is to present a novel model for WNSN under interference limited scenario and thereby to analyze various important performance measures and their improvements. In the analysis Poisson Point Process (PPP) is considered to represent the spatial distribution of multiple nanosensors within the cluster, whereas α-stable process is considered to represent the aggregate power of interferers. However, in particular, this manuscript presents novel analytical expressions of Outage Probability (OP), Bit Error Rate (BER) and Average Capacity (AC) of WNSN in presence of interference. In addition, Selection Combining (SC) scheme is employed to mitigate the effect of impairments. Finally, effect of various parameters such as spatial density of nanosensors nodes(λ), SNR of interferers (γI), outage threshold (xth) and path loss exponent (v) is investigated. The results show that OP and BER increase with an increase in λ, or γI and vice versa. Whereas, AC increases with an increases in λ but it decreases with an increases in γI. Moreover, Simulated results show perfect agreement with the theoretical backgrounds.

Routing Protocols for Wireless Nanosensor Networks and Internet of Nano Things: A Comprehensive Survey

Nanotechnology is a multidisciplinary field that will make our life simpler and safer and mitigate our impact on the surrounding environment. With the recent advancements and transformations in the available networking and communications paradigms, embedding Wireless Nano Sensor Networks (WNSN) with various objects, sensors, and devices would add a new network paradigm. This paradigm is known as the Internet of Nano Things (IoNT). Seamless interconnectivity among nanonetworks with the available communication networks and the Internet requires developing new network architectures and new communication paradigms while addressing the various technical challenges. Routing protocol is one of the most essential requirements in WNSN and IoNT due to the different nanoscale constraints. This routing protocol must accommodate nanoscale communication's characteristics while guaranteeing the data and information transmission. This study aims to give insight into WNSN and IoNT paradigms and present a comprehensive review of a large number of existing routing protocols adapted to nano communication's characteristics and features.

A data dissemination scheme for a wireless nanosensor network towards IoNT

Nanotechnology has gained significant importance in many fields, especially biological, industrial, military, and environmental sectors. Rapid advancements in nanotechnology have led to the development of wireless nanosensor networks (WNSNs). Most researchers focus on addressing resource limitations constraints and ignore the dynamic channel state. Therefore, in this paper, we design a fine-grained, lightweight, and energy-efficient end-to-end data dissemination scheme for WNSN that takes into consideration the dynamic channel state problem and energy efficiency. Simulation results showed that the proposed scheme outperforms TEForward in terms of energy consumption and packet delivery ratio. The effect of employing multiple gateways is also investigated.