High Energy Nodes Research Articles

Relaxation effects in twisted bilayer molybdenum disulfide: structure, stability, and electronic properties

Manipulating the interlayer twist angle is a powerful tool to tailor the properties of layered two-dimensional crystals. The twist angle has a determinant impact on these systems’ atomistic structure and electronic properties. This includes the corrugation of individual layers, formation of stacking domains and other structural elements, and electronic structure changes due to the atomic reconstruction and superlattice effects. However, how these properties change with the twist angle, θ, is not yet well understood. Here, we monitor the change of twisted bilayer (tBL) MoS2 characteristics as a function of θ. We identify distinct structural regimes, each with particular structural and electronic properties. We employ a hierarchical approach ranging from a reactive force field through the density-functional-based tight-binding approach and density-functional theory. To obtain a comprehensive overview, we analyzed a large number of tBLs with twist angles in the range of . Some systems include up to half a million atoms, making structure optimization and electronic property calculation challenging. For , the structure is well-described by a moiré regime composed of two rigidly twisted monolayers. At small twist angles ( and ), a domain-soliton regime evolves, where the structure contains large triangular stacking domains, separated by a network of strain solitons and short-ranged high-energy nodes. The corrugation of the layers and the emerging superlattice of solitons and stacking domains affects the electronic structure. Emerging predominant characteristic features are Dirac cones at K and kagome bands. These features flatten for θ approaching 0∘ and 60∘. Our results show at which range of θ the characteristic features of the reconstruction, namely extended stacking domains, the soliton network, and superlattice, emerge and give rise to exciting electronics. We expect our findings also to be relevant for other tBL systems.

A trusted security approach to detect and isolate routing attacks in mobile ad hoc networks

BackgroundSecure routing is of utmost importance in protecting mobile devices from external threats. However, the dynamic characteristics of Mobile Ad hoc Networks (MANETs) pose significant challenges in achieving a secure routing path. ObjectivesThis paper aims to propose a Trust and Anonymous Model (TAM) for efficient and secure data routing in MANETs. The objective is to address the limitations of existing routing approaches and enhance the security of the network. MethodsThe TAM protocol is designed with a Two-Tier Security Mechanism (TTSM). In the first level of security, trustable nodes are selected based on their ability to process control messages. The recommended trust value of a node is determined by estimating the speed at which it processes control messages, with higher energy nodes being considered more trustable. In the second level of security, the original node identity is concealed, and data is transmitted through selected trusted nodes with duplicate identities generated using a factorial recursive function. This ensures secure transmission, as malicious observers are unable to identify participating nodes in the routing operation. ResultsThe proposed TAM model is evaluated and compared with state-of-the-art schemes such as A Multi-attribute-based Trusted Routing for Embedded devices (EMBTR) and a cognitive energy-efficient-based trusted model (CEMT). Experimental evaluation demonstrates that the TAM model achieves better performance in terms of energy consumption, delay, packet delivery rate, and false node detection rate, thereby improving network optimality. ConclusionThe Trust and Anonymous Model (TAM) with its Two-Tier Security Mechanism (TTSM) presents a promising approach for secure data routing in MANETs. By selecting trustable nodes and utilizing duplicate identities, the TAM model enhances network security while achieving improved performance compared to existing schemes. The findings of this study contribute to the advancement of secure routing techniques in MANETs and provide insights for future research in this domain.

Connectivity Analysis of WSN Nodes using Neighborhood Search Technique (WSNNST)

A new approach to wireless sensor network (WSN) communication through multi-hop routing is investigated in this work. The proposed approach utilizes search radius expansion in order to find highest energy nodes within a WSN network and preserves the energy of the lowest energy nodes. This approach which is built on trust in terms of providing good quality communication channels between a source node and a destination node considers energy as one parameter of trust that will enable strong, reliable communication channels and shorter routes to be used in a WSN. This approach enables efficient energy consumption during data communication, but with higher level energy consumption due to expanded search radius, which can be minimized using search time limit. The work also relates through mathematical equations, number of discovered routes, maximum hops, and search time to the considered search radius. The overall objective of this work is to enable faster and efficient channel communication between WSN nodes, through gradual cost effective search in neighborhoods. This is achieved by uncovering shorter and less number of routes within an acceptable time limits. The proposed and simulated approach presented in this work differ in terms of the gradual expansion of search and the equal increments in search radius compared to other used techniques. The presented work also adds a unique feature of allowing re-charging of low energy nodes using the already established routes connecting high energy nodes through the registration of weak nodes locations. A final general expression relates search radius to other WSN variables is also presented.

Game theory based node clustering for cognitive radio wireless sensor networks

Cognitive radio wireless sensor networks (CRWSN) is a promising technology for developing bandwidth constrained applications. Future Internet of Things (IoT) applications may extensively use CRWSN. CRWSN consists of cognitive radio enabled sensor nodes which are energy constrained, in general. Hierarchical cluster based approach for overall network management is suitable for network stability and scalability. Thus node clustering is an important problem in CRWSN setup. Objective of this work is to develop a suitable node clustering algorithm for CRWSN, in which nodes are expected to be mobile. A node clustering protocol for CRWSN has been proposed in this paper. The proposed clustering protocol is based on evolutionary game theory (EGT). Initial clusters are formed through a simple partitioning approach. Eventually, initial clusters are merged to form the final clusters. After forming the clusters by the resourceful sink node, the cluster head nodes for respective clusters are determined. The sink node runs the EGT based algorithm to identify the most capable node as the cluster head. The strength of this approach is that while identifying the cluster head node, various parameters such as residual energy level, geographic location, mobility, and the probability of primary user (PU) arrival are considered. The clusters and therefore, the cluster head nodes are distributed uniformly in the geographical area. The proposed clustering protocol has been compared with LEACH, RARE and the spectrum aware clustering algorithm. The simulation results show that the proposed clustering protocol outperforms all these similar node clustering protocols. On average, the proposed protocol outperforms the benchmarks protocols by 25% in terms of number of high energy nodes selected as cluster head, by 37% in terms of uniform geographical distribution of cluster head nodes, by 23% in terms of total energy consumed during the simulation time, and by 27% in terms of network lifetime. The future scope of the work has been outlined.

Algorithm for wireless sensor networks in ginseng field in precision agriculture.

In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng.

Cost-Effective Cluster-Based Energy Efficient Routing for Green Wireless Sensor Network

Background: The green Information and Communications Technologies (ICTs) have brought a revolution in uplifting the technology efficiently to facilitate human sector in the best possible way. Green Wireless Sensor Network (WSN) tactically focuses on improving the survival period of deployed nodes (as they have limited battery) in any target area. Objectives: To address this concern, the main objective is to improve the routing in WSN. The cluster- based routing helps in acquiring the same with the appropriate Cluster Head (CH) selection. The use of energy heterogeneous nodes that normally comprise of high energy nodes, puts a lot of financial burden on the users as they incur a huge cost, thus becoming a bottleneck for the growth of green WSN. Therefore , another objective of the study is to reduce this cost involved in the network. Method: A cost-effective routing protocol is proposed that introduces energy-efficient CH selection by incorporating parameters namely, node density, residual energy, the total energy of network and distance factor. Thus, the proposed protocol is termed as Cost-Effective Cluster-based Routing Protocol (CECRP) as it performs remarkably better with only two energy level nodes as compared to state-of-the-art protocols with three levels nodes. Results: It can be encapsulated from the simulation results that CECRP outperforms state-of-theprotocols on different performance metrics. Conclusion: Furthermore, it is comprehended from the simulation results that CECRP proves to be 33.33% more cost-effective as compared to the competent protocols, hence CECRP favors the green WSN.

Bivariate Regression Adaptive Wald’s Boost Energy Aware Routing for Wsn with IoT

WSN is a wireless network where the low powered devices known as sensor nodes which are deployed over the network to measure the environmental conditions. IoT is a model that connects WSN and the Internet through a medium depends on wireless Internet technology sensors. However, the large-scale acceptance of WSN for IoT is still facing the major challenges of routing. In order to improve the routing in WSN, an efficient technique called Bivariate Regressed Adaptive Wald’s Boost Energy Aware Routing (BRAWBEAR) is introduced. The main aim of BRAWBEAR technique is to improve the data delivery with minimum delay as well as routing overhead. Initially, the energy of the each sensor nodes is measured to improve the energy efficient routing in WSN. The Adaptive Wald’s Boost ensemble technique initially comprises the weak learners as a bivariate regression tree with the training samples as sensor nodes. The regression tree analyzes the node energy level with the threshold and categorizes the node into two classes such as higher energy and lesser energy. The Adaptive Wald’s Boost ensemble technique combines the weak learner results into make a strong one resulting increases the accurate sensor node classification with minimum error. After that, the route path discovery is carried out with the higher energy nodes and the sensor nodes with lesser energy are removed. The source node finds the neighboring energy efficient node by applying the time of arrival method. Then the route path is established from source to sink node via neighboring nodes. Followed by, the data packets are transmitted along the route path. Finally, the route maintenance is carried out when the link failure occurs by selecting the alternative energy efficient neighboring node to improve the data packet delivery with minimum time. The performance of the proposed BRAWBEAR technique is estimated using the metrics namely, energy consumption, packet delivery ratio, routing overhead, throughput and end to end delay. The comparative results discussion provides the improved performance in terms of minimum routing overhead and higher packet delivery as well as minimum energy consumption than the other well-known routing methods.

An optimization of distributed Voronoi-based collaboration for energy-efficient geographic routing in wireless sensor networks

In energy-constrained wireless sensor networks (WSNs), geographic routing (GR) also known as location-aware routing has been developed because it uses neighbourhood locality data as an alternative of overall topology information for routing. But, this protocol frequently suffers from the energy holes in the data transmission resulting in path failure. To avoid this problem, energy-aware dual-path GR (EDGR) protocol has been suggested to improve the routing path from energy holes. However, it is unable to heal the energy holes since the node mobility can generate new energy holes. Also, higher mobility distance can cause high energy consumption (EC) and node failure. Hence in this article, an energy-efficient distributed collaboration mechanism is proposed with EDGR for $$k$$ -coverage energy holes detection and healing in WSN that minimizes the delivery delay (DD). In this protocol, the distributed Voronoi-based collaboration (DVOC) method is applied in which the nodes can cooperate in energy holes detection and recovery. The nodes are enabled to monitor each other node’s critical locations around themselves by constructing the local Voronoi diagrams (LVDs). Moreover, an optimized DVOC (ODVOC) is proposed with EDGR in which intelligent water drop (IWD) algorithm is used to find the globally optimized routes to minimize the DD. Finally, the simulation outcomes demonstrate the ODVOC-EDGR accomplishes higher effectiveness than the EDGR and DVOC-EDGR in terms of different performance metrics.

DDC protocol to protract network lifetime of wireless sensor networks

Efficient energy consumption of sensor nodes is the prime design issue for wireless sensor networks because the energy of sensor nodes is the scarcest resource. Clustering has been examined as an energy-efficient approach for wireless sensor networks. Performance of a clustering method is highly dependent upon the way it selects cluster heads. Most of the existing clustering methods, for selecting cluster heads, depend upon a random number generated by each sensor nodes. Dependency of different methods on this random number may result in the selection of low energy nodes as cluster head over high energy nodes which makes network load unbalanced and affects network lifetime. In this paper, a Distributed Dynamic Clustering (DDC) protocol has been proposed that capitalizes the node energy heterogeneity to recondition the random number generated by nodes in such a manner that the reconditioned number of high remaining energy nodes is small while the number of low remaining energy node is large, consequently the nodes having high remaining-energy get selected as cluster heads. Performance of the proposed DDC protocol has been compared to important existing clustering methods namely Low Energy Adaptive Cluster Hierarchy, Stable Election Protocol, and Distributed Energy-Efficient Clustering for both homogeneous and heterogeneous wireless sensor networks. The analysis of simulation results shows that the network lifetime is longer and throughput is higher in the case of DDC protocol in comparison of other methods.

Energy Efficient Design Techniques in Next-Generation Wireless Communication Networks: Emerging Trends and Future Directions

The projected rise in wireless communication traffic has necessitated the advancement of energy-efficient (EE) techniques for the design of wireless communication systems, given the high operating costs of conventional wireless cellular networks, and the scarcity of energy resources in low-power applications. The objective of this paper is to examine the paradigm shifts in EE approaches in recent times by reviewing traditional approaches to EE, analyzing recent trends, and identifying future challenges and opportunities. Considering the current energy concerns, nodes in emerging wireless networks range from limited-energy nodes (LENs) to high-energy nodes (HENs) with entirely different constraints in either case. In view of these extremes, this paper examines the principles behind energy-efficient wireless communication network design. We then present a broad taxonomy that tracks the areas of impact of these techniques in the network. We specifically discuss the preponderance of prediction-based energy-efficient techniques and their limits, and then discuss the trends in renewable energy supply systems for future networks. Finally, we recommend more context-specific energy-efficient research efforts and cross-vendor collaborations to push the frontiers of energy efficiency in the design of wireless communication networks.

A three-tier scheme for sybil attack detection in heterogeneous IWSN

Industrial wireless sensor network is a new application of wireless sensor network in the field of industry in recent years. However, IWSN may be subject to different attacks and security risks, among which the Sybil attack is the most harmful type of base attack. According to the characteristics of wireless sensor networks in industrial environment, a new three-tier detection scheme is proposed. In the first-level, all common nodes and Sybil nodes were detected by RSSI-based quadratic difference method. In the second layer, the residual energy-based method is used to continue the detection of the nodes that have been detected in the first-level. The detection of first and second-level high-energy nodes is finally completed by the base station. The simulation results show that our proposed scheme significantly improves network lifetime and effectively improve the detection rate of Sybil nodes.

A novel energy-efficient framework (NEEF) for the wireless body sensor network

Increasing the availability of wireless body sensor network is obligatory to monitor the patient inside and outside the hospital environment. Major amount of energy dissipated in the sensor node is through the enormous switching transitions in the transceiving unit, and hence, it becomes essential to minimize the switching transitions to prolong the lifetime of the network. Also, the packet holding cost in terms of energy influences the network lifetime to a greater extent. The novel energy-efficient framework (NEEF) approach provides a solution for lifetime problem and availability problem in the network. The subject is modeled as finite state machine with normal, abnormal and above normal states. The packet in the cluster head is transmitted once it reaches the threshold level. The critical packet is hoped through high energy node to ensure safe data communication. The framework is evaluated with Fail Safe Fault Tolerant algorithm. The lifetime enhancement is achieved through reducing the switching loss of the transceivers circuit. The NEEF provides extended lifetime and throughput and the framework also promotes improved half-life period. The first dead node in case of NEEF framework is high. The NEEF ensures high availability and extended lifetime.

Energy Efficient Cross Layer Based Multi-Hop Clustered Routing Protocol For Wireless Sensor Networks

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.

An efficient elite group-based routing protocol for wireless sensor network

ABSTRACT In recent days, due to the wide verities of applications of Wireless Sensor Networks, it gets recognition from research communities. As the sensor nodes are operated through limited battery capacity, how to utilise the battery power or energy in an optimum way is a major concern. In this paper, we have addressed the energy issue of wireless sensor networks. We have developed an energy-efficient routing protocol. This paper proposes the Novel Elite group concept where the cluster-head selection process is restricted to only a few high-energy nodes rather than all nodes in the network, which substantially reduces the number of cluster-head selection overhead in every iteration, decreases the energy consumption and increases network lifetime. Our method is compared with three well-known routing protocols, i.e. EECRP (Energy Efficient Centroid-Based Routing Protocol) protocol, NCBR (New Cooperative Balancing Routing Protocol) and Mod-LEACH (Modified low-Energy Adaptive Clustering Hierarchy Protocol). We have conducted a simulation in NS-2 simulator. We have computed various network quality parameters like Throughput, transmission delay, analysis of the number of dead nodes (reciprocal of alive nodes) and energy dissipation with respect to the number of simulation rounds. The simulation results show that our proposed methodology outperforms the rest of the protocol.

New Method to Improve Energy Savings in Wireless Sensor Networks by Using SOM Neural Network

A new routing protocol for wireless sensor network is presented using energy clustering based on self-organizing map (ECSOM). In the process of neural network clustering, a self-organizing plan is used. Network input, three dimensions of energy and spatial coordinates of each node are denoted by X, Y and E, respectively. Connectional weights are the coordinates X, Y and E, which correspond to every unit of map, i.e., energetic nodes. The self-organizing neural network forms high-energy clusters based on the nodes in the network right after the training and reorganization of weights. In fact, each cluster is a combination of a high-energy node and the closest low energy nodes. Therefore, all clusters have almost the same energy level.

Energy Efficient Trust Node Based Routing Protocol (EETRP) to Maximize the Lifetime of Wireless Sensor Networks in Plateaus

Wireless Sensor Networks (WSNs) can extant the individual profits and suppleness with regard to low-power and economical quick deployment for numerous applications. WSNs are widely utilized in medical health care, environmental monitoring, emergencies and remote control areas. Introducing of mobile nodes in clusters is a traditional approach, to assemble the data from sensor nodes and forward to the Base station. Energy efficiency and lifetime improvements are key research areas from past few decades. In this research, to solve the energy limitation to upsurge the network lifetime, Energy efficient trust node based routing protocol is proposed. An experimental validation of framework is focused on Packet Delivery Ratio, network lifetime, throughput, energy consumption and network loss among all other challenges. This protocol assigns some high energy nodes as trusted nodes, and it decides the mobility of data collector. The energy of mobile nodes, and sensor nodes can save up to a great extent by collecting data from trusted nodes based on their trustworthiness and energy efficiency. The simulation outcome of our evaluation shows an improvement in all these parameters than existing clustering and Routing algorithms.

Self Adaptable Deployment for Heterogeneous Wireless Sensor Network

Wireless Sensor Networks (WSN) is becoming a crucial component of most of the fields of engineering. Heterogeneous WSN (HWSN) is characterized by wireless sensor nodes having link (communication), computation or energy heterogeneity for a specific application. WSN applications are constrained by the availability of power hence; conserving energy in a sensor network becomes a major challenge. Literature survey shows that node deployments can have good impact on energy conservation. Works show that self-adaptable nodes can significantly save energy as compared to other types of deployment. This work uses the concept of self-adaptation of nodes to conserve energy in a HWSN. A deployment strategy driven by some dynamic decision making capability can boost the overall performance of a WSN. The work presents an analysis of three types of deployments: like keeping all nodes fixed, all node moving and high energy nodes moving with respect to throughput, delay and energy consumption. Experimental results show that self-adaptable dynamic deployment gives 10% better throughput and 6% better energy conservation than static deployment strategies.

Physical-traffic attentive vigorous routing (P-TAVR) and hot-spot detection to reduce the bottleneck in WSN

Minimizing the duration of data transmission is one of the major challenges in the wireless sensor communication. The sensor nodes in the networks take certain duration for observing the nearby sensor devices. Prominent factors such as broadcast storms, low bandwidth, multicasting, artificial congestion, etc can cause the bottleneck, results in data loss. In order to reduce the bottleneck in the sensor networks, physical traffic attentive vigorous routing protocol (P-TAVR) is proposed. This protocol will reduce the bottleneck effect by detecting the hot-spots thus reducing the network traffic. The proposed method is presented with three different phases such as Run-up, Set-up, Routing and detection phases. With the use of physical knowledge in this protocol, the location as well as the energy of every other sensor node is known by all the sensor nodes in the stream. In addition, an efficient modified routing algorithm is presented to select the cluster head nearer to the sink next hop. So that, in case of the bottleneck, the nodes are capable of determining the best possible routes with higher energy nodes for data transmission. Since the protocols utilized by the WSNs are application oriented; three classes such as data-centric, hierarchical and location-based classes are investigated. The simulation tool used here is Network Simulator 2 and the comparison has been made with AODV, MintRoute and TADR. The parameters such as End to End Delay, Throughput, Energy Consumption and Packet delivery ratio have been investigated for two cases such as increasing simulation time and increasing density. The results show that P-TAVR provides higher efficiency and throughput among the existing methods.

Balanced and energy‐efficient multi‐hop techniques for routing in wireless sensor networks

In Wireless Sensor Networks, the power resources of the nodes are significantly restricted. Hence, a special treatment for their available energy is deeply required. In long distance transmission, Multi-Hop (MH) techniques are preferred. Although MH minimizes the amount of energy cost consumed by each node along the path but finding the optimal routing path between nodes is still very interesting issues. This paper proposes a Balanced and Energy Efficient MH (BEEMH) algorithm that is developed based on Dijkstra algorithm. It gives great interest to the residual energy of nodes; hence higher energy nodes are exclusively elected to work as relays. Moreover, the total energy consumption at both TX and RX has been merged to model the weight of links between nodes. Finally, Dijkstra algorithm is employed to efficiently search for the minimum cost path. Furthermore, two proposed MH protocols are introduced. Both are mainly based on the BEEMH algorithm. MATLAB simulator has been used to evaluate BEEMH in comparison with other conventional algorithms such as; minimum transmission energy (MTE), energy saving oriented least-hop routing algorithm (ESLHA), and energy saving-oriented routing algorithm based on Dijkstra (ESRAD) under various scenarios of network models. Then the performance of our proposed protocols is compared with the related MH protocols.

Data Collection Strategy for Magnetic Induction Based Monitoring in Underwater Sensor Networks

Underwater wireless sensor networks (UWSNs) based on magnetic induction (MI) have been recently proposed as a promising candidate for underwater networking due to its benefits, such as small transmission delay, low vulnerability to environment changes, multipath fading negligibility, and high bandwidth. Most of the UWSN applications are location dependent and, thus, localization plays an important functionality for obtaining sensor positions. In this paper, we first study an MI-based monitoring network in shallow sea, then focus on how to design an optimal node deployment strategy and a clustering algorithm to prolong network lifetime for a 3D-UWSN by reducing the network energy consumption. Using the Voronoi diagram, we propose a high-energy node priority clustering algorithm, in which a cluster head would be selected according to the remaining energy of sensor nodes and the geometry distance among them. Moreover, in order to improve the efficiency of data collection, we use the ant colony optimization to find the shortest path for autonomous underwater vehicle. The simulation results show that the proposed approach outperforms other conventional protocols in some certain scenarios.