Residual Energy Of Nodes Research Articles

Coverage Control for Underwater Sensor Networks Based on Residual Energy燩robability

Underwater sensor networks have important application value in the fields of water environment data collection, marine environment monitoring and so on. It has some characteristics such as low available bandwidth, large propagation delays and limited energy, which bring new challenges to the current researches. The research on coverage control of underwater sensor networks is the basis of other related researches. A good sensor node coverage control method can effectively improve the quality of water environment monitoring. Aiming at the problem of high dynamics and uncertainty of monitoring targets, the random events level are divided into serious events and general events. The sensors are set to sense different levels of events and make different responses. Then, an event-driven optimization algorithm for determining sensor target location based on self-organization map is proposed. Aiming at the problem of limited energy of underwater sensor nodes, considering the moving distance, coverage redundancy and residual energy of sensor nodes, an underwater sensor movement control algorithm based on residual energy probability is proposed. The simulation results show that compared with the simple movement algorithm, the proposed algorithm can effectively improve the coverage and life cycle of the sensor networks, and realize real-time monitoring of the water environment.

Mobility Induced Multi-Hop LEACH Protocol in Heterogeneous Mobile Network

Heterogeneous mobile networks are a vital cue for Internet of Things (IoT) networks and their applications. Therefore, an optimal routing protocol is essential for the heterogeneous network to realize energy efficiency and robustness. However, designing an optimal routing protocol is more complex due to uneven energy depletion and dynamic event generation. The complexity further increases with the node mobility. In this context, the multi-hop routing approach with a controlled mobility pattern provides an energy efficient network by improving memory and storage utilization. This work proposes a new energy-efficient model for heterogeneous network, considering the effect of mobility and residual energy of nodes for cluster head selection in multi-hop-LEACH (M-LEACH). The performance of the proposed mobility induced multi-hop LEACH (Mob M-LEACH) protocol is further compared with existing baseline methods. The robustness of the network is evaluated considering static and dynamic environments for multiple network technologies. The simulation results show that the proposed method reduces network latency by 25% and enhances the throughput by 75%, improving energy consumption and network lifetime when compared with the state-of-art methods.

Automatic Repair Method for D2D Communication Routing Buffer Overflow Vulnerability in Cellular Network

Repairing D2D communication routing buffer overflow in a cellular network is of great significance in improving communication quality and security. Due to the increase of user usage, the communication data are easy to exceed the boundary of the buffer, resulting in the reduction of covered data information. The traditional repair methods mainly repair through the characteristics of covered data information, ignoring the impact of network topology information transmission delay and packet loss during calculation, resulting in the problem of low communication security. A cellular network routing buffer overflow repair algorithm based on the homomorphic analysis of node residual energy is proposed; the cellular network D2D communication routing protocol is designed; the cellular network D2D communication protocol path index is determined; then, the cellular network D2D communication routing protocol is designed by analyzing node residual energy; and the cellular network D2D communication network routing optimization method based on AHP is designed. Big constructs the energy model of cellular network D2D communication network, solves and sets the routing optimization objective function, realizes the control of network routing, and repairs the buffer overflow. The experiment results show that the improved method can effectively reduce the packet loss rate of communication data, improve the anti-interference ability of the system, and ensure the security of network communication.

Research on Clustering Routing Protocol Based on Improved PSO in FANET

In disaster response, 2D wireless sensor networks fail to be deployed since a large number of sensors cannot be placed in harsh ground environments. In this case, as the best air carrier for sensors, unmanned aerial vehicles (UAVs) are always used to construct a 3D flying ad hoc network (FANET) to realize emergency communication. In FANET, however, node localization and data transmission are great challenges due to the increase in network dimensions and the high mobility of UAVs. In this paper, a novel FANET clustering routing protocol based on nodes location is proposed. Firstly, an improved particle swarm optimization (IPSO) algorithm is designed by fusing variable neighborhood search, and IPSO is used to improve the locating precision of UAVs. Furthermore, the base station (BS) clusters UAVs evenly according to nodes location, and the cluster head is determined by weighting the intra-cluster distance and residual energy of nodes. Finally, the optimal next-hop routing is selected by IPSO according to the link reliability and the distance between nodes and the BS to ensure data are transmitted to the BS timely and reliable. The simulation results show that routing protocol based on IPSO realize more efficient performance compared with the existing schemes in terms of positioning indicators, energy consumption, delay, and clustering lifetime.

Artificial Intelligence Based Sensor Network Congestion Fuzzy Control Algorithm

The topology control of sensor sensor network was studied based on fuzzy control algorithm. Aiming at the dynamic changes of the topology of large-scale and heterogeneous artificial intelligence sensor networks and the incomplete information between nodes, a smart network-based congestion control algorithm for sensor networks was proposed and the performance of fuzzy control algorithms was analyzed. Based on this, a fuzzy control algorithm was designed. The algorithm fully considered the residual energy of nodes and the distribution of nodes in the network. Therefore, the reasonable election of the cluster head can be realized through the game between nodes, which effectively avoided energy holes, made the network energy consumption more uniform, prolonged the network life cycle, and optimized the network topology.

Improve the QoS using multi-path routing protocol for Wireless Multimedia Sensor Network

The diversity of quality-of-service (QoS) necessities of Internet applications prompts several QoS routing techniques which receive different QoS metrics into deliberation. Conversely, merely adjusting existent multi-path routing techniques to maintain several QoS metrics, cannot assurance correctness. To solve this problem, we essentially analyze the Improve the Qos Using Multipath Routing Protocol (IQMRP) for Wireless Multimedia Sensor Network (WMSN) is proposed. Generally, wireless transactions are prone to link losers owing to signal intrusion that result in communication failures as well as packet drop. Thus, concurrent routing beside multi-path will considerably enhance the capability to handle these failures, significantly gaining wireless multimedia application. The multi-path communication assists to offer a great bandwidth necessary through the multimedia transaction among two nodes. Even while a single route would be capable of offering connectivity, hence, the multi-path transmission also serves to balance traffic load that can extend the network lifespan. In this approach, Ant Colony Optimization (ACO) technique to chooses the multi-path using route preference possibility. This route preference possibility is measured based on node residual energy, bandwidth as well as next-hop accessibility. Next route load is equated through an indicator to allocate the data traffic evenly on the connections from sender to recipient. Simulation results illustrate that diminishes both the average delay as well as route load function in the network. • We essentially analyze the Improve the Qos Using Multipath Routing Protocol (IQMRP) for Wireless Multimedia Sensor Network (WMSN) is proposed. • Even while a single route would be capable of offering connectivity, hence, the multi-path transmission also serves to balance traffic load that can extend the network lifespan. In this approach, Ant Colony Optimization (ACO) technique to chooses the multi-path using route preference possibility. • The load on the paths can be equated through determining an indicator via every node to disseminate the data load uniformly from sender to recipient.

Routing failure prediction and repairing for AUV-assisted underwater acoustic sensor networks in uncertain ocean environments

Underwater acoustic sensor networks (UASNs) provide temporary links, which is of great significance when it comes to dealing with abnormal situations or emergencies in Internet of underwater things (IoUT). However, UASNs are susceptible to changes and uncertainties in network topology, channel conditions, etc., which can easily lead to frequent link interruptions. In this paper, we introduce a link failure prediction mechanism and an autonomous underwater vehicle (AUV)-assisted routing holes repairing mechanism for routing design of UASNs in uncertain ocean environments, to save system energy consumption and improve network connectivity. The proposed link failure prediction mechanism takes into account residual energy of sensor nodes, node drifting information, and uncertain ocean ambient noise. When the energy of multiple sensor nodes is exhausted, the particle swarm optimization algorithm (PSO) is adopted to calculate the optimal repair location, and an AUV is used for fixed point repairing. The proposed method can effectively reduce the energy consumption of sensor nodes, increase the packet delivery ratio, and extend the life of entire network of UASNs.

OF-FZ: An Optimized Objective Function for the Ipv6 Routing Protocol for LLNs

Internet of Things (IoT) has seen a lot of traction over the last few years and is expected to play a major role in controlling devices and communication. IoT network involves sensors with constrained memory, limited processing and power capabilities. The process of network formation largely decides the Quality of service in these networks. IPv6 Routing Protocol for LLNs (RPL) is specially designed by the IETF ROLL working group to cater to routing requirements in such networks. In RPL, an Objective function specifies a set of metrics or constraints which can be used as criteria for best parent and path selection, ensuring a faster route to the destination. In our work, we propose a novel objective function OF-FZ, which uses four metrics to make routing decisions. Fuzzy Logic is used to combine the metrics hop count (HC), ETX, delay and node residual energy (RE) to obtain a single decision metric termed as Quality Assurance (QA) score. During routing, a neighbor node having the highest QA score is chosen as the best parent. The proposed Objective Function leads to significant savings in energy consumption (EC) (9% lower), Packet Delivery Ratio (PDR) (3% higher), End-to-end Delay (8% lower) as compared to existing OFs. Controlling advertisement messages circulating in the network leads to a significant reduction in control overhead to the tune of 45%. Performance evaluation and deep dive of OF-FZ is done in three configurations: network scalability, increasing packet transmission rates and multi-sink scenarios using Contiki OS and COOJA network simulator.

Research on Cluster Optimization Method of Node Clustering for PEGASIS Protocol

Chain-structured routing protocol PEGASIS can reduce redundant data and energy consumption in wireless sensor network, but topology adjustment will bring a lot of expense. The distributed and uneven nodes lead to a larger gap between the energy consumption and the larger delay distance of the nodes. The algorithm of the protocol leads to the formation of long chains. In order to improve the survival time and connectivity of WSN and increase the number of nodes in the network, we propose an improved node clustering cluster scheme, taking into account the residual energy of nodes. The simulation results show that the improved protocol has better performance than PEGASIS in balancing energy consumption and prolonging the network life cycle.

Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol

A Flying Ad-hoc network constitutes many sensor nodes with limited processing speed and storage capacity as they institute a minor battery-driven device with a limited quantity of energy. One of the primary roles of the sensor node is to store and transmit the collected information to the base station (BS). Thus, the life span of the network is the main criterion for the efficient design of the FANETS Network, as sensor nodes always have limited resources. In this paper, we present a methodology of an energy-efficient clustering algorithm for collecting and transmitting data based on the Optimized Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The selection of CH is grounded on the new optimized threshold function. In contrast, LEACH is a hierarchical routing protocol that randomly selects cluster head nodes in a loop and results in an increased cluster headcount, but also causes more rapid power consumption. Thus, we have to circumvent these limitations by improving the LEACH Protocol. Our proposed algorithm diminishes the energy usage for data transmission in the routing protocol, and the network’s lifetime is enhanced as it also maximizes the residual energy of nodes. The experimental results performed on MATLAB yield better performance than the existing LEACH and Centralized Low-Energy Adaptive Clustering Hierarchy Protocol in terms of energy efficiency per unit node and the packet delivery ratio with less energy utilization. In addition, the First Node Death (FND) is also meliorated when compared to the LEACH and LEACH-C protocols.

LBR‐GWO: Layered based routing approach using grey wolf optimization algorithm in wireless sensor networks

SummaryThe sensors deployed inside a wireless sensor network (WSN) have limited energy sources, significantly impacting the network throughput. This article's research objective is to increase network lifetime by developing an energy‐efficient layered‐based routing algorithm for WSNs using the grey wolf optimization (LBR‐GWO) algorithm. In this, the grey wolf's leadership hierarchy has followed, which improves the network's energy capability. The entire region of the deployed nodes divides into four layers. In these nodes, layer one is chosen as cluster heads. If more than two nodes are present in layer one, then the cluster head is selected based on the game theory model; otherwise, the decision is made based on the node's residual energy. While the existing algorithm has several complex control parameter points, the current algorithm has fewer complex parameters. Therefore, in comparison to other algorithms, this algorithm is easy to apply in cluster‐based sensor networks. Simulation findings prove the LBR‐GWO algorithm supremacy for balancing energy consumption across the nodes and improving the network's lifetime compared to the LEACH, HEED, and PSO protocols.

Internet of Things Based Stable Increased-throughput Multi-hop Protocol for Link Efficiency (IoT-SIMPLE) For Health Monitoring Using Wireless Body Area Networks

Aims: This study aimed to propose a routing protocol for IoT-based WBANs that is reliable, power-efficient, and has a high throughput. Background: A variety of services and applications that use wireless connections such as LTE, 3G, Wi-Fi, Bluetooth, and ZigBee communication technologies have become popular in daily life as a result of the rapid development of network hardware technology. Remote medical monitoring and care is one such service. Governments have developed new policies in response to the healthcare needs of aging populations. Their goal is to create a comprehensive medical network based on new wireless technologies like sensor networks and cloud computing. Their purpose is to take the medical industry and the Internet of Things (IoT) to the next level of development. Objective: The goal of our proposed study is to improve the network nodes' ability to stay alive for a longer period of time and to maintain stability. A longer stability period contributes to high packet delivery of the node to the sink that enhances the efficiency of the WBAN network. Methods: The Wireless Body Area Network (WBAN) Internet of Things (IoT) for healthcare applications has attracted attention from various fields of study in the last few years. In this paper, we propose a routing protocol for IoT-based WBANs that is reliable, power-efficient and has a high throughput. To achieve low energy consumption and a longer network lifetime, we used a multi-hop topology. To choose a parent node or forwarder, we propose a cost function that selects a parent node with the highest residual energy and the shortest distance to sink. The residual energy parameter balances energy consumption among sensor nodes, while the distance parameter ensures packet delivery to the sink. Our key goal is to increase WBAN’s total network by raising cumulative energy usage. The residual energy parameter governs the usage of energy by the sensor nodes, while the distance parameter ensures that the packet is effectively transmitted to the sink. Result: Simulation results demonstrate that our proposed protocol is energy efficient and maximizes network stability for longer periods. Conclusion: Real-time health and activity recognition with wearable sensors is a prerequisite for assistive paradigms. In this paper, we suggest a method for routing data to WBANs. The proposed scheme employs a cost function to determine the best route to the sink. The residual energy of nodes and their distance from the sink is used to calculate the cost function. Nodes with a lower cost function value are selected as the parent node. Other nodes are children nodes and send their data to the parent node. The proposed routing scheme improves network stability time and packet delivery to sink, according to our simulation results. Path loss is also investigated in this protocol and will be considered in future work.

A reliable multipath routing protocol based on link quality and stability for MANETs in urban areas

A mobile ad hoc network (MANET) is a set of mobile and self-organizing nodes that cooperate to create dynamic network architecture to establish communications. Its characteristics present critical challenges: limited residual energy of nodes and transmission range, wireless links sensitivity to environmental effects, and the mobility aspect, which leads to frequent link failure and rapid changes in the network topology. In this paper, we propose a new multipath routing protocol RMQS-ua (Reliable Multipath Routing Protocol based on Link Quality and Stability in Urban Areas). Our objective is to select the path that has better link quality and more stable links to guarantee reliable data transmission. We consider a combination of signal to noise ratio SNR and an enhanced packet reception ratio PRR to evaluate link quality, and the exponential moving average (EMA) to estimate the link stability. RMQS-ua is designed for an urban area that includes shadowing effect and background noise which deteriorates the link quality. Simulation results show that RMQS-ua improves network performance, and provides more reliability compared to some recent existing protocols.

A proficient data gathering technique for unmanned aerial vehicle‐enabled heterogeneous wireless sensor networks

SummaryUnmanned aerial vehicle (UAV)‐enabled wireless sensor networks (WSNs) have evolved as the significant paradigms to communicate the information among the devices in today's scenario instantly. These technologies support for developing smart crop spraying, smart infrastructure, aerial photography and videography, emergency services, etc. in providing smart solutions. Therefore, there is a dire need to develop an energy‐efficient solution for data gathering through UAVs. In this paper, an optimum weighted probability function is proposed by considering residual node energy, node spacing, and average energy of networks. This function helps in optimizing the clustering process for three‐tier heterogeneity by minimizing the energy of the proposed network. The proposed methods achieve 29.45% and 52.48% increment in the network lifespan as compared to the existing algorithm. The reason for such a gigantic enhancement in the network lifespan is the selection of the highest capable node as a cluster head using the proposed function.

An Improved D-SMART Algorithm for Wireless Sensor Networks

In this paper, a secure and low energy dynamic slicing algorithm, namely, Improved D-SMART (IM-D-SMART) based on the Data Aggregation Protocol on Slice Mix Aggregate (D-SMART) is proposed to improve the security and confidentiality of wireless sensor networks and reduce the energy consumption of nodes in data collection and transmission in wireless sensor networks. According to the importance of data, the residual energy of nodes and the relative density of nodes, the data are dynamically partitioned to improve the D-SMART algorithm. Simultaneously, sending negative number splicing is used to compensate for the loss caused by the collision of data transmission between nodes. The simulation results show that IM-D-SMART outperforms D-SMART in terms of computation, privacy and communication cost.

A mobile sink–integrated framework for the collection of farmland wireless sensor network information based on a virtual potential field

To overcome the limitations of traditional data collection methods in large-scale farmland wireless sensor network, in this study, we introduce a mobile sink and propose a virtual potential field-based strategy for mobile sink path planning. Virtual potential field-based strategy constructs a virtual field based on the residual energy, data generation rate, location information and cache urgency of nodes in the monitoring area. The stronger the virtual field, the more attractive it will be to mobile sink, which consequently affects the mobile path of sink node. Rendezvous points are selected in accordance with the maximum-farthest criterion, and the shortest path connecting all rendezvous points is taken as the mobile path of sink. Furthermore, the monitoring nodes employ the distance probability transmission strategy to have the transmission moment selected and the energy consumption optimized with reference to the path control information sent by the sink. The virtual potential fields and the rendezvous points are recalculated periodically according to the dynamic changes of both the node residual energy and the real-time cache. The simulation results showed that excellent transmission efficiency and network lifetime, and the combination of virtual potential field-based strategy and distance probability transmission strategy can have the fairness and real time of nodes guaranteed, thus it may meet the needs of large-scale farmland data collection.

A Minimum Spanning Tree based Clustering Algorithm for Cloud based Large Scale Sensor Networks

Wireless sensor networks (WSNs) can be composed of huge numbers of nodes collecting data from the environment. WSNs are crucial communication layer technologies of Internet of Things. The obtained data by the WSNs can grow exponentially, hence utilizing big data analysis techniques and cloud computing technologies are of utmost importance. WSNs can be used in various applications such as habitat monitoring, military surveillance, smart agriculture, miner safety and healthcare applications. Sensor nodes are generally battery-powered, so conserving the residual energy of nodes is very important to prolong the lifetime of the applications. WSNs do not own a fixed infrastructure, hence messages of the applications transmitted in an ad hoc manner to the sink node. Since the transmission range of sensor nodes are limited, multi-hop communication is used. Clustering is a very important method for supporting multi-hop routing in WSNs. Data aggregation, time synchronization and load balancing are some of the well-known operations that benefit from clustering. Selecting efficient communication paths and distribution of nodes evenly to partitions in clustering operation lead to boost the network lifetime. In this paper, we propose a minimum spanning tree based clustering and backbone formation algorithm (MICUB) for WSNs. The proposed algorithm inputs node coordinates, transmission range, sensing area dimensions and partition numbers and outputs clustering and backbone information. MICUB algorithm first forms a minimum spanning tree backbone and divides the networking area into equal partitions where each partition is a cluster. In this manner, efficient links are selected for backbone formation and the clusters are constructed evenly. The intra-cluster links are constructed by again executing a minimum spanning tree algorithm inside the clusters. We measure the coefficient of variations of the proposed MICUB algorithm and its counterparts to obtain the clustering quality. These results show us that our proposed algorithm performs very well against node counts and degrees.

Triangular Fuzzified Support Vector Regression Based Multivariate Rocchio Robust Boost Classification for Traffic and Congestion Aware Data Delivery in WSN

Wireless sensor network (WSN) is a huge set of sensor nodes distributed geographically with limited power supply. These nodes are used to sense environmental changes, gather information and send the collected data to a remote destination for data analysis and decision making. During continuous data transmission, the network traffic causes congestion. Congestion in WSN is a major cause for packet loss and it degrades the network performance. In order to improve the congestion-aware routing, a novel technique called as the Triangular Fuzzified Support Vector Regression Based Multivariate Rocchio Robust Boost Classification (TFSVR-MRRBC) technique is introduced. The proposed TFSVR-MRRBC consists of two processes such as route path identification and congestion aware data delivery. Initially, route paths are constructed by estimating node residual energy. After that, Support Vector Regression is applied to analyze the energy using the fuzzy Triangular membership function. Thus, energy-efficient nodes construct the multiple paths between sources and sink node through control message distributions namely route request with route reply is identified. Then the Multivariate Rocchio adaptive robust boost technique is applied for congestion aware data delivery based on the buffer space and bandwidth capacity. The route path with low buffer space and higher bandwidth capacity is selected as the best route among the multiple paths. Finally, Delay and packet loss is reduced by achieving congestion-aware data delivery. The simulation is achieved by various performance factors namely, energy consumption, packet delivery ratio, packet loss rate, and end-to-end delay with versus to amount of data packets and sensor nodes. Experimental results of proposed TFSVR-MRRBC technique improves data packet delivery and energy consumption is minimized, packet loss rate, delay than the conventional routing techniques.

Energy-Efficient Routing Protocol for Network Life Enhancement in Wireless Sensor Networks

Background: The Wireless Sensor Network (WSN) is composed of autonomous nodes consist of sensors to collect the status of the surrounding environment. These nodes are equipped with limited batteries. One cannot recharge or replace the batteries of the nodes during the mission, as the applications of WSNs include in underwater, forest driven and mountain based. Objective: Thus available energy must be utilized effectively. Energy efficient routing is one of the primary sources of energy management. Cluster-based routing in WSN is a prevalent method to achieve network performance and energy efficiency. In literature, the number of cluster-based energy efficient routing protocols and their route selection metric is designed based on the residual status of node energy. However, this metric causes some of the intermediate nodes to drain energy instantly. In wireless networks this situation roots intermediate nodes to turn into a bottleneck node, and thereby performance degradation in terms of efficiency and packet delivery caused. Methods: Thus our paper aims to design a cluster based routing protocol to prevent the creation of intermediate bottleneck node. We introduce a novel routing metric called “ranking status” for the bottleneck problem. Results: Performances results indicate that the proposed routing protocol prevents the creation of intermediate bottleneck node, and improve the network's performance.

A mobility‐aware cluster‐based MAC protocol for radio‐ frequency energy harvesting cognitive wireless sensor networks

Cognitive wireless sensor networks (CWSN) are severely energy constrained and radio frequency (RF) wireless energy harvesting (RFWEH) has been shown to improve the network lifetime. In many CWSN applications, node mobility imposes challenges owing to changing network topology. Therefore, the design of a new medium access control (MAC) protocol that can handle node mobility as well as energy harvesting is required. A cluster-based multihop MAC protocol (RMAC-M) is proposed that incorporates RF energy harvesting in a mobility-aware CWSN. Our protocol selects cluster heads using an algorithm based on an R-factor parameter consisting of residual node energy, residual node data and node speed, with appropriate weights. It then transmits data packages using a multitier super cluster head routing mechanism without the need for neighbour discovery. The multitier clustering and RFWEH mechanisms boost the energy performance of the network, increasing its lifetime. On the other hand, time slots allocated for RFWEH increase delay, thereby affecting system latency. Owing to its unique nature, the proposed algorithm has no comparable protocols in the literature. For the sake of completeness, RMAC-M is compared with well-known MAC protocols such as LEACH-M and KoNMAC that do not have energy harvesting or mobility features. Simulation results show that the proposed protocol increases the lifetime of the CWSN nodes substantially, promising a self-sustainable network in terms of energy. Furthermore, despite the allocation of time slots for energy harvesting, critical network parameters such as throughput, packet loss and average delay remain within target levels.