Maximum Residual Energy Research Articles

Study on the influencing factors of impact resistance of shear thickening fluids filled foam

PurposeThe present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.Design/methodology/approachThe maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).FindingsThe following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35 g/cm3, the hardness is 45HC and the thickness is 10 mm.Originality/valueThis is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.

Communication efficient federated learning with data offloading in fog-based IoT environment

Federated Learning (FL) has become a popular distributed machine learning technique that preserves privacy of data set generated by the Internet of Things (IoT) devices. However, straggler effect, and communication delay are the two major issues that should be properly taken care during model preparation of any FL process. In this study, we propose a novel and efficient scheme, called Fog Cloud Assisted Federated Learning (FCAFL) in IoT platform that address these issues. Specifically, the proposed scheme is shown to reduce the overall communication delay of the global model preparation in the FL process. It is also able to resolve straggler effect by employing clustering of the IoT devices with an efficient scheme of cluster head (CH) selection based on minimum intra-cluster distance and maximum residual energy. In order to reduce communication delay further, we also propose an efficient scheme of fog node selection using Genetic Algorithm (GA) by formulating the data offloading as a single objective problem with latency as an offloading parameter. There are some existing schemes which address straggler effect and communication delay. However, none of their approaches incorporate explicit clustering technique utilizing residual energy and minimum intra-cluster distance of the CHs to select clients, aiming to address the straggler effect. Additionally, their works do not involve any data offloading as a means to reduce communication delay in the FL process. The simulation results demonstrate better performance of the proposed FCAFL as compared to the traditional FL and existing approaches, namely, Hierarchical Federated Edge Learning (HFEL) and FedFog with respect to communication cost. The FCAFL also outperform traditional FL and HFEL with respect to training and testing accuracy of the produced FL model. The validity of the result is additionally proved through a widely recognized statistical technique, the analysis of variance (ANOVA), followed by a least significant difference (LSD) post-hoc analysis.

Simulation and Experimental Study on the Precision Molding of Irregular Vehicle Glass Components.

The high level of stress and dimension deviation induced by glass molding are the main causes of the low yield rate of large, irregular glass components on vehicles. To solve this issue, a numerical model of large glass component molding was established in this study, which aimed to analyze the dominant factors of molding quality and achieve a synergistic balance between quality characteristics and energy consumption. The results show that molding temperature is the dominant factor affecting the energy consumption and residual stress, and the molding pressure is the main factor affecting the dimension deviation. Furthermore, the NSGA-II optimization algorithm was used to optimize the maximum residual stress, dimension deviation, and energy consumption with the numerical results. The combination of a heating rate of 1.95 °C/s, holding time of 158 s, molding temperature of 570 °C, molding pressure of 34 MPa, and cooling rate of 1.15 °C/s was determined to be the optimized scheme. The predictive error of the numerical result, based on the optimized scheme, was experimentally verified to be less than 20%. It proved the accuracy of the model in this study. These results can provide guidance for the subsequent precision molding of large, irregular glass components.

FE model to define impacting resistance behavior of RC beams protected by AlSi10Mg buffer interlayer

Inspired by the biological structure of the beetle elytra, the bio-inspired honeycomb column thin-walled structure (BHTS) is designed as lightweight buffer interlayer to prevent the key parts of reinforced concrete (RC) beams of engineering structures under overload impact from destruction. The mechanical properties of the additive manufacturing technology selective laser melting (AM-SLM) BHTS material AlSi10Mg were determined through quasi-static and medium-speed uniaxial compression tests. Based on the drop weight test models, the maximum impact force and duration, maximum displacement and residual displacement, energy proportion and other indicators, the impact of the buffer interlayer on the dynamic response of RC beams were compared under the drop weight test at different heights. The results showed that the proposed BHTS buffer interlayer has a very significant impact protection effect on the RC beam: the average energy absorption (EA) of the BHTS buffer interlayer is 25.65 % of the total internal energy, which greatly reduces the energy input into the RC beam. In addition, based on the study of the drop weight test simulation of BHTS buffer interlayer, an approximate calculation model for predicting the ultimate displacement of BHTS-RC beam is proposed, which can be used as an important method for assessing the damaging degree of reinforced beam under impact load quickly. BHTS can be used as a replaceable structure to avoid impact damage to RC components in structural engineering.

ESTEEM – Enhanced stability and throughput for energy efficient multihop routing based on Markov Chain Model in wireless body area networks

Wireless Medical Body Area Sensor Network (WMBASN) monitors vital human biological parameters used for various healthcare and fitness applications. The design and development of a reliable WMBASN routing protocol with improved network performance are significant tasks for researchers and healthcare industries. This work focuses on multi-hop routing to select a relay node to collect data from far away sensor nodes and to Central Coordinator Node (CCN). A novel approach for choosing best fitted Assistive Node (AN) by incorporating Hidden Markov Chain Model (HMCM) called Enhanced Stability and Throughput for Energy Efficient Multihop routing protocol (ESTEEM). Selection Function selects the best-fitted AN based on HMCM relating to maximum residual energy and minimum distance between the sensor node and CCN. The outcome of the proposed ESTEEM achieves increased throughput, better stability with the first dead node and extended network lifetime with the last dead node at 71% and 95.1% of total simulation time, respectively. In addition, the proposed work also concentrates on CCN placed at different positions on the human body to analyze and identify its best position for better routing. Overall, an improved multi-hop, energy efficiency and better quality of service are achieved based on specific network parameters with random postural movements through ESTEEM, and the results are superior to conventional routing protocols.

Protective Behaviors of Bio-Inspired Honeycomb Column Thin-Walled Structure against RC Slab under Impact Loading.

In order to protect the reinforced concrete (RC) slab structure from damage under some accidental conditions, such as impacting and explosion, we used bio-inspired honeycomb column thin-walled structure (BHTS) to serve as a buffer interlayer for the concrete structure inspired by the biological structure of beetle's elytra. The mechanical properties of AlSi10Mg used to fabricate the BHTS buffer interlayer were determined by low- and medium-speed uniaxial compression tests and numerical simulations. Subsequently, based on the drop weight impact test models, the effect of the buffer interlayer on the response of the RC slab under the drop weight tests with different energy input was compared by the impact force and duration, maximum displacement and residual displacement, energy absorption (EA), energy proportion, and other indicators. The results show that the proposed BHTS buffer interlayer has a very significant protection effect on the RC slab under the impact of the drop hammer. Due to its superior performance, the proposed BHTS buffer interlayer provides a promising solution for EA of augmented cellular structures widely used in defensive structural components, such as floor slabs, building walls, etc.

An Energy-Aware and Fault-Tolerant WSN Routing Approach Using Serial Exponential Newton Metaheuristic Algorithm for Agricultural Lands

Wireless Sensor Network (WSN) is becoming a promising platform, in which Sensor Nodes (SNs) can sense and monitor the physical or environmental conditions and send the data to the Base Station (BS) through multi-hop routing. Here, opting for the right Cluster Head Selection (CHS) is the key to enhancing the clustering routing protocol performance. Here, a new optimization model to prolong the lifetime of the network and progress the energy efficiency in the routing process is anticipated. The Serial Exponential Newton Meta heuristic algorithm (SExpNMA) is developed for CHS and routing. The parameters like energy, Link Lifetime (LLT), and delay, are considered as the fitness function of the proposed SExpNMA to select the optimal solution. Ultimately, the performance analysis clearly reveals that the SExpNMA technique attains the maximum residual energy of 0.515 J, LLT of 0.346, the throughput of 0.617, and minimum delay of 0.236 s, respectively.

FBCHS: Fuzzy Based Cluster Head Selection Protocol to Enhance Network Lifetime of WSN

With enormous evolution in Microelectronics, Wireless Sensor Networks (WSNs) have played a vital role in every aspect of daily life. Technological advancement has led to new ways of thinking and of developing infrastructure for sensing, monitoring, and computational tasks. The sensor network constitutes multiple sensor nodes for monitoring, tracking, and surveillance of remote objects in the network area. Battery replacement and recharging are almost impossible; therefore, the aim is to develop an efficient routing protocol for the sensor network. The Fuzzy Based Cluster Head Selection (FBCHS) protocol is proposed, which partitions the network into several regions based on node energy levels. The proposed protocol uses an artificial intelligence technique to select the Cluster Head (CH) based on maximum node Residual Energy (RE) and minimum distance. The transmission of data to the Base Station (BS) is accomplished via static clustering and the hybrid routing technique. The simulation results of the FBCHS protocol are com- pared to the SEP protocol and show improvement in the stability period and improved overall performance of the network.

Energy aware farmland fertility optimization based clustering scheme for wireless sensor networks

Wireless Sensor Networks (WSNs) encompass an enormous set of spatially dispersed sensor nodes connected via wireless links for monitoring and recording the physical data in the target region. The nodes in WSN operate via an inbuilt battery which depletes the energy after a certain period. The partitioning of networks into clusters or groups is one of the efficient solutions to lengthen the lifespan of the WSN. The clustering process can be treated as an NP-hard optimization problem and the utilization of metaheuristics has drastically raised the ability to resolve continuous optimization problems. This study designs an energy-aware farmland fertility optimization-based clustering scheme (EAFFOCS) for WSN. An objective of the EAFFOCS technique is for determining the optimal nodes as CHs and enhancing the overall network efficiency. The proposed EAFFOCS technique is based on the concepts of farmland fertility. Besides, the EAFFOCS technique derives a fitness function involving three input variables like distance to neighbours, distance to BS, and energy. Using the fitness function values, the EAFFOCS technique chooses the node with maximum fitness as CHs. Then, the nodes placed closer to the CHs are joined together to form a cluster. To demonstrate the improved outcomes of the EAFFOCS technique, a wide range of simulations was carried out and the outcomes are inspected under several aspects. The comparative outcomes reported the better performance of the EAFFOCS technique with the maximum residual energy of 11% under the presence of 1000 sensor nodes whereas the HABC-MBOA, FFCGWO, FFOCR, and HASPSO systems have resulted in least RE of 10%, 5%, 2%, and 1% correspondingly.

Enhanced Metaheuristics with Trust Aware Route Selection for Wireless Sensor Networks

Recently, a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks (WSN). In routing, the trust system includes or avoids nodes related to the estimated trust values in the routing function. This article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol (EMTA-SRSP) for WSN. The presented EMTA-SRSP technique majorly involves the optimal selection of routes in WSN. To accomplish this, the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data communication. For the clustering process, the nodes with maximum residual energy will be considered cluster heads (CHs). In addition, the OAOA technique gets executed to choose optimal routes based on objective functions with multiple parameters such as energy, distance, and trust degree. The experimental validation of the EMTA-SRSP technique is tested, and the results exhibited a better performance of the EMTA-SRSP technique over other approaches.

An Energy Efficient Load Balancing Tree-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks

A wireless sensor network (WSN) consists of a very large number of sensors which are deployed in the specific area of interest. A sensor is an electronic device equipped with a small processor and has a small-capacity memory. The WSN has the functions of low cost, easy deployment, and random reconfiguration. In this paper, an energy-efficient load balancing tree-based data aggregation scheme (LB-TBDAS) for grid-based WSNs is proposed. In this scheme, the sensing area is partitioned into many cells of a grid and then the sensor node with the maximum residual energy is elected to be the cell head in each cell. Then, the tree-like path is established by using the minimum spanning tree algorithm. In the tree construction, it must meet the three constraints, which are the minimum energy consumption spanning tree, the network depth, and the maximum number of child nodes. In the data transmission process, the cell head is responsible for collecting the sensing data in each cell, and the collected data are transmitted along the tree-like path to the base station (BS). Simulation results show that the total energy consumption of LB-TBDAS is significantly less than that of GB-PEDAP and PEDAP. Compared to GB-PEDAP and PEDAP, the proposed LB-TBDAS extends the network lifetime by more than 100%. The proposed LB-TBDAS can avoid excessive energy consumption of sensor nodes during multi-hop data transmission and can also avoid the hotspot problem of WSNs.

Effect of Confining Pressure on Mechanical and Energy Conversion Properties of Gas-Containing Coal under Loads

Confining pressure is closely related to the deformation and failure characteristics of gas-containing coal and is one of the key factors for gas outburst-rockburst coupled dynamic disaster. Firstly, this paper briefly summarized the triaxial compression test results of gas-containing coal under different confining pressures, including deformation and stiffness and failure and strength. Then, based on the second developed MatDEM gas-solid coupling program, the macro- and microdeformation and failure process of coal samples under different confining pressures and constant gas pressure were simulated, and the distribution of particle stress, pore stress, and crack, as well as energy conversion characteristics, was obtained. Finally, the influence mechanism of confining pressure on deformation and failure of gas-containing coal was discussed, and the occurrence conditions of coal and gas outburst, rockburst, and their coupled dynamic disasters were distinguished. The results show that the peak strength and residual strength after failure of gas-containing coal both increase approximately linearly with the increase of confining pressure, while the elastic modulus does not change much or increases continuously, which is closely related to the number of microdefects in the coal sample. The strengthening effect of confining pressure on rock stiffness and strength mainly comes from external support and compaction. The total number of cracks decreases with the increase of confining pressure, while the number of shear cracks increases, and the inclination angle between the formed macroscopic main crack and the horizontal plane gradually decreases. The maximum cumulative elastic energy and residual elastic energy both increase with the increase of confining pressure, which leads to the increase of the impact tendency index of coal samples.

IBRE-LEACH: Improving the Performance of the BRE-LEACH for Wireless Sensor Networks

Wireless sensor networks are extensively used in different fields, including severe and harsh environments such as battlegrounds, volcanic areas, healthcare, and so on. The major constraint of WSNs is the limited power supply, which impacts the lifecycle of the entire network. Clustering is a performing method used in WSNs to optimize power consumption and extend the lifetime of WSNs. LEACH is considered the first classical clustering protocol used in WSNs to optimize energy consumption. Many protocols have been developed to enhance the conventional LEACH protocol. BRE-LEACH (Balanced Residual Energy LEACH) is one of them. It is used to enhance the performance of the LEACH protocol. In this paper, we propose a new improved BRE-LEACH protocol called IBRE-LEACH (Improved Balanced Residual Energy LEACH), which improves the performance of the BRE-LEACH approach. The IBRE-LEACH combines clustering and multi-hop techniques. It selects CHs according to the residual energy and limits the maximum number of nodes in each cluster to balance the energy consumption. Thus, IBRE-LEACH allows the Abandoned Nodes to send their data to the BS. Furthermore, it routes the gathered data using CHs, ANs, and a root node, which is a node with maximum residual energy and minimum distance to the BS. The simulation results in MATLAB show that the IBRE-LEACH protocol increases the throughput, optimizes energy consumption, extends network lifetime, and ameliorates stability by 81.99%, 94.33%, and 91.47% compared to BRE-LEACH, LEACH-C, and LEACH, respectively.

Blockchain Based Authentication and Cluster Head Selection Using DDR-LEACH in Internet of Sensor Things.

This paper proposes a blockchain-based node authentication model for the Internet of sensor things (IoST). The nodes in the network are authenticated based on their credentials to make the network free from malicious nodes. In IoST, sensor nodes gather the information from the environment and send it to the cluster heads (CHs) for additional processing. CHs aggregate the sensed information. Therefore, their energy rapidly depletes due to extra workload. To solve this issue, we proposed distance, degree, and residual energy-based low-energy adaptive clustering hierarchy (DDR-LEACH) protocol. DDR-LEACH is used to replace CHs with the ordinary nodes based on maximum residual energy, degree, and minimum distance from BS. Furthermore, storing a huge amount of data in the blockchain is very costly. To tackle this issue, an external data storage, named as interplanetary file system (IPFS), is used. Furthermore, for ensuring data security in IPFS, AES 128-bit is used, which performs better than the existing encryption schemes. Moreover, a huge computational cost is required using a proof of work consensus mechanism to validate transactions. To solve this issue, proof of authority (PoA) consensus mechanism is used in the proposed model. The simulation results are carried out, which show the efficiency and effectiveness of the proposed system model. The DDR-LEACH is compared with LEACH and the simulation results show that DDR-LEACH outperforms LEACH in terms of energy consumption, throughput, and improvement in network lifetime with CH selection mechanism. Moreover, transaction cost is computed, which is reduced by PoA during data storage on IPFS and service provisioning. Furthermore, the time is calculated in the comparison of AES 128-bit scheme with existing scheme. The formal security analysis is performed to check the effectiveness of smart contract against attacks. Additionally, two different attacks, MITM and Sybil, are induced in our system to show our system model’s resilience against cyber attacks.

Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

Wireless Body Area Network (WBAN) technologies are emerging with extensive applications in several domains. Health is a fascinating domain of WBAN for smart monitoring of a patient's condition. An important factor to consider in WBAN is a node's lifetime. Improving the lifetime of nodes is critical to address many issues, such as utility and reliability. Existing routing protocols have addressed the energy conservation problem but considered only a few parameters, thus affecting their performance. Moreover, most of the existing schemes did not consider traffic prioritization which is critical in WBANs. In this paper, an adaptive multi-cost routing protocol is proposed with a multi-objective cost function considering minimum distance from sink, temperature of sensor nodes, priority of sensed data, and maximum residual energy on sensor nodes. The performance of the proposed protocol is compared with the existing schemes for the parameters: network lifetime, stability period, throughput, energy consumption, and path loss. It is evident from the obtained results that the proposed protocol improves network lifetime and stability period by 30% and 15%, respectively, as well as outperforms the existing protocols in terms of throughput, energy consumption, and path loss.

Optimal Routing Protocol for Wireless Sensor Network Using Genetic Fuzzy Logic System

The wireless sensor network (WSN) is a growing sector in the network domain. By implementing it many industries developed smart task for different purposes. Sensor nodes interact with each other and this interaction technique are handled by different routing protocol. Extending the life of the network in WSN is a challenging issue because energy in sensor nodes are quickly drained. So the overall performance of WSN are degraded by this limitation. To resolve this unreliable low power link, many researches have provided various routing protocols to make the network as dependable and sustainable as possible. While speeding up the data delivery is also considered to be an effective approach to save energy. To achieve this objective, we propose a new energy efficient routing protocol using genetic fuzzy logic system. Our primary objective is to save energy by sending data packets via the shortest path. Numerous studies have proved that the clustering protocol plays an important role in prolonging the life of the sensor node in the WSN. Keeping up with this our second objective is selection of head node from a cluster. This cluster head is selected based on the availability of maximum residual energy among the nodes, lifetime of head-to-head link, and its minimum distance to the base station. The genetic fitness approach is proposed for optimal routing and the selection of cluster head (CH) is employed with fuzzy logic system. As a result, the genetic fuzzy logic system (GFLS) can effectively accelerate the process to solve this problem. MATLAB is used to deploy nodes in WSN. The performance is calculated in terms of efficiency, delay, packet delivery rate and network throughput. The performance is compared with previous pertinent work. The proposed approach has elevated its performance around 8% in packet delivery and 6% in overall network throughput.

Investigation on seismic behavior of RC shear walls with multiple post-construction openings based on experiment and simulation

The quasi-static tests and finite element simulations of one shear wall without openings and three shear walls with the same total area but different arrangement of post-construction openings were carried out. The failure modes, ultimate loading capacities, skeleton curves, energy dissipation capacities, shear deformations and strain distribution of the shear wall specimens were obtained and analyzed. The results showed that the layout of post-openings has different effects on the failure mode of shear wall. The failure modes of shear wall without openings and the wall with two post-openings arranged vertically in the middle are flexural shear failure with damage at the wall base, while that of the shear wall with one post-openings in the middle or two post-opening arranged horizontally in the middle is shear failure which occurred on the wall limbs on both sides of the openings. The opening generates redistribution of strains in the wall, revealing that the largest strain does not occur at the bottom of the wall, but at the upper corner and bottom corner of the openings, which leads to the vertical reinforcement near the opening to bear greater stress, so it reaches the yield earlier than that in the wall without opening. Compared with the shear wall without openings, the wall with two openings in the horizontal direction has the minimum residual bearing capacity, ductility and energy dissipation capacity, while the wall with two openings in the vertical direction had the maximum residual bearing capacity, ductility and energy dissipation capacity. The energy dissipation capacity, the shear deformation as well as the contribution of shear deformation to the total deformation were all significantly reduced by post-openings.

A Novel Energy-Efficient Clustering Algorithm for More Sustainable Wireless Sensor Networks Enabled Smart Cities Applications

Wireless Sensor Networks (WSNs) is a major sensing technology that has revolutionized the way information is collected, processed, and used in many smart cities’ applications that rely on sensing technologies for event detection and monitoring. Despite the multiple benefits that such technology offers, the quick depletion of sensors’ battery power represents a major concern, mainly due to the extensive computational tasks and communication operations performed by individual sensors. Indeed, the cost of replacing batteries can be prohibitively expensive, especially when sensors are deployed in areas where access is difficult, in urbanized cities. To extend sensors’ lifetime, this paper proposes a new variant of LEACH protocol named LEACH enhanced with probabilistic cluster head selection (LEACH-PRO). LEACH-PRO introduces several measures to extend WSNs nodes’ lifetime such as cluster head node selection using a probabilistic function based on maximum residual energy and minimum distance to the sink. The obtained simulation results have proven the supremacy of LEACH-PRO over LEACH and direct transmission protocol in terms of the achieved network lifetime and the generated traffic overhead. Most importantly, LEACH-PRO will significantly extend the sensors’ lifetime, which would make this type of deployment more viable in smart city scenarios.

Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption

Wireless sensor network (WSN) can achieve real-time data collection and transmission of environment, soil, meteorology, crop physiology and other information in agriculture. The data provided by WSN could be used for decision making and management, which is very important in precision agriculture. Wheat farmland wireless sensor network has the characteristics of wide coverage area, long planting period, inconvenient energy supply, and serious impact of crop environment on wireless signal transmission. Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission. According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland, a non-uniform clustering routing protocol based on effective energy consumption (UCEEC) was proposed in this work. The method combined with the characteristics of multi-path fading of farmland environment signals. The idea of image segmentation was introduced. Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance. Meanwhile, a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed. The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network. Simulation results show that, compared with the existing Maximum Residual Energy Based Routing (MREBR) protocol, minimum Energy Consumption Based Routing (MEC) routing protocols, UCEEC improves the energy balance effect between nodes, prolongs the network life cycle, and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. Keywords: farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimization DOI: 10.25165/j.ijabe.20211403.6540 Citation: Miao Y S, Zhao C J, Wu H R. Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. Int J Agric & Biol Eng, 2021; 14(3): 163–170.

A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm

Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the wireless sensor network is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. In this paper, a routing protocol is proposed and simulated based on an ant colony optimization algorithm’s performance. The clustering is performed with a routing method based on energy level criteria, collision reduction, distance from the cluster-head to the destination, and neighborhood energy in the proposed method. The cluster head is selected based on the maximum residual energy, minimum distance with other clusters, and consumed energy. This energy is minimized to reach the base station. The node with more energy than the threshold is selected as the new cluster head. Then, four conditions are applied for routing: the shortest path, the leading path, the shortest distance to the source node and the destination node, and routing. Results show that after about 50 cycles of transferring information, only the average of 19.4% of the initial energy is consumed in the network nodes. Therefore, obtained results illustrate that the proposed method helps to retain the energy more than 40% comparing the available methods.