Multi-hop Routing Protocol Research Articles

The Supply Chain Financial Supervision Mechanism of the Internet of Things Based on the Integration of RFID and Wireless Sensor Network

Based on the fusion of wireless sensor modules and UHF RFID readers, this paper develops a UHF RFID reading and writing system based on wireless sensing technology and designs a communication interface circuit that integrates wireless sensing and RFID technology. The financial supervision mechanism of the Internet of Things compatible with these two technologies improves the communication distance limitation of the RFID system and improves the flexibility of the RFID reading and writing system. Secondly, in view of the security issues of WSN small and medium data distribution, this paper proposes a lightweight small data supply chain financial supervision program. The solution adopts two‐way authentication technology based on the improvement of the Internet of Things supply chain, the negotiation of the Internet of Things supply chain, and a lightweight encryption algorithm, which realizes the secure communication between ordinary nodes and gateway nodes, and can more effectively solve the problem of small and medium data distribution in WSN to resist the deficiencies of the financial supervision mechanism; compared with existing solutions of the same magnitude, it has higher security and efficiency. Experimental simulation shows that an important problem in the converged network is the imbalance of node energy consumption. In order to reduce the negative impact of the imbalance of energy consumption on the network, this article compares the two for direct transmission protocol and minimum energy multihop routing protocol. From the perspective of supply chain process performance, based on the proposed technical impact framework, it analyzes how companies actually carry out ID application work, making the research from general to individual, from theory to practice. The network energy consumption calculation method under this protocol improves an improved network architecture model that increases the communication scale. The test results show that the technical impact analysis framework established in this article based on the theory of the Internet of Things and the advantages of RFID technology can analyze the automation benefits, information benefits, and transformative benefits brought by automatic identification technology to the supply chain and introduce complementary resources and potential factors. It provides a theoretical basis and operation method for measuring the impact of RFID on the performance of the financial supervision process based on the Internet of Things supply chain in practical applications.

An Enhanced Multi-Hop Routing Protocol For Wireless Body Area Networks

Routing is one of the main issues in designing wireless body area networks. Some drawbacks are revealed in existing routing technologies for practical networks: First, defective criteria e.g., only energy or distance is considered to elect the forwarder nodes. Second, the protocol’s controllable parameters are decided manually, and for all application they stay fix, no automatic tuning is used. Third, the protocol is not altered and based on application specifications they remain optimized. In order to get the better of the above mentioned drawbacks, an EMRP named protocol which is an adaptive Enhanced Multi-hop Routing Protocol is proposed and implemented in this paper. In this, the forwarder nodes are elected based on high energy, low communication distance and low path-loss and low energy consumption loss. The EMRP protocol’s controllable parameters can be adaptively ad-justed and tuned according to application requirement via genetic algorithm. With this view the paper focuses on study and implementation of protocols in NS2 such that it elects forwarder nodes with high energy, low communi-cation distance, low path-loss and low energy consumption. The implementation of (EMRP): Enhanced Multi-hop Routing Protocol and M-Attempt in NS2 and comparison of EMRP and M-Attempt protocols depending on various parameters like Packet-Drop, Energy Consumption, Packet Delivery Ratio (PDR) and Throughput. Network simu-lation results of the proposed protocol exhibit significant improvement compared to existing protocols in terms of lifetime, path-loss, PDR, energy consumption and throughput.

A WSN Clustering Multi-Hop Routing Protocol Using Cellular Virtual Grid in IoT Environment

By dividing the grid and clustering multi-hop algorithm, the lifetime of WSN can be prolonged effectively, and the reliability of the system can be improved. In order to prolong network lifetime and balance network energy consumption, a WSN clustering multi-hop routing protocol for electric vehicles using cellular virtual grid is proposed. The routing mechanism divides cells into regular hexagons. In the cluster head selection stage, the node angle ratio, distance ratio, and throughput optimization threshold function are introduced to select cluster heads independently. In data transmission, single hop in cluster and mixed hop between clusters are used to optimize the path and reduce energy consumption when transmitting data among cluster head nodes. In the routing protocol, the path cost from the intermediate node to the target node is calculated according to the distance and residual energy. The simulation results show that the protocol has obvious advantages in reducing network energy consumption compared with several traditional algorithms when the running time reaches 1200 s and the network coverage is high.

Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks

Wireless sensor network is a hot research topic with massive applications in different domains. Generally, wireless sensor network comprises hundreds to thousands of sensor nodes, which communicate with one another by the use of radio signals. Some of the challenges exist in the design of wireless sensor network are restricted computation power, storage, battery and transmission bandwidth. To resolve these issues, clustering and routing processes have been presented. Clustering and routing processes are considered as an optimization problem in wireless sensor network which can be resolved by the use of swarm intelligence–based approaches. This article presents a novel swarm intelligence–based clustering and multihop routing protocol for wireless sensor network. Initially, improved particle swarm optimization technique is applied for choosing the cluster heads and organizes the clusters proficiently. Then, the grey wolf optimization algorithm–based routing process takes place to select the optimal paths in the network. The presented improved particle swarm optimization–grey wolf optimization approach incorporates the benefits of both the clustering and routing processes which leads to maximum energy efficiency and network lifetime. The proposed model is simulated under an extension set of experimentation, and the results are validated under several measures. The obtained experimental outcome demonstrated the superior characteristics of the improved particle swarm optimization–grey wolf optimization technique under all the test cases.

E2MR-HOA: Conservation of Energy through Multi-Hop Routing Protocol for WSN’S Using Hybrid Optimization Algorithm

Consuming energy at the maximal level is a major concern in wireless sensor networks (WSNs). Many researchers focus on reducing and preserving the energy. The duration of active network of WSNs is affected by energy consumption of sensor nodes. For typical applications such as structure monitoring, border surveillance, integrated into the external surface of a pipeline, and clambered along the sustaining structure of a bridge, sensor node energy efficiency is an important issue. The paper proposed an energy-efficient multi-hop routing protocol using hybrid optimization algorithm (E2MR-HOA) for WSNs. The proposed routing protocol consists of two algorithms, i.e., hybrid optimization algorithm. We present modified chemical reaction optimization (MCRO) algorithm to form clusters and select cluster head (CH) among the cluster members. Then the modified bacterial forging search (MBFS) algorithm is used to compute reliable route between source to destination. The proposed E2MR-HOA protocol is evaluated using NS2 simulations. The simulation result shows that the proposed routing protocol provides significant energy efficiency with network lifetime over the existing routing protocols.

Two-Level Clustering and Routing Algorithms to Prolong the Lifetime of Wind Farm-Based WSN

In recent years, wind power is emerging as one of the most promising renewable energy sources. Yet, reliability is less due to the unplanned downtimes caused by faults in the wind turbines. Monitoring of turbine elements with existing wired technology is not economical and hence replacement with smart wireless sensor devices are rapidly emerging as the next evolution. In such a wireless scenario, maximizing network lifetime and reliability is essential. The recently proposed hybrid multihop routing protocol aims to improve the lifetime of a WSN deployed in a widely distributed network. Though its performance is revealed to be better, the chain based CH selection and routing of data through MST increases the energy consumption thereby reducing the network lifetime. With an objective to circumvent this, three novel multihop routing strategies namely, Shortest Grid Routing, Partitioned Super Grid Direct Routing, and Shortest Super Grid Routing are proposed. For different network scenarios, the proposals are analyzed through simulation and validated via real time experimentation. The performance of the proposals is evaluated using metrics such as first node death, energy consumption, stability, and network reliability and are compared with the recently proposed protocol. The results reveal enhanced network lifetime and reliability which proves the applicability of the proposed routing protocols for CPS based infrastructure network.

Hybrid Wolf Pack and Particle Swarm Optimization Algorithm for Multihop Routing Protocol in WSN

Hybrid Wolf Pack and Particle Swarm Optimization Algorithm for Multihop Routing Protocol in WSN

Trust and Opportunity Based Routing Framework in Wireless Sensor Network Using Hybrid Optimization Algorithm

Opportunistic routing (OR) is the area of research in the trending scenario as the traditional methods for ensuring secure routing in the Wireless Sensor Networks (WSNs) suffer from the security and reliability issues. Though the existing multi-hop routing protocols are cheap and require less-intensive deployment, security is a major concern. The paper proposes the OR in WSNs using the hybrid optimization algorithm named, Monarch-Cat Swarm Optimization (M-CSO) which is the integration of Monarch Butterfly Optimization in Cat Swarm Optimization. The framework operates on two crucial aspects: one is to select the secure nodes and the other is to choose opportunistic nodes among selected secure nodes. The selection of secure nodes through the tolerant constant is based on the parameters of trust, connectivity, and QoS. The first two parameters are direct whereas, for QoS, Link Life Time and delay are considered to define it. Secondly, opportunistic nodes are optimally chosen through proposed M-CSO, based on the fitness parameters trust, distance, delay, and connectivity. The effectiveness of M-CSO based routing framework is evaluated using the performance metrics with 50 and 100 nodes in the presence of the attacks DoS, and Blackhole. The maximal detection rate, maximal throughput, minimum delay and minimum distance of the proposed M-CSO are 74.95, 77.7, 6.7 s and 102.67, respectively which is far better than competing methods Trust aware routing framework, Simple Opportunistic Adaptive Routing and Ant Colony Optimization for secured routing protocol. Moreover, M-CSO shows better performance as compared to the existing trust and opportunity based routing and optimization schemes.

WSN nodes power consumption using multihop routing protocol for illegal cutting forest

The need for an automation system from a remote area cannot be separated from the role of the wireless sensor network. However, the battery consumption is still a problem that influences the lifetime of the system. This research focused on studying how to characterize the power consumption on each sensor node using multihop routing protocol in the illegal logging field, to get the prediction lifetime of the network. The system is designed by using six sensor nodes in a master-slave connection and implemented in a tree topology. Each sensor node is consisting of a sound sensor, vibration sensor, Xbee communication, current and voltage sensor, and Arduino nano. The system is tested using battery 10050 mAH with several scenarios to have calculated how long the battery lifetime can be predicted. The results stated that the master node on the network depleted the power of the battery faster than the slave node since the more slaves connected to the master, the more energy the battery consumes.

Seamless clustering multi-hop routing protocol based on improved artificial bee colony algorithm

An important issue in the mobile sink wireless sensor networks (MSWSNs) is sensor energy optimization. In order to alleviate the problem of unbalanced network load and high energy consumption in MSWSNs, we proposed a new data collection protocol in this paper: seamless clustering multi-hop routing protocol based on improved artificial bee colony algorithm (IABCP). Because of limited by the communication sensing range and intelligence of ordinary nodes, routing paths can only be constructed by crude methods. And the movement of the sink node will generate a large amount of energy consumption for locating the sink node. In order to solve this problem, we assign the task of routing table generation to the sink node, which will generate the routing table through the improved artificial bee colony algorithm. In addition, we adopt a new method to select cluster head (CH) nodes; node uses the average energy of the surrounding nodes and its own residual energy to calculate the claimed cluster head time. Moreover, we added a sub cluster head CH-β node. When the CH node reaches the number of replacement rounds, the CH-β node becomes CH directly. The simulation results show that our routing protocol is more robust compared with three other protocols.

Multihop routing protocols on wireless ad hoc sensor networks with modified MAC layer and broadcasting scheme

SummaryMost sensor devices are equipped with local batteries, placing a limitation on available energy, assuming that replacement of batteries is not feasible. This constraint limits the operation time of sensor networks. In many scenarios, sensors are operating in remote or dangerous areas, and it is impractical to replace or recharge the battery of the sensors. In some scenarios, such as machine monitoring or medical monitoring, it is more convenient to install new sensors than to replace the battery of the sensor nodes. The focus of this article is to design routing methods to achieve the maximum operation time of sensor networks (the number of rounds to transmit data) under the constraint of battery sources. Therefore, the main contribution of this research is not to change any characteristic of the network infrastructure, but to define the interactions between nodes to achieve better energy efficiency.

Location‐based data delivery between vehicles and infrastructure

Multi-hop routing in vehicular ad-hoc networks (VANETs) and wireless sensor networks has attracted significant interest of researchers in the wireless ad-hoc networks community. Most multi-hop routing protocols in VANET are based around the idea of choosing the next destination, which will provide the shortest-delay to reach a destination. To ensure better monitoring and reporting of road condition information, this study proposes location-based data forwarding through roadside sensors using k-shortest path routing combined with Q-learning. Q-learning is used for exploration of the sensing field to determine those sensors which have a higher queuing delay during peak hours as well as those which have comparatively lower delays. The use of Q-learning for exploration (sans routing) enables faster convergence for the sensors as compared to those techniques which utilise naive Q-learning for shortest path routing. Secondly, multi-hop routing is being combined with source coding (Huffman and Arithmetic coding) to compress the data payload of packets. This has shown some promising results for the VANETs employing dedicated short-range communication.

RETRACTED ARTICLE: Multi-hop optimized routing algorithm and load balanced fuzzy clustering in wireless sensor networks

Now-a-days, wireless sensor node acts as a basement for a higher level industrial internet of things application. Any kind of real time IoT applications sense the data using already in-built sensors. In real time physical environment, sensors are having minimum amount of power for their operations such as sensing, communicating and processing the data. Many researches are carried out to improve the energy efficiency of sensor nodes and improves their network lifetime. More concentration is needed on clustering and routing part of the communication to go for energy saving. We have proposed an algorithm based on fuzzy and unequal clustering (FBUCA) and a three tier multi-hop optimized routing technique (TM-ORT) to improve the efficiency of the network. Energy consumption and data reliability are stabilized by QOS based multi-hop routing protocols. Whenever clustering plays a main role, load balancing among the clusters has to be important to concentrate. Load balancing has been achieved by choosing best parameters for fuzzy based clustering to select an efficient cluster head for data aggregation and routing. We have done experimental simulations and concluded the results in terms of performance metrics such as standard deviation (SD), First node Die (FND), total energy consumption (TEC) and average energy consumption (AEC).

Collaborative energy efficient zone‐based routing protocol for multihop Internet of Things

ABSTRACTIn Internet of Things (IoT) the nodes collaborate over a network in multihop manner and relay data toward IoT gateway that is ultimately connected to an IP network. The conventional multihop routing protocols assume that all nodes behave truthfully when they receive packets for downstream network but in reality, the IoT relaying nodes avoid message forwarding. The main reason of selfish behavior of nodes is the limited battery power. Many such nodes have limited battery constraint so these nodes may become selfish to save their energy. These nodes need to be encouraged to cooperate in order to increase network life time instead of just trying to increase node's own benefits. This paper discusses energy aware zone‐based routing technique that employs game theory to enhance nodes' cooperation and energy efficiency. The nodes follow a path with highest average energy for communication and provide collective support, hence the network life time is increases. For comparative analysis, simulation is performed for the proposed technique along with the existing techniques. The results show betterment in throughput, packet delivery ratio, and network life time.

Intelligent Agent-Based Assessment of a Resilient Multi-hop Routing Protocol for Dynamic WSN

Wireless sensor networks (WSN) constitute a current field of interest in which the major concerns are related to mobility, spatial distribution, connectivity and dynamic creation of networks between autonomous nodes for cooperative detection and data transfer in diverse areas (e.g., healthcare, environmental or industrial monitoring). To this end, the present work describes the theoretical and practical development of a communication protocol for WSNs based on Bluetooth. The interaction between mobile nodes is performed with a multi-hop scheme in response to traffic needs without requiring a scatternet formation procedure. The interest of this algorithm—based on the concept of routing vector—is that it was designed to withstand changes in the node distribution for high-mobility scenarios, thus allowing the implementation of a robust data routing in low-resource microcontrolled devices with no operability loss. As the main contribution, we present the hardware and software implementation of the communication protocol in real devices along several case studies. With this aim, a long-term experimentation in a dense scenario has been carried out through an intelligent agent-based approach to formally validate the protocol considering three different performance metrics: packet delivery ratio, feedback overhead and round-trip time.

Efficient and secured information transfer for congestion avoidance and collision detection in vehicular ad hoc networks (V2V) methodology

Vehicular ad hoc networks (VANET) connects the vehicle and the infrastructure in solving various issues on the travel path. In this paper, a multi-hop routing protocol is established to transfer the information among vehicles when the infrastructure is out of range from the source and provides warning system on congestion level. This increases the efficiency and reduces the cost of establishing the infrastructure mechanism at various points. The timely reporting at the infrastructure for decision making is the key concern and it has been addressed in this proposed concept. In addition, a payload format is proposed with the essential parameters such as position status, speed, heading, vehicle identification number, date etc. This gives the complete information about the vehicle thereby updating the database for future reference. Simulations of route path, message transfer frequency and time frame distribution is done with NS-2.

Centralized Routing Protocol for Detecting Wormhole Attacks in Wireless Sensor Networks

Nodes in wireless sensor networks (WSN) are resource and energy-constrained because they are generally batteries powered and therefore have limited computational capability. Due to the less secure environment in WSN, some malicious nodes at one point can tunnel packets to another location to damage the network in terms of packets dropping and eavesdropping and this is a so-called wormhole attack. Many of the current protocols solve the wormhole attack problem in isolation from the node energy consumption. However, some other proposed solutions consider reducing the energy consumption to detect such attacks but still it is needed to probe better performance. In this paper, we present a lightweight multi-hop routing protocol for 802.15.4 WSN that aims to minimize the energy consumption and also to detect the wormhole attacks. Simulation results prove that our MAC Centralized Routing Protocol (MCRP) outperforms other existing similar protocols.

A Hybrid Swarm Intelligence Algorithm for Clustering-Based Routing in Wireless Sensor Networks

Wireless sensor networks (WSNs) comprise a large number of tiny sensing nodes, which are battery-powered with limited energy. An energy-efficient routing protocol is of utmost importance to prolong the network lifetime. Clustering is the most common technique to balance energy consumption among all nodes, while minimizing traffic and overhead during the data transmission phases. In this paper, a Multi-Objective nature-inspired algorithm based on Shuffled frog-leaping algorithm and Firefly Algorithm (named MOSFA) as an adaptive application-specific clustering-based multi-hop routing protocol for WSNs is proposed. MOSFA’s multi-objective function regards different criteria (e.g., inter- and intra-cluster distances, the residual energy of nodes, distances from the sink, overlap, and load of clusters) to select appropriate cluster heads at each round. Moreover, another multi-objective function is proposed to select the forwarder nodes in the routing phase. The controllable parameters of MOSFA in both clustering and multi-hop phases can be adaptively tuned to achieve the best performance based on the network requirements according to the specific application. Simulation results demonstrate average lifetime improvements of 182%, 68%, 30%, and 28% when compared with LEACH, ERA, SIF, and FSFLA, respectively, in different network scenarios.

Improved method of OGM packet statistics and measurement calculation in BATMAN. Adv routing protocol

In the performance test of mesh network routing protocol, it is found that BATMAN. Adv routing protocol has better performance than the existing multi-hop routing protocol, but it also has the defects of poor routing convergence and slow response to network topology changes. Based on the detailed analysis of BATMAN. Adv routing protocol, this paper proposes an improved method. First, the statistical method of OGM package was redesigned, the cumulative sliding window method is used to improve the influence of the latest serial number of OGM, and the calculation method of TQ value is changed from average accumulation to weighted accumulation to further improve the influence of the latest TQ value. At the same time, an improved mechanism is proposed in order to solve the problem of link blocking caused by sudden node failure. Finally, through simulation experiments, the performance of the packet delivery rate and end-to-end delay of the three routing protocols in two different scenarios is compared. It shows that the improved protocol can effectively improve the packet delivery rate, reduce the average end-to-end delay, and improve the network performance.

Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm

The advancements of Wireless sensor network (WSN) in large number of applications made it common. However, the energy is a major challenge in the WSN environment as the battery-operated sensor nodes in the network consumes huge amount of energy during transmission. This work addresses the energy issue and provides an energy efficient multi-hop routing in WSN named Taylor based Cat Salp Swarm Algorithm (Taylor C-SSA) by modifying C-SSA with Taylor series. This method undergoes two stages for attaining multi-hop routing, which includes selection of cluster head (CH), and transmission of data. Initially, the energy-efficient cluster heads are selected using the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for effective data transmission, the sensor nodes sends data over the CH, which transmits the data to the base station through the selected optimal hop. The optimal hop selection is done using the proposed Taylor C-SSA. Moreover, the security aware multi-hop routing is performed by introducing trust model that involves indirect trust, integrity factor, direct trust, and data forwarding rate. The proposed Taylor C-SSA algorithm shows best performance in terms of energy, number of alive nodes, delay, and throughput values of 0.129, 42, 0.291, and 0.1, respectively.