Balanced Routing Research Articles

Real-time detection of energy consumption of IoT network nodes based on artificial intelligence

Low power loss networks and wireless sensor networks are important components of the Internet of Things. With the development and popularization of artificial intelligence, the network application of wireless sensors is gradually scaled up and industrialized. Aiming at the problems of high energy consumption of the routing strategy, the algorithm protocol is easy to fall into the local optimum and the uneven energy consumption of network nodes. This paper proposes a regional energy balance routing algorithm based on intelligent chaotic ant colony. Based on the intelligent chaotic ant colony algorithm, combined with the remaining energy factors of wireless sensor network nodes, this paper propose a neighbor selection strategy. In order to enhance the ant search ability and speed up the algorithm convergence, an adaptive perturbation strategy and algorithm termination conditions are proposed respectively to find the global optimal solution and avoid falling into the local optimal solution. Simulation results show that the routing planning method in this paper has obvious advantages in terms of network energy consumption and network delay, node equilibrium energy distribution, network life cycle and other performance. Compared with similar algorithms, the average energy consumption has been saved by 7.3%.

Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks

Wireless sensor networks (WSN) are gaining attention in numerous fields with the advent of embedded systems and IoT. Wireless sensors are deployed in environmental conditions where human intervention is less or eliminated. Since these are not human monitored, powering and maintaining the energy of the node is a challenging issue. The main research hotspot in WSN is energy consumption. As energy drains faster, the network lifetime also decreases. Self-Organizing Networks (SON) are just the solution for the above-discussed problem. Self-organizing networks can automatically configure themselves, find an optimal solution, diagnose and self-heal to some extent. In this work, “Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks” is introduced which uses self-organization to balance energy and thus reduce energy consumption. This protocol uses combination of number of neighboring nodes and residual energy as the criteria for efficient cluster head election to form a tree-based cluster structure. Threshold for residual energy and distance are defined to decide the path of the data transmission which is energy efficient. The improvement made in choosing robust parameters for cluster head election and efficient data transmission results in lesser energy consumption. The implementation of the proposed protocol is carried out in NS2 environment. The experiment is conducted by varying the node density as 20, 40 and 60 nodes and with two pause times 5ms, 10ms. The analysis of the result indicates that the new system consumes 17.6% less energy than the existing system. The routing load, network lifetime metrics show better values than the existing system.

Selective-path clustered-based routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSNs) consist of large number of small low-powered electronic sensor devices. Therefore, reliable power saving schemes must be developed in order to manage the energy dissipated and extend the network life and functionality for a meaningful time. Arranging sensor nodes (SNs) into clusters has been viewed as an efficient approach of balancing the energy dissipated in WSNs. Regardless, a clustered WSN needs a robust energy efficient (EE) and energy balanced (EB) routing communication protocol. This paper proposes a selective-path priority table (SPT) EE and EB routing protocol (RP) ideal for most conventional clustering algorithms. The SPT RP forms the priority table by prioritising the k nearest multi-hop paths to the cluster heads (CHs) and/or base station (BS) based on some robust rules. These rules are compiled using a combination of some routing metrics which include the residual energy (RE) and transmission range/power. Firstly, the simulation results indicate that the SPT RP can be combined with most of the conventional clustering algorithm irrespective of the number of deployed SNs. Secondly, the performance of the SPT RP improves as the value of the selected number of routing paths (k) increase. More so, the simulation results show that the SPT RP reduces the energy dissipated and can prolong the network life and throughput as compared to related routing schemes.

Selective-path clustered based routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSNs) consist of large number of small low-powered electronic sensor devices. Therefore, reliable power saving schemes must be developed in order to manage the energy dissipated and extend the network life and functionality for a meaningful time. Arranging sensor nodes (SNs) into clusters has been viewed as an efficient approach of balancing the energy dissipated in WSNs. Regardless, a clustered WSN needs a robust energy efficient (EE) and energy balanced (EB) routing communication protocol. This paper proposes a selective-path priority table (SPT) EE and EB routing protocol (RP) ideal for most conventional clustering algorithms. The SPT RP forms the priority table by prioritising the k nearest multi-hop paths to the cluster heads (CHs) and/or base station (BS) based on some robust rules. These rules are compiled using a combination of some routing metrics which include the residual energy (RE) and transmission range/power. Firstly, the simulation results indicate that the SPT RP can be combined with most of the conventional clustering algorithm irrespective of the number of deployed SNs. Secondly, the performance of the SPT RP improves as the value of the selected number of routing paths (k) increase. More so, the simulation results show that the SPT RP reduces the energy dissipated and can prolong the network life and throughput as compared to related routing schemes.

Investigation on optimisation, prioritising and weight allocation techniques for load balancing and controlling multimedia traffic in wireless mesh network

Wireless mesh network (WMN) is a type of wireless ad hoc network where radio nodes are wirelessly connected within sizable geographic area through mesh topology. The best path is identified by routing metrics to ensure efficient data transmission from source node to destination node. The performance of routing is concern with set of routing constraints such as bandwidth, network delay, energy consumption, load balancing and communication cost. The routing constraints are needed to be resolved to improve the WMN performance. In WSN, network load balancing plays a significant role to achieve effective routing without traffic. The energy consumption is an additional factor to provide high-quality data delivery at the destination end. Our research work is concentrated on developing the energy efficient and load balanced routing in WMN.

Investigation on optimisation, prioritising and weight allocation techniques for load balancing and controlling multimedia traffic in wireless mesh network

Wireless mesh network (WMN) is a type of wireless ad hoc network where radio nodes are wirelessly connected within sizable geographic area through mesh topology. The best path is identified by routing metrics to ensure efficient data transmission from source node to destination node. The performance of routing is concern with set of routing constraints such as bandwidth, network delay, energy consumption, load balancing and communication cost. The routing constraints are needed to be resolved to improve the WMN performance. In WSN, network load balancing plays a significant role to achieve effective routing without traffic. The energy consumption is an additional factor to provide high-quality data delivery at the destination end. Our research work is concentrated on developing the energy efficient and load balanced routing in WMN.

An Energy Balanced Routing Hole and Network Partitioning Mitigation Model for Homogeneous Hierarchical Wireless Sensor Networks

This article addresses the challenges of routing hole and network partitioning often experienced in hierarchical wireless sensor networks (WSNs). This developed model classifies network nodes into sets for effective energy management and formulates two cluster networks namely: switching and non-switching networks. Both networks are considered homogeneous and static WSNs and adopted approaches of residual energy, multi-hop and minimal distance as routing decision parameters. The switching network in addition introduces an energy switching factor as a major decision parameter for the switching of cluster head roles amongst cluster nodes. Network simulation was done using Truetime 2.0 and energy dissipation of the respective nodes and cluster heads was observed against a threshold. Results showed the introduction of the energy switching factor gave a significant energy balancing effect as nodes exhibited uniform energy dissipation. Furthermore, the residual energies for most nodes were above the threshold eliminating the possibility of the presence of routing hole and network partitioning.

A hybrid soft computing-based clustering protocol for wireless sensor networks

In this paper, an inter-cluster data aggregation based on General Self-Organized Tree-based Energy Balance (GSTEB) routing protocol has been improved by proposing energy efficient protocol under hybrid soft computing. First, finest cluster heads are elected by using enhanced ant colony optimization (ACO) method. After that, information which has been gathered by cluster heads is sent to sink node by applying hybrid soft computing (i.e., hybridization of glow swarm and ACOs). Experimental analysis shows that network lifetime has been improved according to the proposed procedure in contrast with already available procedures.

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.

Dynamic Channel Assignment and Gateway Load Balanced Routing for Multi-Channel Wireless Mesh Networks

Dynamic Channel Assignment and Gateway Load Balanced Routing for Multi-Channel Wireless Mesh Networks

A Flip-Flop Based Arbiter Physical Unclonable Function (APUF) Design with High Entropy and Uniqueness for FPGA Implementation

A PUF is a physical security primitive that allows to extract intrinsic digital identifiers from electronic devices. It is a promising candidate to improve security in lightweight devices targeted at IoT applications due to its low cost nature. The Arbiter PUF or APUF has been widely studied in the technical literature. However it often suffers from disadvantages such as poor uniqueness and reliability, particularly when implemented on FPGAs due to physical layout restrictions. To address these problems, a new design known as FF-APUF has been proposed; it offers a compact architecture, combined with good uniqueness and reliability properties, and is well suited to FPGA implementation. Many PUF designs have been shown to be vulnerable to machine learning (ML) based modelling attacks. In this paper, initial tests show that to attack the FF-APUF design requires more effort for the adversary than a conventional APUF design. A comprehensive analysis of the experimental results for the FF-APUF design is presented to show this outcome. An improved APUF design with a balanced routing, and the proposed FF-APUF design are both implemented on an Xilinx Artix-7 FPGA at 28 nm technology. The empirical min-entropy of the FF-APUF design across different devices is shown to be more than twice that of the conventional APUF design.

Energy Efficient SOCGO Protocol for Hole Repair Node Scheduling in Reliable Sensor System

A sensor node in the wireless sensor network (WSN) has an inadequate energy, and it cannot be interchanged due to the arbitrary placement, so the objective is to extend the network lifetime. An inadequate energy becomes a crucial problem to solve energy efficiency in WSN. In this work, we propose a new Self-Organizing Cluster based Greedy best-first search Opportunistic routing (SOCGO) protocol for balanced energy routing. In our proposed work, the operation of work is divided into four stages for energy balanced routing. They are Sleep state, active state, guard state and death state. The residual energy consumed through the examining adjacent nodes is presented as an aspect to estimate the detection rate, and it can achieve through the novel approach named as hybrid K-means and Greedy best-first search algorithm. Furthermore, the presence of coverage holes pairs within WSN can be recovered through an Opportunistic routing algorithm. This method repairs the coverage hole pairs and improves the network lifetime. Then this proposed SOCGO protocol can be implemented in both the homogeneous and heterogeneous environment. Simulation outcomes deliberates that our proposed SOCGO algorithm attains enhanced performance regarding the network lifetime, throughput, energy consumption, average end to end delay and packet delivery ratio.

Autonomous Load Regulation Based Energy Balanced Routing in Rechargeable Wireless Sensor Networks

Recent progress in wireless charging technologies has greatly promoted the development of rechargeable wireless sensor networks (RWSN). The network lifetime of RWSN can be commonly extended through routing strategy and wireless charging technology. However, the node accepts the relay request of its neighbor unconditionally, and it cannot remove its overload on its own in a timely manner in traditional routing strategies. The energy balancing efficiency of the network may be limited by this passive mechanism, which poses a great challenge to obtaining optimal joint efficiency of routing and charging strategies. In this paper, we propose an autonomous load regulation mechanism-based energy balanced routing algorithm (ALRMR) for RWSN. In addition to an efficient framework of joint wireless energy transfer and multi-hop routing where the routing strategy is adapted to the charging scheme, an innovative load regulation mechanism is proposed. Under this mechanism, each node can actively adjust its own load by controlling its relay radius. The simulation demonstrates the advantages of our algorithm for energy balance efficiency and improving the network lifetime through the charging scheme and the innovative mechanism.

Machine Learning Aided Load Balance Routing Scheme Considering Queue Utilization

Due to the rapid development of network techniques, packet-switched systems experience high-speed growth of traffic, which imposes a heavy and unbalanced burden on the routers. Hence, efficient routing schemes are required in order to achieve load balance. By decoupling the control plane and the data plane, Software-Defined Network (SDN) shows its flexibility and extensibility to achieve the automatic management of network resources. Based on the SDN architecture, we propose a pair of machine learning aided load balance routing schemes considering the queue utilization (QU), which divide the routing process into three steps, namely the dimension reduction, the QU prediction, as well as the load balance routing. To the best of our knowledge, it is the first time that principal component analysis (PCA) is used for the dimension reduction of the substrate network. Furthermore, QU prediction is conducted with the aid of neural network algorithms for the sake of coping with the network congestion resulting from burst traffic. Finally, simulation results show that our proposed routing schemes considering QU predicted by the machine learning algorithms outperform the traditional Bellman–Ford (BF) routing strategy in terms of the average packet loss ratio, the worst throughput and the average delay.

Joint Balanced Routing and Energy Harvesting Strategy for Maximizing Network Lifetime in WSNs

Nowadays, wireless sensor networks (WSNs) are becoming increasingly popular due to the wide variety of applications. The network can be utilized to collect and transmit numerous types of messages to a data sink in a many-to-one fashion. The WSNs usually contain sensors with low communication ability and limited battery power, and the battery replacement is difficult in WSNs for large amount embedded nodes, which indicates a balanced routing strategy is essential to be developed for an extensive operation lifecycle. To realize the goal, the research challenges require not only to minimize the energy consumption in each node but also to balance the whole WSNs traffic load. In this article, a Shortest Path Tree with Energy Balance Routing strategy (SPT-EBR) based on a forward awareness factor is proposed. In SPT-EBR, Two methods are presented including the power consumption and the energy harvesting schemes to select the forwarding node according to the awareness factors of link weight. First, the packet forwarding rate factor is considered in the power consumption scheme to update the link weight for the sensors with higher power consumption and mitigate the traffic load of hotspot nodes to achieve the energy balance network. With the assistance of the power consumption scheme, hotspot nodes can be transferred from the irregular location to the same intra-layer from the sink. Based on this feature, the energy harvesting scheme combines both the packet forwarding rate and the power charging rate factors together to update the link weight with a new battery charging rate factor for hotspot nodes. Finally, simulation results validate that both power consumption and energy harvesting schemes in SPT-EBR achieve better energy balance performance and save more charging power than the conventional shortest path algorithm and thus improve the overall network lifecycle.

Delay-Based Routing Mechanism for Load Balanced Routing in Wireless Mesh Networks

Delay-Based Routing Mechanism for Load Balanced Routing in Wireless Mesh Networks

Adaptive Energy Balanced Routing Strategy for Wireless Rechargeable Sensor Networks

The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing process. To balance the network energy in charging part, node’s charging efficiency is balanced by dynamically planning charging point positions and the charging time is allocated according to the energy consumption rate of nodes. Moreover, the routing method is adapted to the node’s charging efficiency. The adaptive routing strategy assigns more forwarding tasks to nodes that can get more energy during the charging phase, and makes the data packets transmit farther away, thus reducing the average hops and energy consumption of the network. Finally, the simulation results reveal that the proposed algorithm has certain advantages in prolonging the network lifetime, reducing the average hop counts and balancing the energy of each node.

Energy Consumption Balanced Topology Variable Routing Algorithm for WWSN in Disaster Rescue Scenarios

In recent years, the Wearable Wireless Sensor Network (WWSN) has become one of the most popular networks used in disaster and emergency scenarios. We propose a routing algorithm named Energy Consumption Balanced Topology Variable (ECB-TV) on the body of users in WWSN. In the ECB-TV algorithm, network topology can be variable according to the change of network state. A multi-hop topology is used in normal situation and the network will switch to single-hop topology at once when an abnormal event happens. We also design a novel multi-hop routing algorithm for multi-hop topology where we select the node with the highest energy balance factor as next hop node. Energy balance factor is innovatively designed by simultaneously taking into account both energy consumption of transmitting and receiving nodes, which can balance the energy consumption of sensor nodes well. The simulation results show that the proposed ECB-TV algorithm has better performance in terms of lifetime in normal situations and delay in abnormal situations.

$$E^{2} SR^{2}$$ E 2 S R 2 : An acknowledgement-based mobile sink routing protocol with rechargeable sensors for wireless sensor networks

The advances in hardware manufacturing technologies and wireless communications enabled the evolution of tiny, multi-functional, low-power and resource constrained sensor nodes (SNs) for wireless sensor networks (WSNs). SNs located in sinks vicinity, deplete their batteries quickly because of concentrated data traffic near the sink, leaving the data reporting wrecked and disrupted. In order to mitigate this problem, mobile sinks are introduced that provide uniform energy consumption and load balanced data delivery through the sensor network. However, advertising the mobile sinks position information brings forth additional overhead in terms of energy wastage. Recently, an energy-efficient distributed mobile sink routing protocol named ring routing has been proposed aiming to mitigate the introduced overhead. In this present work, we propose an Energy Efficient Secured Ring Routing ($$E^{2} SR^{2}$$E2SR2) protocol which is an enhancement of existing ring routing protocol [62] that considers rechargeable sensors to be deployed in the sensing region and employs Maximum Capacity Path (MCP), a dynamic load balanced routing scheme for load balancing and prolonging the networks lifetime. Furthermore, we use 2ACK scheme that serves as an efficient mechanism for detecting the routing misbehaviour and simultaneously enhance the security. Finally, the proposed protocol was simulated by varying the sink speed for similar node deployments and the results obtained confirm that the proposed $$E^{2} SR^{2}$$E2SR2 achieves improved performance than the existing protocols such as LBDD (Line Based Data Dissemination), rail road and ring routing.

Adaptive Load Balancing Ad Hoc Routing Scheme Inspired by True Slime Mold

Engineering neo-biomimetics, i.e. imitation models based on body structures and behavior of living organisms, relied upon to solve complex problems, have been studied in various fields. In distributed networks, such as ad-hoc networks and wireless sensor networks, the behavior of a variety of true slime molds which are capable of constructing multipath flow networks based on the amount of body, has been studied. Ad hoc networks only consist of mobile terminals (nodes) that can relay packets along an established route. However, link relations and the available bandwidth of the nodes change dynamically due to the mobility of nodes. In addition, the speed of communication between nodes also varies due to node positions and their communication-related quality. Thus, practical use of ad-hoc networks still remains an issue, because it is difficult to establish stable routes under such environments. This study aims to propose an adaptive load balancing routing technique that adaptively diversifies the transmission paths based on the available bandwidth, residual battery life, and the data transmission volume, by applying a mathematical model of slime mold routing, known as the physarum solver. We confirm the effectiveness of its adaptive behavior in dynamic environments using computer simulations.