Hop Count Research Articles

Cross-Layer Based QoS Aware Load-balancing Multi-Path Routing Protocol over Wireless Multimedia Sensor Networks

Abstract: Currently, the utilization of WMSNs in different real-time and non-real-time applications requires an excessive amount of bandwidth for reliable data delivery. The unique features of WMSNs are significantly challenging in satisfying the QoS requirements in such application-specific environments and balancing the traffic load among the devices. The provision of reliable multipath routing is a cornerstone in fulfilling the QoS requirements of WMSNs. Selecting multiple optimal paths between a source and destination based on peculiar routing metrics enhances the performance of QoS routing. Generally, routing protocols exploit several routing metrics, such as delay, remaining energy of nodes, hop count, available bandwidth, and packet loss rate in path selection to attain high reliability in data delivery. Many existing routing protocols only consider the network layer parameters, whereas it lacks focus on the data link and physical layer parameters, which creates a severe impact on the degradation of QoS. In addition to that, varying bandwidth channels create interference in multimedia data delivery and degrade the network performance. Designing a multipath routing protocol by considering cross-layer parameters offer a promising solution to optimize the WMSN performance. In cross-layer design, diverse protocol layers support the routing decisions adaptively by perceiving the dynamic characteristics of the wireless medium, resulting in fair use of scarce resources with high QoS. A Cross-Layer Based QoS Aware Load-Balancing Multipath Routing Protocol over Wireless Multimedia Sensor Networks was the goal of the study's five design objectives. The study and analysis of QoS and cross-layer-based routing algorithms for WMSNs was the initial goal. Secondly, a Deep Learning prioritization-based packet classifier to divide traffic according to priority. To ensure fair resource consumption and distribution of multimedia traffic, the third goal was to design and create a cross-layer optimizer model for optimal multiple disjoint route selection using machine learning techniques. The development of a cutting-edge channel-scheduling algorithm was goal four. It was designed to efficiently assign low-interference channels to communication devices in order to lower the packet drop rate in real-time packet delivery. Last but not least, a security method for Wireless Multimedia Sensor Networks' Cross-Layer based multipath routing protocol.

Introducing a new routing method in the MANET using the symbionts search algorithm.

A wireless MANET network is a grouping of wireless nodes that communicate without the use of a centralized network infrastructure. The lack of reliable elements, such as routers, as well as severe resource constraints, have an important impact on the performance of these networks. To improve the efficiency of MANET, intelligent routing algorithms are required; in fact, the design of a smart and efficient routing algorithm can significantly affect the efficiency of these networks. In this regard, this paper proposes an intelligent routing method for MANET networks based on (SOS) symbiotic organism search. The proposed method is implemented in dynamic environments by considering four important criteria: available bandwidth, remaining battery energy, mobility speed, and hop count. The simulation results show that the learning process of the symbionts search algorithm has a significant impact on network performance and outperforms the FBRP algorithms in terms of throughput rate, data loss rate, packet delivery rate, and the number of hops.

RETRACTED ARTICLE: Privacy-preserving routing using jointly established protocol in IoT network environment

In this paper, network energy assesses the capacity of a node to convey messages to others. In most cases, network energy is created when two nodes interact with one another. If a node is part of the same network as the node it is connecting with, then it will be able to make an inter-network energy connection with the node it is meeting. In the case that this does not take place, there will be an accumulation of energy within the part of the network that is facing the node. A node with higher inter-network energy is considered suitable for forwarding. The energy optimisation is achieved using efficient identification of source and destination pairs. This work has considered two scenarios, i.e. lossless transmission and lossy transmission, for our experiments and evaluated the detection probability. The performance of the proposed PPM is evaluated in terms of delivery ratio, overhead and hops count performance measures. When the buffer size is set to 100 MB, PPM delivers 59% of messages with message overhead of 750 and it has a hop count of 2, which is comparable to the state-of-the-art methods. With lengthy lifetimes of IOT networks, PPM is capable of giving higher performance while maintaining the privacy of network. The detection probability for the lossy observations model is applied to a 10-node, 20-node, 30-node and 40-node IoT network.

Innovative DMHS Algorithm Application in Wireless Sensor Networks for Efficient Routing in High-Risk Environments.

Efficient routing is essential for the proper functioning of wireless sensor networks (WSNs). Recent research has focused on optimizing energy and delay for these networks. Nevertheless, there is a dearth of studies that have examined the effects of volatile settings, such as chemical plants, coal mines, nuclear power plants, and battlefields, where connectivity is inconsistent. In such contexts, sensor networks may face security incidents, and environmental factors such as node movement and death can result in dynamic changes to the network topology. A novel design algorithm grounded on Dynamic Minimum Hop Selection (DMHS) was introduced in this paper. The key principle behind DMHS is to use a probabilistic forwarding decision-making process through a distributed route discovery strategy that utilizes dynamically adjusted minimum hop counts of nodes. Simulation results indicate that the life cycle of the DMHS algorithm increases by more than 12% over 700 nodes when compared to the traditional energy-saving algorithm. Furthermore, our algorithm performs better in the average delivery rate of node, and has a 10% to 21% improvement compared to the other algorithms. Overall, the DMHS algorithm represents an important contribution to the development of WSNs that can function robustly in high-risk and unstable environments.

Energy-Efficient Opportunistic Routing Algorithm for Post-Disaster Mine Internet of Things Networks.

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables a user to monitor and control the safety of an affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in a low level of network reliability for the post-disaster MIoT. To improve transmission reliability and reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) approach for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in the CFS are prioritized based on a routing quality evaluation, which takes the local attributes of the nodes, such as the directional angle, transmission distance, and residual energy, into consideration. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results verify that the proposed DEOR approach outperforms the ORR, OBRN and ECSOR methods in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

Study on the wireless sensor networks routing for Low-Power FPGA hardware in field applications

Very intelligent compact sensors with low-power and inexpensive solutions have been created because of the industrial revolution and subsequent advancements in electrical technology and wireless communications. Modern innovative enhancements have been made for the utilization of small, low-price, and low-power wireless communication devices with fast processing capabilities. The sensor node communication and routing play a significant role in the configuration of a specific WSN environment. There are three types of WSN routing: proactive, reactive, and hybrid. DSDV and OLSR are two proactive routing technologies. AODV and DSR are reactive routing technologies. DSDV Routing requires a progress update of its routing tables even when the network is not in use, which uses battery power and generates negligible data. As a result, this protocol is inappropriate for networks that are both huge in scope and very dynamic. OLSR maintains track of all potential solutions in a routing table. The overhead from control messages rises as there are more mobile hosts. It requires more processing power than other protocols while looking for alternate routes. The DSR protocol relies on the minimal hop count parameter to pick the way without considering other parameters that impact routing algorithm performance, such as energy consumption, residual energy, and connection stabilities. The FPGA realization provides an ascendable computing environment for WSN planning in a specific region. The research articles emphasize the hardware chip simulation and analysis of these routing protocols which can be further applied for field applications and configuration The network performance is evaluated using several performance metrics such as throughput, control overhead, delay, packet delivery ratio, and power consumption. This study offers a key method for creating FPGA-based power estimation and verification models for a WSN planning environment.

An auction-based distributed network slicing scheme for resource allocation in satellite-UAV integrated networks

Network slicing is a promising solution to satisfy different service quality requirements in the satellite-UAV integrated network of B5G and 6G. To relieve the significant transmission delay and system overhead during network slicing, we propose an auction-based distributed network slicing scheme (ADNSS), in which the resource allocation is collaboratively performed by satellite heads using an auction algorithm without transmitting the messages to the ground station in a centralized way. The convergence and service delay performance of ADNSS is analyzed in this paper. Moreover, considering that the deviation of theoretical slice analysis models from actual ones may lead to the degradation of service delay performance of ADNSS, we design an online optimization method driven by the multi-arm bandit algorithm (ORLOM) to enhance the accuracy of slice models of ADNSS in the actual environment. Numerical results show that we can achieve optimal service delay performance by ADNSS applying ORLOM after finite slicing windows and realize 8% performance improvement compared with ADNSS without ORLOM when the service number is 9. In addition, ADNSS can reduce the system overhead by 8.5%–76% compared with the centralized method in the scenario where the hops count from satellite heads to the ground station exceeds that between satellite heads by 3. As the hops count difference and service number increase, ADNSS shows more significant advantages in reducing service delay and system overhead.

SoftCaching: A framework for caching node selection and routing in Software-Defined Information Centric Internet of Things

A considerable demand for Internet of Things (IoT) services is causing exponential growth in Internet traffic. Software-Defined Networking (SDN) and Information-Centric Networking (ICN) are complementary technologies for IoT services provisioning that reduce network traffic and service provisioning delays by caching content at intermediate nodes in the network. Existing research on Software-Defined Information-Centric Networking (SDICN) for IoT service provisioning suffers from two major challenges: (a) optimal caching node selection and (b) optimal path computation from content consumers to caching nodes based on end-to-end delay and link utilization constraints. We propose a SoftCaching framework that optimizes caching node selection for content publishers and computes the optimal routing path to caching nodes for content consumers. It computes optimal locations for caching nodes and finds optimal routing paths for IoT services to access cached content. SoftCaching analyzes network traffic on all nodes in the network and collects traffic metrics. It estimates the best possible caching nodes by using Waypoint Enforcement (WPE) and solving the traffic matrix using Singular Value Decomposition (SVD) and QR Factorization. WPE and SVD-based QR factorization provide optimal locations to cache the content for IoT services. Subsequently, SoftCaching uses a constraint-based shortest path algorithm to compute the optimal routing path from content consumers to caching nodes. We make sure that the caching node and the routing path selection follow delay and link utilization constraints. We perform extensive experiments for evaluation, and the results show that SoftCaching outperforms state-of-the-art caching schemes in terms of delay, link load, hop count, path stretch, and energy consumption metrics.

A social relationship-based energy efficient routing scheme for Opportunistic Internet of Things

Opportunistic Internet of Things (OppIoT) combines Opportunistic Networks and the Internet of Things to provide opportunistic communication between IoT devices and human-created communities in order to improve network connectivity, reliability, and longevity. This is significant because it introduces a new approach to connect and communicate smart devices in situations where there is no end-to-end connectivity. Due to the non-stable existence of connectivity between nodes, building a scalable, flexible, interoperable, and energy efficient routing protocol is a difficult issue. This study presents a new routing protocol for the Opportunistic Internet of Things called Social relationship based Energy Efficient Routing (SEER), which bases routing decisions on the forwarding feasibility degree, residual energy, and buffer capacity of nodes. SEER surpasses EBR and EDR in terms of delivery probability, hop count, and overhead ratio, according to simulation results utilizing the Opportunistic Network Environment (The ONE) simulator.

AODV-EOCW: An Energy-Optimized Combined Weighting AODV Protocol for Mobile Ad Hoc Networks.

The Ad Hoc On-demand Distance Vector (AODV) is a routing protocol for mobile ad hoc networks (MANETs) and other wireless ad hoc networks. The vanilla AODV protocol is simple and easy to implement because it only uses the hop count as a routing metric. Single-metric route determination also causes problems, such as network congestion and energy exhaustion, which limit the usage of AODV in resource-limited applications. To solve these problems, the authors propose a new routing protocol that combines the analytic hierarchy process (AHP), the entropy weight method (EWM), and AODV. The proposed protocol uses energy, congestion, and the hop count as metrics and weights these three metrics using AHP and EWM. To address the importance of energy in applications, such as drones, the proposed protocol chooses different comparison matrices for AHP at different node residual energy levels. Finally, the node chooses the best route link according to the score (sum of weighted metrics). It is also suitable for wireless sensor networks because the proposed protocol considers the residual energy of the node. The simulation results show that the improved routing protocol can effectively reduce the average end-to-end delay and energy consumption and prolong the lifetime of the whole network.

Contextual Cluster-Based Glow-Worm Swarm Optimization (GSO) Coupled Wireless Sensor Networks for Smart Cities.

The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH's routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network's lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique's throughput and energy efficiency.

Hybrid routing protocol for quantum network based on classical and quantum routing metrics

A quantum repeater is the heart of a quantum internet that enables end-to-end communication over long distances using the quantum entanglement feature. Although this characteristic gives quantum networks tremendous power in terms of speed and security, it puts quantum networks, especially the quantum internet, in front of challenges, like transforming a short-distance quantum link into a long-distance link, in addition to entanglement routing for finding the best path within a quantum network. So, this research aims to propose a hybrid quantum routing protocol (HQRP) based on routing metrics of the classical networks like hops count, as well as metrics of the quantum network represented by the possibility of entanglement between end nodes in the network. As a result, a mathematical model was built to determine the optimal path among many paths within the quantum network, and it was implemented on our quantum network simulator. Finally, we concluded that the proposed algorithm gives the optimal path based on the highest entanglement probability and lowest number of hop count.

Analysis of Greedy Strategies in Geographic Routing of VANETs

The study and creation of networks that are independent of any pre-existing infrastructure has become highly popular in recent years. These networks fall under the category of Vehicular Ad-hoc Networks (VANETs), in which each car takes part in routing by sending data to other vehicles. However, geographic routing attracts VANETs networks because they lack route discovery and routing databases and the accessibility of low-cost GPS systems as well as the advent of the 128-bit address structure of IPv6 have enhanced the advantages of geographical routing over classical routing techniques. Additionally, the proposed algorithms based on greedy routing are the main method for the next hop selection in multi-hop communication for optimal and optimized solution in geographic routing. In this article, the study takes place with a number of hops per route and greedy algorithm selection success ratio in VANETs with source-to-destination pairs. A comparative study is taken out in which LLP affects node density, hop count, and transmission range. Monte Carlo simulations have been done with two important network parameters which are transmission range and node density. This study will be a guideline for the choice of greedy decisions to meet the objectives of network applications.

Performance Analysis of Energy Efficiency and Security Solutions of Internet of Things Protocols

The scientific and business communities are showing considerable interest in wireless sensor networks (WSN). The availability of low-cost, small-scale components like CPUs, radios, and sensors, which are often combined into a single chip, is crucial. Parallel to the evolution of WSNs, the concepts of the IoT have been evolving in recent years. Wireless communication technologies may play a significant role in the implementation of IoT, despite the fact that IoT does not need or require any particular technology for communication. WSN assisted IoT networks can drive several applications in many industries. The proposed research explores the possibility of enhancing energy efficiency in WSN-assisted IoTN by balancing various challenging sensor network performance metrics. The base station's current placement inside the sensing field is predetermined by the preexisting routing algorithms. Our study examines the impact of base station placement outside and within the prescribed sensing domains on energy consumption and network longevity. In addition, methods for transferring data from the distributed source sensor to the base station while minimizing energy consumption are investigated. In this preliminary study, we focus on developing an algorithm for WSN-Assisted IoTN that can balance network factors such as hop count, communication distance, and residual energy. To further optimize the routing route between local cluster heads and the base station, a novel network architecture is built based on the Ant-optimization model, which uses centroid routing to balance energy consumption among local clusters. An open-source Network Simulator (NS-3) is used to model the behaviour of the proposed routing protocols and compare them to comparable existing network protocols. All of the suggested protocols have the same fundamentals for creating networks, however they vary in terms of routing, optimization, and performance depending on the development effort under consideration.

A Novel Energy-Efficient Reservation System for Edge Computing in 6G Vehicular Ad Hoc Network.

The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%.

FMap: A fuzzy map for scheduling elephant flows through jumping traveling salesman problem variant toward software‐defined networking‐based data center networks

SummaryNowadays data center networks (DCNs) should handle the ever‐growing load generated by diverse applications. It particularly occurs under concurrent flow requests and so‐called mice flows (MFs): elephant flows (EFs) ratio. Concentrating on a binary vision over flow size classification (EF or MF) results in subsequent unpredicted load imbalance due to neglecting EF's distinctions including a wide range of sizes. As a result, some EFs might utilize a path owing qualities beyond the given EF's demands, while another EF with higher requirements is attending to use an over‐utilized path. This article proposes FMap, a fuzzy map for scheduling EFs through our proposed variant of traveling salesperson problem (TSP) toward DCNs. FMap represents a novel EF scheduling scheme that integrates flow prioritization and routing decisions under the event pf parallel incoming flows besides the cooperation of the controller and OpenFlow switches in software‐defined networking (SDN) paradigm. FMap adopts fuzzy inference process to overcome the vagueness over EF's resource allocation. Mainly, FMap proposes a new variant of TSP (optimized by genetic algorithm) which enables EF's group forwarding with a minimum cost. FMap reduces the total hop count of EFs through considering a single optimal path for delivering groups of EFs that contain a same tag (priority). The outstanding results represent a major improvement as compared with equal cost multiple path, Hedera, Sonoum, and Size‐KP‐PSO. Particularly, the results illustrate an outperforming by 3.76×, 0.21×, 0.15×, 0.03×, and 0.03× in terms of total hop count, EFs FCT, packet loss, goodput, and received packets as compared with Size‐KP‐PSO, respectively.

Exploring the effects of directional antennas on the secure connectivity and hop count of secure multi-hop ad-hoc wireless networks

Directional antennas can increase the received power in specific directions while reducing it in other directions. Utilizing this unique feature, we configure directional antennas at legitimate users to obtain twofold benefits for secure multi-hop ad-hoc wireless networks (AHWNs), i.e., enhancing the secure connectivity among legitimate users and lowering the hop count of the multi-hop paths. For the quantitative evaluation of these benefits, we first use a stochastic geometry graph to model the multi-hop AHWNs under the coexistence of eavesdroppers. Then, we introduce a simulation-based analysis method comprised of two algorithms: (a) the first algorithm provides the connectivity and the hop count of the shortest path between random source–destination pairs; (b) the second algorithm utilizes the results of the first one to return the average path connectivity, the probability mass function (pmf) of the hop count distribution, and the average hop count. This simulation-based analysis method helps to exhaustively study the behaviors of connectivity, hop count distribution, average hop count, and their mutual relationship in different scenarios. To the best of our knowledge, this paper is the first research work that studies the effects of directional antennas equipped at legitimate users on both secure connectivity and hop count of secure AHWNs in four combinations of two types of practical directional antennas, i.e., uniform circular array (UCA) antenna and uniform linear array (ULA) antennas, and two beamforming schemes, i.e., centralized and randomized beamforming. Moreover, comparisons with the case of using omnidirectional antennas are also provided. From the obtained simulation results, we demonstrate that using directional antennas does not always benefit the secure connectivity and hop count of secure AHWNs, i.e., only UCA-random gives higher secure connectivity and lower hop count than the omnidirectional antenna among four combinations of antenna type — beamforming scheme. Moreover, in the cases of high-density legitimate users and low-density eavesdroppers, lowering the average hop count is more remarkable than improving secure connectivity. The critical findings in this paper are valuable for deploying secure multi-hop AHWNs with directional antennas in practice.

BBSF: Blockchain-Based Secure Weather Forecasting Information through Routing Protocol in Vanet.

A vehicular ad hoc network (VANET) is a technique that uses vehicles with the ability to sense data from the environment and use it for their safety measures. Flooding is a commonly used term used for sending network packets. VANET may cause redundancy, delay, collision, and the incorrect receipt of the messages to their destination. Weather information is one of the most important types of information used for network control and provides an enhanced version of the network simulation environments. The network traffic delay and packet losses are the main problems identified inside the network. In this research, we propose a routing protocol which can transmit the weather forecasting information on demand based on source vehicle to destination vehicles, with the minimum number of hop counts, and provide significant control over network performance parameters. We propose a BBSF-based routing approach. The proposed technique effectively enhances the routing information and provides the secure and reliable service delivery of the network performance. The results taken from the network are based on hop count, network latency, network overhead, and packet delivery ratio. The results effectively show that the proposed technique is reliable in reducing the network latency, and that the hop count is minimized when transferring the weather information.

Routing and Resource Scheduling for Air-Ground Integrated Mesh Networks

Due to the advantage of achieving scalable connectivity and low-latency communications, air-ground integrated mesh networks (AGIMNs) will play an important role in the next generation wireless communication systems. However, due to the heterogeneous character of AGIMNs, it is challenging to manage the network and optimize the communication resources for improving the end-to-end (E2E) performance. Therefore, in this paper, we study a joint routing and time-frequency resource scheduling problem aiming at minimizing the total weighted E2E delay for heterogeneous AGIMNs. To capture the features of this complex system, we mathematically model the network constraints and formulate an optimization problem. To solve the original nonconvex problem, a suboptimal solution is proposed. First, we propose an optimal minimum-weight routing method, in which the hop count, conflict delay, and contention delay are taken into consideration. Then, we transform the time-frequency resource scheduling subproblem into a series of tractable problems for maximizing the number of active links through channel assignment in successive time slots. Finally, the successive convex approximation (SCA) technique is utilized to solve the channel assignment problem per time slot. Extensive simulation results show the performance superiority of the proposed solution compared to the benchmarks in terms of the total E2E delay.

TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making

The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay.