Load Balancing Routing Algorithm Research Articles

Load-balancing routing algorithms for service congestion avoidance in LEO optical satellite networks

The low-Earth-orbit optical satellite network (LOSN) is an attractive solution to realize the end-to-end service quality of large-scale services, and it is the basis of establishing the 6G mobile network with high throughput and high reliability. However, the current LOSN is practically unable to achieve such high throughput for global service access. First, the centralized deployment of ground gateways will cause a heavy traffic load in the space segment of the LOSN, which becomes the bottleneck constraining the further growth of network throughput. Second, the high-speed movement of LEO satellites will cause continuous movement of traffic load, which will affect the scalability of routing computing. In this paper, two routing algorithms are proposed to increase the throughput in the dynamic LOSN topology. The congestion-aware load balancing (CALB) algorithm is proposed to address the inter-satellite link congestion in the dynamic LOSN topology. Then, a load-balancing routing algorithm based on satellite–ground cooperation (SGC-LB) is proposed to further reduce the impact of the network bottleneck. To evaluate the performance of the proposed routing algorithm, extensive simulations were performed on a 288-satellite Walker-Star constellation with inter-satellite links. The service blockage rate and network bandwidth utilization rate are evaluated showing the effectiveness of the proposed routing algorithm. The network using the SGC-LB algorithm can accommodate 60.00%, 56.00%, 42.22%, and 33.33% more services than using the Shortest Path algorithm, Sway algorithm, CALB algorithm, and Anycast algorithm, respectively, with zero service congestion during the simulation. The SGC-LB also gains a 6.04%, 5.00%, 5.04%, and 0.77% higher network utilization rate than the Shortest Path, Sway, CALB, and Anycast algorithms, respectively.

A Load Balance Routing Algorithm for Medical IoT Based on Link Quality

A Load Balance Routing Algorithm for Medical IoT Based on Link Quality

Adaptive Load Balancing for Dual-Mode Communication Networks in the Power Internet of Things

As an important part of the power Internet of Things, the dual-mode communication network that combines the high-speed power line carrier (HPLC) mode and high-speed radio frequency (HRF) mode is one of the hot directions in current research. Since non-uniform transmission demands for power consumption information can lead to link congestion among nodes, improving the network load-balancing performance becomes a critical issue. Therefore, this paper proposes a load-balancing routing algorithm for dual-mode communication networks, which is achieved in dual-mode communication networks by adding alternate paths and proxy coordinator (PCO) node election mechanism. Simulation results show that the proposed algorithm achieves the load-balanced distribution of power consumption information transmission. The proposed scheme reduces the delay and packet loss rate, as well as improving the throughput of dual-mode communication compared to existing routing algorithms.

DRL-Based Load-Balancing Routing Scheme for 6G Space–Air–Ground Integrated Networks

Due to the rapid development of the space–air–ground integrated network (SAGIN), a satellite communication system has the advantages of wide coverage and low requirements for a geographical environment and is gradually becoming the main competitive technology for 6G. The low-earth-orbit (LEO) satellite network has the characteristics of low transmission delay, small propagation loss, and global coverage, and its exploration has become the main research object of contemporary satellite communications. However, traditional routing algorithms cannot adapt to the characteristics of the high dynamics and load-balancing requirements of LEO satellite networks. In this paper, a load-balancing routing algorithm for LEO satellites based on Deep Q-Network (DQN-LLRA) is proposed by using deep reinforcement learning. Making use of the model obtained by the DQN training, satellite nodes can select the best routing results according to the delay, bandwidth, and queue utilization of the surrounding satellite nodes. The simulation and analysis show that the path load obtained by the proposed algorithm is low. Compared with the Q-learning-based algorithm, this algorithm reduces the maximum queue utilization rate of the routing path by 5%, reduces the average queue utilization rate of the routing path by 13%, and effectively balances the load in the network.

An improved non-local awareness of congestion and load balanced algorithm for the communication of on chip 2D mesh-based network

Due to advancements in multi-core design technology, IC (Integrated Circuits) designers have expanded the single chip multi-core design. A privileged way of communication effectively between these multi-cores is a Network on-chip (NoC). Design of an effective routing algorithm capable of routing data to non-congested paths is the most notable research challenge in NoC, by retrieving congestion information of non-local nodes. This research proposed an improved congestion-aware load balancing routing algorithm. Non-local or distant links congestion awareness is done by propagating congestion information via data packets. By counting number of hops from the source node, in the quadrant of the destination node, an intermediate node has been defined, and after the calculation of the least congested route to the intermediate node, this route is also stored in the data packet for source routing. Furthermore, for load balancing network is partitioned into two areas called high congested area (HCA) and low congested area (LCA). For load balancing, from HCA a node in LCA is selected as output for data packets. Comparison of the proposed algorithm is done in the form of average latency, average throughput, power consumption, and scalability analysis under synthetic traffic patterns. Under simulation experiments, it is shown improvement in an average latency and throughput of the proposed algorithm is 31.28% and 5.28% respectively, than existing.

$$\tt F_{K-means}RA$$: Fuzzy K-Means Clustering Routing Algorithm for Load Balancing in Wireless Sensor Networks

$$\tt F_{K-means}RA$$: Fuzzy K-Means Clustering Routing Algorithm for Load Balancing in Wireless Sensor Networks

An evolutionary routing protocol for load balancing and QoS enhancement in IoT enabled heterogeneous WSNs

Energy awareness is a key concern of recent advances in the Internet of Things (IoT) enabled wireless sensor networks (WSNs), and many optimization approaches to reduce energy consumption have been proposed. The most widely used routing technique for achieving energy efficiency in WSNs is the clustering hierarchy. Data transmission over long distances has a negative impact on network efficiency in terms of stability period, network lifetime, and QoS due to the selection of inadequate Cluster Heads (CHs). This paper describes a new Evolutionary Gateway-based Load-Balanced Routing (E-GLBR) algorithm for efficiently selecting appropriate CHs. The proposed algorithm is based on the genetic algorithm optimization method with a new fitness function that takes into account four major parameters to achieve the following goals: improving the CH selection process, reducing energy transmission range, increasing network stability and lifetime, and improving WSN coverage. A comparison simulation with the most recent related methods in MATLAB simulator is performed to evaluate the performance of our proposed algorithm. The simulation findings demonstrate that applying the developed evolutionary approach reduces the network’s energy consumption rate and increases the wireless network throughput. In various network scenarios, our suggested approach surpasses all other examined methods, extending the network coverage and prolonging the stability periods of Evolutionary Routing Protocol (ERP), Energy-Efficient Weighted Clustering (EEWC), Distance Incorporated Modified Stable Election Protocol (D-MSEP), and Energy dependent cluster formation (EDCF) by 55%, 43%, 26%, and 12% respectively.

Secure Energy-Efficient Load Balancing and Routing in Wireless Sensor Networks With Mediative Micro-ANN Fuzzy Logic

The security and life time of network are most import factors in wireless sensor networks (WSN). In this research work Mediative Micro ANN Fuzzy logic(MMAFL) has been proposed, along with load-balance routing algorithm. The designed method can increase WSN’s additional feature like securing packet from message capture and tampering attacks. The aim of the proposed routing algorithm is reduce the overall energy consumption and ensure fair use of node energy, so that lifetime of the network has been automatically increased. Experimentation of the proposed Mediative Micro ANN Fuzzy logic is implemented in MATLAB 2018b software and compared with the existing techniques to prove the effectiveness of the approach. The MMAFL model is most useful for medical, Mobile, and industrial applications for data transferring and network security. The performance measures like accuracy 97.45%, F measure 97.34%, overhead 11.10%, delay 8.96ms, throughput 90%, lifetime 27%, and packet-delivery ration 86.11% had been attained, which are most prominent compared to earlier models.

SDN‐based load balance routing mechanism for Information Centric Networking

With the increasing requirements of Information Centric Networking (ICN) on high bandwidth, low delay and high fault tolerance, more and more ICN networks begin to adopt the hierarchical topology. The hierarchical topology based on ICN can establish multiple equivalent paths between any two servers in different locations, resulting in high bandwidth, high throughput and high error tolerance. However, the traditional routing algorithm can not give full play to the performance improvement brought by the hierarchical structure, which will cause a great waste of bandwidth. Therefore, this paper studies a load balancing routing algorithm of ICN based on Software Defined Network (SDN). It relies on SDN controller to obtain the global information of ICN and make the optimal load balancing routing decision, so as to reduce the probability of network congestion and improve the bandwidth utilization.

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Satellite networks can provide a wider service range and lower delay than traditional terrestrial optical fiber networks. However, due to the bursty characteristic of the Internet traffic and the distributive feature of satellite links, traffic-intensive areas often suffer from link congestion while links in other areas are underutilized, i.e., the traffic imbalance problem in LEO satellite networks. In this paper, an ant colony optimization routing algorithm with window reduction for LEO satellite networks, ACORA-WR, is proposed to achieve load balancing. ACORA-WR limits the movement of the ant colony to a specific range and comprehensively considers the path distance, transmission direction, and link load to find a path with low delay and overhead. Simulation results verify that the proposed ACORA-WR scheme demonstrates high data delivery ratio and network throughput, while ensuring low average delay and network transmission overhead.

Load balancing routing algorithm based on extended link states in LEO constellation network

As an important part of satellite communication network, LEO satellite constellation network is one of the hot research directions. Since the nonuniform distribution of terrestrial services may cause inter-satellite link congestion, improving network load balancing performance has become one of the key issues that need to be solved for routing algorithms in LEO network. Therefore, by expanding the range of available paths and combining the congestion avoidance mechanism, a load balancing routing algorithm based on extended link states in LEO constellation network is proposed. Simulation results show that the algorithm achieves a balanced distribution of traffic load, reduces link congestion and packet loss rate, and improves throughput of LEO satellite network.

Load Balancing Routing Algorithm of Low-Orbit Communication Satellite Network Traffic Based on Machine Learning

Satellite communication has become an important research trend in the field of communication technology. Low-orbit satellites have always been the focus of extensive attention by scholars due to their wide coverage, strong flexibility, and freedom from geographical constraints. This article introduces some technologies about low-orbit satellites and introduces a routing algorithm DDPG based on machine learning for simulation experiments. The performance of this algorithm is compared with the performance of three commonly used low-orbit satellite routing algorithms, and a conclusion is drawn. The routing algorithm based on machine learning has the smallest average delay, and the average value is 126 ms under different weights. Its packet loss rate is the smallest, with an average of 2.9%. Its throughput is the largest, with an average of 201.7 Mbps; its load distribution index is the smallest, with an average of 0.54. In summary, the performance of routing algorithms based on machine learning is better than general algorithms.

An Indoor Positioning and Prewarning System Based on Wireless Sensor Network Routing Algorithm

One of the most important means to position abnormal devices is to efficiently utilize the resources of wireless sensor network (WSN) and make proper analysis of the relevant data. Therefore, this paper constructs an indoor positioning and prewarning system that utilizes energy efficiently and achieves a long lifecycle. Firstly, the adjacent round iteration load balancing (ARILB) routing algorithm was proposed, which elects the cluster heads (CHs) by the adjacent round strategy. In this way, the random components were eliminated in CH election. Next, a short-distance multifrequency routing strategy was constructed between CHs to transmit the information to the sink, and a positioning algorithm was designed called ARILB-received signal strength (RSS). The ARILB-RSS positioning algorithm traverses the triangles formed by anchor nodes, forming multiple sets of ranging points; then, the optimal anchor node is recorded, and the path loss factor is iterated to reduce the positioning error. Simulation shows that the network survives 54.5% longer using ARILB than using the distributed energy-efficient clustering (DEEC) algorithm; the packet delivery rate using ARILB was about 139% higher than that of low energy adaptive clustering hierarchy (LEACH) algorithm and 35% higher than that of uneven clustering routing algorithm based on chain-cluster type (URCC) algorithm; ARILB-RSS reduced the ranging error by 14.31% and then the positioning error by 26.79%.

Inter-satellite load balancing routing algorithm for LEO satellite constellation based on regional-traffic-detour

Inter-satellite load balancing routing algorithm for LEO satellite constellation based on regional-traffic-detour

Optimization of load balancing routing algorithm based on extended localized link states in low earth orbit satellite networks

SummaryIt has been observed for a long time that there exists a conflict between the un‐uniform terrestrial traffic distribution and the regular satellite deployed in low earth orbit (LEO) satellite networks. This can result in the link congestion in some areas and the network performance degradation. Load balancing routing is an effective method to solve this problem. This paper discusses the optimization of this kind of routing algorithms and focuses on the local optimization problem due to the routing decision based on localized link states. The extended localized link state load balancing routing algorithm (LB‐ELS) is proposed. It makes use of the path congestion states to determine routes avoiding the local optimization and reduces the overhead by the on‐demand route computing and link congestion state exchange mechanism. The triggered local congestion notification mechanism (TLCN) is also presented, which ensures the timely response to the burst traffic changes and further alleviation of the traffic gathering in congestion links. Simulation results show that this algorithm can disperse the traffic better and improve the network performance greatly with an acceptable delay increase and a small overhead.

Load-balanced routing algorithm for Network-on-Chip employing fair arbiter

Balanced load is one of the most important performance metrics for on-chip communication. To design flexible, adaptive load-balanced routing algorithms, an arbiter that alternated the priority order fairly is employed. With fair arbiter to decide the routing path for network-on-chip, balanced load can result in performance improvement in speed and capacity for both congestion-oblivious and congestion-aware routing schemes.

Load Balancing Oriented Predictive Routing Algorithm for Data Center Networks

A data center undertakes increasing background services of various applications, and the data flows transmitted between the nodes in data center networks (DCNs) are consequently increased. At the same time, the traffic of each link in a DCN changes dynamically over time. Flow scheduling algorithms can improve the distribution of data flows among the network links so as to improve the balance of link loads in a DCN. However, most current load balancing works achieve flow scheduling decisions to the current links on the basis of past link flow conditions. This situation impedes the existing link scheduling methods from implementing optimal decisions for scheduling data flows among the network links in a DCN. This paper proposes a predictive link load balance routing algorithm for a DCN based on residual networks (ResNet), i.e., the link load balance route (LLBR) algorithm. The LLBR algorithm predicts the occupancy of the network links in the next duty cycle, according to the ResNet architecture, and then the optimal traffic route is selected according to the predictive network environment. The LLBR algorithm, round-robin scheduling (RRS), and weighted round-robin scheduling (WRRS) are used in the same experimental environment. Experimental results show that compared with the WRRS and RRS, the LLBR algorithm can reduce the transmission time by approximately 50%, reduce the packet loss rate from 0.05% to 0.02%, and improve the bandwidth utilization by 30%.

Load balancing routing under constraints of quality of transmission in mesh wireless network based on software defined networking

Load balancing routing and quality of transmission (QoT) aware routing have been increasingly studied in mesh wireless networks (WMN) to improve their performance. For the load balancing routing, the traffic bottleneck in the network can be resolved. However, it can decrease QoT because the routes may passthrough multiple hops. On the other hand, the QoT aware routing often improves the QoT of the routes, but it can increase thetraffic bottleneck due to the unbalanced traffic load in the network. Therefore, the investigation of load balancing routing taking into account QoT is very essential, especially in the case of a wideand ultra-high speed WMN. In this paper, we propose a load balancing routing algorithm under the constraints of QoT for WMN. Our method uses the principle of the software defined networking (SDN) to choose the load balancing routes satisfying the constraints of QoT. Our performance evaluations using OMNeT+ have shownthe effectiveness of the proposed algorithm in improving QoT of thedata transmission routes, increasing the packet delivery ratio andthe network throughput, decreasing the end-to-end delay.

QoT AWARE LOAD BALANCING ROUTING IN MANET USING RELAY TYPE OF AMPLIFY AND FORWARD BASED COOPERATIVE COMMUNICATIONS

In research topics to improve the performance of the mobile ad hoc networks (MANET), the load balancing routing has been attracted many research groups because it is an effective solution to reduce the traffic congestion. However, for the mesh topologies as MANET, the load balancing routing can decrease the Quality of Transmission (QoT) because some routes can pass through many intermediate nodes, especially in the case of MANET using the relay type of amplify and forward (AF) based cooperative communications, where the power of the noise signal can be amplified at intermediate nodes. In this paper, we focus on investigating the QoT in MANET using AF. Thence, a load balancing routing algorithm that takes account of the QoT is proposed in order to improve the network performance. Our evaluation by simulation method has showed that the proposed algorithm can improve the network performance in terms of the QoT, blocking probability of data packet, and network throughput compared with the original routing algorithms.

QOS Assured and Energy Efficient Load Balancing Routing Algorithm for Wireless Video Delivery

QOS Assured and Energy Efficient Load Balancing Routing Algorithm for Wireless Video Delivery