Load Balancing Routing Algorithm Research Articles

Load-Balancing Routing Algorithm Based on Segment Routing for Traffic Return in LEO Satellite Networks

To tackle the network congestion problem caused by ground gateway stations arranged within a limited area in low earth orbit (LEO) satellite networks, a routing algorithm based on segment routing for traffic return is proposed. Light and heavy load zones are dynamically divided according to the relative position relationship between gateways and the reverse slot. The pre-balancing shortest path algorithm is used in the light load zone, and the minimum weight path defined by congestion index is the routing rule in the heavy load zone. Then, the consistent forwarding is performed referring to segment routing in all zones. Simulation conditions are different sizes of heavy load zone, different traffic density distributions, and different traffic demands. Simulation results confirm that the load-balancing performance is improved significantly with the extension of the heavy load zone size in terms of the average rejection ratio, the average relative throughput, the maximum link utilization, and the average delay. The proposed algorithm is an alternative solution and guidance for routing strategy in LEO satellite networks.

A novel adaptive congestion-aware and load-balanced routing algorithm in networks-on-chip

Congestion-aware routing algorithms attempt to have more diversity in routes to be chosen and avoid congested areas in networks-on-chip. In this paper, a novel fully adaptive congestion-aware routing algorithm called zigzag routing algorithm (ZRA) along with a new load-balanced method is proposed. ZRA presents a new way for transmitting congestion information, which allows a better view on congestion compared to other algorithms. Furthermore, the load-balanced method recognizes a forbidden area in the network according to betweenness centrality parameter. Fortifying ZRA with this novel load-balanced scheme yields more improvement in performance compared with the previous work. On average, we have accomplished 20.8% and 12.4% improvement in SPLASH-2 benchmark in contrast to DyAD and CATRA algorithms, respectively. It can be claimed that the proposed routing scheme does not consume more power than DyAD and CATRA. Moreover, a new parameter is suggested for comparing load-balanced algorithms, called the variance of crossbar activity.

Traffic load-aware dynamic energy-efficient routing strategy with spectrum reservation and load balance in elastic optical networks

Abstract For reducing the energy consumption in elastic optical networks (EONs) and mitigating the increasement of bandwidth blocking probability (BBP), a spectrum reservation and load balancing routing strategy (SRLBRS) is proposed. In SRLBRS, a spectrum state formula of node is designed to report the link spectrum usage of node-related links on the shortest path of traffic. Then, the node spectrum state can be determined by comparing the spectrum status of node-related links on the shortest path and average spectrum status in the EON. At the same time, the load state of candidate lightpath is decided by node spectrum state and available frequency slots of candidate lightpath. Available spectrum aware reservation grooming algorithm (ASARG) and load balancing routing algorithm (LBRA) are proposed and performed independently based on load state of candidate path. The ASARG focuses on energy saving by reserving lightpath dynamically according to available frequency slots of lightpath. While LBRA focuses on BBP by designing a lightpath cost formula, which is with respect to hops and spectrum continuity. Moreover, a balance index is designed to evaluate the balance between energy efficiency and blocking performance. Compared with the green grooming algorithms of distance-adaptive spectrum resource allocation (GGA + DASRA), simulation results show that the proposed SRLBRS can balance the energy consumption and blocking probability significantly. For instance in terms of balance index, our proposal achieved 57.9% better results averagely in a NSFNET topology.

Load-balanced routing algorithm based on cluster heads optimization for wireless sensor networks

In order to solve the problem of unbalanced load consumption of nodes for wireless sensor networks (WSNs), this paper proposes a load-balanced routing algorithm based on cluster heads optimization for wireless sensor network. The proposed algorithm first applies first-order wireless transmission model to calculate the optimal number of clusters, then calculate nodes competitiveness rating by fuzzy algorithm considering the residual energy of node and distance from the node to base station, cluster head selection uses unequal clustering algorithm according to the competitiveness of nodes. By node competitiveness and energy management mechanism which cooperate with each other to select the best cluster heads. Use connected optimization between clusters to search multi-hop paths base station for reducing energy consumption of node, and consider transmission energy consumption, residual energy, transmission distance and other factors. The experimental results show that the proposed algorithm compared with LEACH and UCDP algorithm, can balance loading and effectively extend the life cycle of wireless sensor network.

A load balanced routing algorithm based on congestion prediction for LEO satellite networks

This paper presents a load balancing routing algorithm based on congestion prediction (LBRA-CP) so as to realize an efficient load balancing over the entire Low Earth Orbit satellite networks. A multi-objective optimization model is built, which not only adopts modifying factor to adjust path cost, but also uses congestion prediction to foresee inter-satellite link congestion. Then an ant colony algorithm is utilized to solve this model, resulting in finding an optimal path for every connection request. Meanwhile, in order to improve the reliability of LBRA-CP, the valve of the pheromone evaporation coefficient is discussed in this paper. The performance is measured by the receiver’s throughput, the link utilization and the end-to-end delay. Simulation results show that LBRA-CP performs well in balancing traffic load and increases the receiver’s throughput. Meanwhile, the end-to-end delay can meet the requirement of video transmission.

Ant colony optimization based load balancing routing and wavelength assignment for optical satellite networks

An ant colony optimization (ACO) based load balancing routing and wavelength assignment (RWA) algorithm (ALRWA) was put forward for the sake of achieving a fairy load balancing over the entire optical satellite networks. A multi-objective optimization model is established considering the characteristic of global traffic distribution. This not only employs the traffic intensity to modify the light path cost, but also monitors the wavelength utilization of optical inter-satellite links (ISLs). Then an ACO algorithm is utilized to solve this model, leading to finding an optimal light path for every connection request. The optimal light path has the minimum light path cost under satisfying the constraints of wavelength utilization, transmission delay and wavelength-continuity. Simulation results show that ALRWA performs well in blocking probability and realizes efficient load balancing. Meanwhile, the average transmission delay can meet the basic requirement of real-time business transmission.

Load Balance Routing Algorithm Based on Cross-Layer Power Control for Wireless Sensor Network

Load Balance Routing Algorithm Based on Cross-Layer Power Control for Wireless Sensor Network

HyperFatTree: A Large-Scale Tree-Based Network with Low-Radix Switches

To lower the large-scale network cost and energy consumption, we proposed a hierarchical topology with low-radix switches. The hierarchical topology HyperFatTree is designed by combining Fat Tree topology and complete graph topology. Theory analysis of topology characteristic shows that the proposed topology can achieve high cost performance and high scalability. According to the characteristic of HyperFatTree, we designed a minimum path routing algorithm and a load balanced non-minimum path random routing algorithm for the WorstCase traffic. Evaluation shows that the saturated throughput of HyperFatTree is nearly 68.5 % at the scale of 83,232 nodes under Uniform Random traffic, which is higher than both Fat Tree and Dragonfly. It is also important that the throughput reduces only 5 % while the scale has increased 80 times, which shows good smooth scalability. Evaluation on energy efficiency shows that HyperFatTree performs better than Fat Tree and can achieve 3---7 times higher energy efficiency than Dragonfly.

A Routing Aggregation for Load Balancing Network-on-Chip

A routing aggregation (RA) is proposed for load balancing network-on-chip (NoC). The computing nodes with dense traffic and long distance in network are gathered into the same routing node to form a super router. A load balancing routing algorithm for super router is presented to improve the overall performance of NoC. A simulation platform using System C is presented to confirm the feasibility of the proposed design in 2D mesh. The simulation results show that the proposed RA design can reduce the average packet latency and the standard deviation of host link utilization 8% and 33%, respectively compared with the reported routing methods. The area cost and power consumption compared with the reported schemes are 22% and 12% less, respectively.

Load balancing and data aggregation tree routing algorithm in wireless sensor networks

Load balancing and data aggregation tree routing algorithm in wireless sensor networks

A load-balancing routing algorithm for multi-channel wireless mesh networks

This paper presents a load-balancing routing LBR algorithm for multi-channel wireless mesh networks WMNs. The objective of this algorithm is to reduce interference and balance network load among li...

A load-balancing routing algorithm for wireless sensor networks based on domain decomposition

Massively-dense wireless sensor networks (WSNs) may increase the difficulty of designing efficient and optimal routing algorithms. Since, from a macroscopic perspective, the optimal load-balancing routing problem may be formulated as a set of partial differential equations (PDEs), a scalable routing algorithm may be obtained by using WSNs themselves to solve the PDEs numerically, e.g., through the Gauss–Seidel iteration. To accelerate convergence without sacrificing precision, the proposed distributed Multiplicative Schwarz routing (DMSR) algorithm uses domain decomposition to iteratively solve the PDEs. Furthermore, the precision and parallelism may be improved by adapting an appropriately defined iteration order. Algorithm performance is analyzed theoretically for parallelism and errors, and numerical simulation results are presented to assess the efficiency and effectiveness of DMSR in achieving load balancing.

Efficient Clustering with Proposed Load Balancing Technique for MANET

this paper, an efficient and modified load balancing algorithm is proposed. This paper shows the results of the proposed energy aware load balancing algorithm. Global re- clustering is initiated when the network becomes significantly unbalanced i.e. if the variance of degree of the cluster heads in the network is greater than a pre-determined threshold. Degree of all cluster heads would be required at a single node to evaluate the average of degree of all cluster heads in the network and subsequently the variance among themselves, which is not possible in adhoc network because of its distributed nature. For this, a formula is derived in which variance can be updated at each hop i.e. variance of N nodes can be expressed in terms of variance of (N-1) nodes and average of (N-1) nodes. The results of simulation indicate that compared with the load balanced routing algorithm DEECA, the proposed algorithm increased the network lifetime, packet delivery ratio at different traffic. KeywordsClustering, Cluster Maintenance, Load Balancing,

A load-balancing routing algorithm for multi-channel wireless mesh networks

This paper presents a load-balancing routing LBR algorithm for multi-channel wireless mesh networks WMNs. The objective of this algorithm is to reduce interference and balance network load among links. The LBR algorithm is composed of link allocation algorithm and load-balancing route-selection algorithm. First, the network model is presented. Based on this model, a link allocation algorithm is proposed to allocate all links to channels which aims to minimise interference degree of networks. After links are allocated to channels, a route-selection algorithm is proposed to select a path from source to destination to balance network load. Simulation results demonstrate that the proposed algorithm balances network load and improves the network throughput significantly.

Ant Colony Optimization-Based Fault-Aware Routing in Mesh-Based Network-on-Chip Systems

The advanced deep submicrometer technology increases the risk of failure for on-chip components. In advanced network-on-chip (NoC) systems, the failure constrains the on-chip bandwidth and network throughput. Fault-tolerant routing algorithms aim to alleviate the impact on performance. However, few works have integrated the congestion-, deadlock-, and fault-awareness information in channel evaluation function to avoid the hotspot around the faulty router. To solve this problem, we propose the ant colony optimization-based fault-aware routing (ACO-FAR) algorithm for load balancing in faulty networks. The behavior of an ant colony while facing an obstacle (failure in NoC) can be described in three steps: 1) encounter; 2) search; and 3) select. We implement the corresponding mechanisms as: 1) notification of fault information; 2) path searching mechanism; and 3) path selecting mechanism. With proposed ACO-FAR, the router can evaluate the available paths and detour packets through a less-congested fault-free path. The simulation results show that this paper has higher throughput than related works by 29.1%–66.5%. In addition, ACO-FAR can reduce the undelivered packet ratio to 0.5%–0.02% and balance the distribution of traffic flow in the faulty network.

Load-Balanced Low-Power Routing Algorithm Design for Wireless Sensor Networks

Low-power wireless sensor networks (WSNs) design involves all aspects of research in wireless sensor networks. As energy is limited in wireless sensor networks, how to effectively manage and use energy of WSNs, and how to maximize the reduction of power consumption in WSNs and extend the lifetime of WSNs become a key problem faced by wireless sensor networks. Aimed at these problems, a low-power clustering routing algorithm based on load-balanced is proposed. The algorithm introduced an energy load factor to reduce the power consumption of WSNs. The simulation results show that the low-power routing algorithm can effectively reduce power consumption of networks and extend the lifetime of networks.

A Load-Balanced Multicast Routing Algorithm in Cognitive Wireless Mesh Networks

A load balanced wireless links weights computing function and computing algorithm(LBWC) are proposed.On this basis,a load balanced joint multicast routing and spectrum allocation algorithm with QoS constraints in cognitive wireless mesh networks(LMRS2A) is proposed.Balancing the load of network and minimizing the number of transmission of multicast tree are the objective of LMRS2A under the QoS constraints.First,LMRS2A computes the weights of wireless links using LBWC for constructing the load balanced multicast tree.Second,LMRS2A uses the algorithm WBA2S with QoS constraints allocating channel to links which is based on the Wireless Broadcast Advantage(WBA).Simulation results show that LMRS2A algorithm can achieve expectation goal.It can not only avoid the congestion of node,but also need lower number of transmission of multicast tree.

DAG Based Multipath Routing Algorithm for Load Balancing in Machine-to-Machine Networks

In M2M networks, most nodes are powered by battery; hence the overused nodes may easily be out of power, which causes the reduction of network lifetime. To solve this problem, it is helpful to balance network load into more nodes and links, so as to reduce network congestion. Multipath routing is a useful tool to reduce congestion, since data flow can be dispersed into multiple paths. However, most of the previous multipath routing algorithm is based on the path disjoint constraint, which leads to the lack of routing paths and the failure to disperse data flow into more links. In this paper, a directed acyclic graph based multipath routing algorithm for congestion minimization (DAGMR) is proposed, where different routing paths are confined in a directed acyclic graph (DAG) under time delay constraint. Furthermore, the data flow distribution is accomplished through partial capacity network to obtain the minimal multipath routing congestion factor. Simulation indicates that our algorithm can obtain lower congestion factor and formulates multipath routing graph with more nodes and links than algorithm with path disjoint constraint. In addition, our algorithm is a polynomial time complexity algorithm with nodes and links number of the entire network.

A Load Balance Routing Algorithm Based on Uneven Clustering

Aiming at the problem of uneven load in clustering Wireless Sensor Network (WSN), a kind of load balance routing algorithm based on uneven clustering is proposed to do uneven clustering and calculate optimal number of clustering. This algorithm prevents the number of common node under some certain cluster head from being too large which leads load to be overweight to death through even node clustering. It constructs evaluation function which can better reflect residual energy distribution of nodes and at the same time constructs routing evaluation function between cluster heads which uses MATLAB to do simulation on the performance of this algorithm. Simulation result shows that the routing established by this algorithm effectively improves network’s energy balance and lengthens the life cycle of network. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3403

Cross-layer design and ant-colony optimization based routing algorithm for low earth orbit satellite networks

To improve the robustness of the Low Earth Orbit (LEO) satellites networks and realise load balancing, a Cross-layer design and Ant-colony optimization based Load-balancing routing algorithm for LEO Satellite Networks (CAL-LSN) is proposed in this paper. In CAL-LSN, mobile agents are used to gather routing information actively. CAL-LSN can utilise the information of the physical layer to make routing decision during the route construction phase. In order to achieve load balancing, CAL-LSN makes use of a multi-objective optimization model. Meanwhile, how to take the value of some key parameters is discussed while designing the algorithm so as to improve the reliability. The performance is measured by the packet delivery rate, the end-to-end delay, the link utilization and delay jitter. Simulation results show that CAL-LSN performs well in balancing traffic load and increasing the packet delivery rate. Meanwhile, the end-to-end delay and delay jitter performance can meet the requirement of video transmission.