Efficient Load Balancing Algorithms Research Articles

Efficient Load Balancing Algorithm for the Arrangement-Star Network

The Arrangement-Star is a well-known network in the literature and it is one of the promising interconnection networks in the area of super computing, it is expected to be one of the attractive alternatives in the future for High Speed Parallel Computers. The Arrangement-Star network has many attractive topological properties such as small diameter, low degree, good connectivity, low broadcasting cost and flexibility in choosing the desired network size. Although, some of the research work has been done on Arrangement-Star network, it still needs more investigation and research efforts to explore these attractive topologies and utilize it to solve some real life applications. In this paper we attempt to fill this gap by proposing an efficient algorithm for load balancing among different processors of the Arrangement-Star network. The proposed algorithm is named as Arrangement Star Clustered Dimension Exchange Method ASCDEM presented and implemented on the Arrangement-Star network. The algorithm is based on the Clustered Dimension Exchange Method (CDEM). The ASCDEM algorithm is shown to be efficient in redistributing the load balancing among all different processors of the network as evenly as possible. A complete detail of this algorithm in addition to examples and discussions to explore the benefits of applying this distributed algorithm is presented in this paper. Furthermore an analytical study on the algorithm is presented and discussed to explore the attractive performance of the proposed algorithm.

Systematic Review on Existing Load Balancing Techniques in Cloud Computing

loud computing requires more reliable, efficient and scalable load balancing algorithm to survive. As one of the main challenges in cloud computing, load balancing facilitate dynamic workload across multiple nodes ensuring that no single node get overloaded. With proper load balancing, resource consumption is maintained at minimum level, enabling scalability, avoiding bottleneck and overprovisioning etc. In this paper, systematic review on existing load balancing techniques currently prevalent in cloud computing was carried out. Load balancing metrics; Response time, Performance, Resource Utilization, Throughput, Cost Overhead, Scalability, Fault Tolerant and Migration Time were used to evaluate the existing techniques. Findings show that the existing techniques mainly focus on reducing response time, completion time, cost and improving throughput. Neither of the techniques was able to unveil efficient load balancing of task scheduling for single and federated cloud environment. However, research such as load balancing of energy consumption, server consolidation, Virtual Machine Migration, are not taken into consideration by the existing techniques. Future research is to unveil efficient multi-objective load balancing of tasks scheduling algorithm with quality of service improvements for homogeneous and federated heterogeneous cloud environment.

Factor‐Optical‐Factor Exchanges Method: a new load balancing method for Extended Optical Transpose Interconnection System‐n‐Cube networks

SummaryThe Optical Transpose Interconnection System (OTIS) optoelectronic interconnection network architecture is a promising attraction in the new era of parallel computing topologies because of its attractive topological properties. Recently, many enhancements were presented on OTIS topologies including the Extended OTIS‐n‐Cube interconnection networks. Therefore, all performance improvement characteristics of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses on developing an efficient algorithm for load balancing on the promising Extended OTIS‐n‐Cube interconnection networks. The proposed algorithm is called Factor‐Optical‐Factor Exchange Model. Furthermore, this paper presents theoretical and experimental study on the proposed algorithm in terms of various parameters including execution time, load balancing accuracy, number of communication steps, and speed. Results show superiority of the proposed algorithm over the well‐known Clustered Dimension Exchange Method (CDEM) algorithm in terms of execution time, number of communication steps, and speed, while maintaining the same level of accuracy. Copyright © 2015 John Wiley & Sons, Ltd.

Heterogenous QoS‐guaranteed load balancing in 3GPP LTE multicell fractional frequency reuse network

ABSTRACTThe performance of 3GPP long term evolution (LTE) network can be significantly influenced by unbalanced user distribution. In heavily loaded cells, users cannot obtain satisfied services because of shortage of resources, whereas in lightly loaded cells, there are plenty of unoccupied resources. Load balancing (LB) is proposed to deal with this problem, through which the load distribution among nearby cells can be greatly balanced. However, because of the usage of full frequency reuse in LTE, the cell‐edge throughput is severely deteriorated by strong intercell interference. Meanwhile, LTE network usually serves users with heterogenous quality‐of‐service (QoS) requirements, which requires LB to be aware of it. Furthermore, call admission control (CAC) is indispensable in the process of LB, and it depends heavily on the long‐term average performance of the scheduling scheme. Thus, design of an efficient LB algorithm with the consideration of intercell interference, QoS, CAC and scheduling together becomes an important issue. To deal with the previous problem, a multi‐objective optimisation problem is formulated in this paper. Its complexity is analysed, and a practical algorithm, which includes hybrid scheduling, QoS‐guaranteed CAC, QoS‐aware intracell and intercell LB, is proposed. Extensive simulations are conducted. Results show that the proposed algorithm can approximate the optimal solution efficiently, thus leading to significantly better performance, that is, a lower new call blocking rate for users with QoS requirement, a larger total utility and a higher cell‐edge throughput for users without QoS requirement, although the cost is a bit degradation of the total throughput. Copyright © 2013 John Wiley & Sons, Ltd.

Efficient load balancing on biswapped networks

This paper focuses on devising an efficient algorithm for load balancing on the promising biswapped interconnection networks which were recently proposed as a better architecture over the well-known OTIS networks. The proposed algorithm is called GPM which reduces the number of load balancing steps of the existed algorithms obviously. GPM algorithm first schedules load flows on inter-groups links to achieve the balanced status among groups. Then a general load balancing strategy is executed in each of all groups to balance processor loads. The analytical model proves that GPM algorithm is efficient and results of computer simulation experiment indicate that GPM can implement load balancing in biswapped network interconnected environments efficiently, in terms of various parameters.

An Adaptive Load Balancing Algorithm for Computational Grid

To improve the global throughput of computational grid, effective and efficient load balancing algorithms are fundamentally important. A computational grid differs from traditional high-performance computing system in the heterogeneity of computing nodes, as well as the communication links that connect the different nodes together. In this paper, we propose a resource queue length based solution to the grid load balancing problem. The proposed algorithm will balance the load in the grid based on the queue length of each resource and transfer the job to the resource having minimum queue length. The simulation results show that our algorithm can achieve a better load balancing performance than its counterpart provided in simulation.

Load Balancing in Grid Environment using Machine Learning - Innovative Approach

ABSTRACT Grid computing creates the illusion of a simple but large and powerful self-managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources which leads to the problem of load balance. The main goal of load balancing is to provide a distributed, low cost, scheme that balances the load across all the processors. To improve the global throughput of Grid resources, effective and efficient load balancing algorithms are fundamentally important. Focus of this paper is on analyzing Load Balancing requirements in a Grid environment and proposing an algorithm with machine learning concepts to find more efficient algorithm. The decisions General Terms Grid Computing, Load balancing, Machine learning, Job migration. 1. INTRODUCTION 1.1 Grid Computing Grid is type of parallel and distributed system that enables the sharing, selection and aggregation of geographically distributed resources dynamically at run time depending on their availability, capability, performance, cost, and user quality-of -self-service requirement. Further we can also identify Grid Computing [1, 2, 4] as, a type of parallel computing that relies on complete computers connected to a network. Grids tend to be more loosely coupled, heterogeneous, and geographically distributed. In Grid computing, the details are abstracted, and the resources are virtualized.

ClustalXeed: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

BackgroundThere is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC) environment with a greatly extended data storage capacity.ResultsWe designed ClustalXeed, a software system for multiple sequence alignment with incremental improvements over previous versions of the ClustalX and ClustalW-MPI software. The primary advantage of ClustalXeed over other multiple sequence alignment software is its ability to align a large family of protein or nucleic acid sequences. To solve the conventional memory-dependency problem, ClustalXeed uses both physical random access memory (RAM) and a distributed file-allocation system for distance matrix construction and pair-align computation. The computation efficiency of disk-storage system was markedly improved by implementing an efficient load-balancing algorithm, called "idle node-seeking task algorithm" (INSTA). The new editing option and the graphical user interface (GUI) provide ready access to a parallel-computing environment for users who seek fast and easy alignment of large DNA and protein sequence sets.ConclusionsClustalXeed can now compute a large volume of biological sequence data sets, which were not tractable in any other parallel or single MSA program. The main developments include: 1) the ability to tackle larger sequence alignment problems than possible with previous systems through markedly improved storage-handling capabilities. 2) Implementing an efficient task load-balancing algorithm, INSTA, which improves overall processing times for multiple sequence alignment with input sequences of non-uniform length. 3) Support for both single PC and distributed cluster systems.

A proactive low-overhead file replication scheme for structured P2P content delivery networks

File replication is a widely used technique for high performance in peer-to-peer content delivery networks. A file replication technique should be efficient and at the same time facilitates efficient file consistency maintenance. However, most traditional methods do not consider nodes’ available capacity and physical location in file replication, leading to high overhead for both file replication and consistency maintenance. This paper presents a proactive low-overhead file replication scheme, namely Plover. By making file replicas among physically close nodes based on nodes’ available capacities, Plover not only achieves high efficiency in file replication but also supports low-cost and timely consistency maintenance. It also includes an efficient file query redirection algorithm for load balancing between replica nodes. Theoretical analysis and simulation results demonstrate the effectiveness of Plover in comparison with other file replication schemes. It dramatically reduces the overhead of both file replication and consistency maintenance compared to other schemes. In addition, it yields significant improvements in reduction of overloaded nodes.

Dynamic load balancing efficiently in a large-scale cluster

Random Stealing (RS) is a well-known dynamic load-balancing algorithm, used both in shared-memory and distributed-memory systems. However, for a large-scale cluster, the simple RS policy is no longer efficient because an idle node must randomly steal many times to obtain a task from another node. In this paper, we propose a novel dynamic load-balancing algorithm, Transitive Random Stealing (TRS), which can make any idle node obtain a task from another node with much fewer stealing times in a large-scale cluster. Analysing and testing show that TRS is a highly efficient dynamic load-balancing algorithm in a large-scale cluster.

The load balancing problem in OTIS-Hypercube interconnection networks

An interconnection network architecture that promises to be an interesting option for future-generation parallel processing systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing accuracy, number of communication steps, and speed.

Task Load Balancing Strategy for Grid Computing

Workload and resource management are two essential functions provided at the service level of the Grid software infrastructure. To improve the global throughput of these environments, effective and efficient load balancing algorithms are fundamentally important. Most strategies were developed in mind, assuming homogeneous set of resources linked with homogeneous and fast networks. However for computational Grids we must address main new challenges, like heterogeneity, scalability and adaptability. Our contributions in this perspective are two fold. First we propose a dynamic tree-based model to represent Grid architecture in order to manage workload. This model was characterized by three main features: (i) it was hierarchical; (ii) it supports heterogeneity and scalability; and (iii) it was totally independent from any Grid physical architecture. Second, we develop a hierarchical load balancing strategy and associated algorithms based on neighbourhood propriety. The main benefit of this idea was to decrease the amount of messages exchanged between Grid resources. As consequence, the communication overhead induced by tasks transferring and flow information was reduced. In order to evaluate the practicability and performance of our strategy we have developed a Grid simulator in Java. The first results of our experimentations were very promising. We have realized a significant improvement in mean response time with a reduction of communication cost. It means that the proposed model can lead to a better load balancing between resources without high overhead.

Load Balancing in WDM Networks through Dynamic Route Changes

This study deals with the formulation of an effective and efficient algorithm for load balancing in WDM networks. Here we develop a Load Balancing algorithm for IP-like Routing. The considered networks are based on a routing protocol where the next hop at a given node depends only on the destination of the communication.The aim of this work is to consider the applicability of this approach in the context of optical networks, by taking into account the routing and wavelength assignment constraints simultaneously which is a NP-Complete problem.Our algorithm performs at each iteration, a basic change in the network by rerouting the traffic to the destination from the given source by finding an alternate path thereby reducing the load on the common link. As a result a single entry change in the routing table is performed, which is very important for the stability of the network.

The design of an efficient load balancing algorithm employing block design

In order to maintain load balancing in a distributed system, we should obtain workload information from all the nodes on network. This processing requires O(v2) communication overhead, where v is the number of nodes. In this paper, we present a new synchronous dynamic distributed load balancing algorithm on a (v, k + 1, 1)-configured network applying a symmetric balanced incomplete block design, where v = k2 + k + 1. Our algorithm needs only O(v√v) communication overhead and each node receives workload information from all the nodes without redundancy. Therefore, load balancing is maintained since every link has the same amount of traffic for transferring workload information.

An efficient load-balancing algorithm based on a two-threshold cell selection scheme in mobile cellular networks

In this paper, we design and analyze an efficient load-balancing algorithm for channel assignment in mobile cellular networks. Based on a two-threshold cell selection scheme, our algorithm employs a fixed channel assignment as an underlying strategy and attempts, at run-time, to balance dynamically the available channels between the cells. Two thresholds, light and heavy, are introduced to classify the cells in the system into three categories— light, moderate, and heavy cells—according to the number of available channels in a cell. Whenever there exist any heavy cells, the load-balancing algorithm is activated by the MSC in order to borrow free channels from light cells to satisfy the demands of the heavy cells. When making a borrowing decision, the algorithm takes into account not only the state of a potential lender cell but also the states of the co-channel cells of the lender. The performance of our algorithm is evaluated and compared with other existing schemes.

Load balancing and routing on the hypercube and related networks

Several results related to the load balancing problem on the hypercube, the shuffle-exchange, the cube-connected cycles, and the butterfly are shown. Implications of these results for routing algorithms are also discussed. Our results include the following: • ⊎ Efficient load balancing algorithms are found for the hypercube, the shuffle-exchange, the cube-connected cycles, and the butterfly. • ⊎ Load balancing is shown to require more time on a p-processor shuffle-exchange, cube-connected cycle or butterfly than on a p-processor weak hypercube. • ⊎ Routing n packets on a p-processor hypercube can be done optimally whenever n = p 1+1/ k , for any fixed k > 0.

An efficient algorithm for load balancing of transformers and feeders by switch operation in large scale distribution systems

A systematic and practical algorithm for load balancing of transformers and feeders by automatic sectionalizing of switch operation in large-scale distribution systems of the radial type is discussed. The algorithm is developed by extending an approximation for load transfer of the desired two transformers. The algorithm is applicable to operations not only in the normal state, but also in the scheduled and failure outage states. Computational experience on a real large-scale system has indicated that the algorithm is valid and effective for practical operations. >