A load balancing method in downlink LTE network based on load vector minimization

This article introduces a method of load balancing. This method can automatically and reasonably allocate information processing requests based on the real-time resources of the server without introducing additional devices in the cloud computing process. The technology establishes a cluster architecture without load balancing devices, including a task pool, a task publishing module, and a task acquisition module. This technology uses pulling to distribute tasks. This method can dynamically allocate computing resources in the cluster. This technology does not require registration nodes to join or exit, and nodes do not interact with each other. It is easy to adjust the cluster size. The use of this technology avoids the waste of system computing resources due to bottlenecks in key nodes, unreasonable task assignments, and the like. This technology reduces the cost of the cluster system, and at the same time solves the problem that the load balancing device can easily become the bottleneck of the cluster.

Hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks (HLWNets) have been recently proposed as a promising technique for indoor wireless communications. Such a network combines the high-speed transmission of LiFi and the ubiquitous coverage of WiFi. Meanwhile, in addition to user mobility, intermittent light-path blockages make the handover issue intricate in HLWNets. Also, load balancing (LB) is necessary because the coverage areas of LiFi and WiFi networks are completely overlapped. This further increases the difficulty in handover as the decision for a vertical or a horizontal handover in a mobile environment with ultra-small cells is non-trival. Aimed at providing an optimal solution to the access point selection (APS) with given channel state information (CSI), the conventional LB method might cause frequent and unnecessary handovers. In this paper, a joint optimisation problem is formulated to simultaneously consider LB and handover in HLWNets. Results show that compared with the conventional LB method, the proposed method can improve the system throughput by up to 60%.

Load balancing problem is one of the key issues in multi-server architecture Distributed Virtual Environment (DVE) system. Existing load balancing methods are mainly for the one-dimensional cutting based DVE system or square cell based DVE system, and it is difficult to apply them to the hexagonal cell based DVE system. In this paper, we propose a new load balancing method for hexagonal cell virtual environment system, which can effectively reduce the number of overloaded server at run time and reduce the client migrations between servers by selecting appropriate migration cells. The experimental results show that the proposed method can effectively keep the load balance among servers in the virtual environment system based on hexagon partitioning and reduce the probability of client migrations, thus improving the usability of the system.

The internet is something that is absolutely needed by every human being, as a result network administrators will implement various alternatives to meet user needs. The administrator will add an ISP line to be able to use the internet smoothly and easily. In fact, administrators often use an ISP's gateway line. This causes traffic inequality on the network when the number of users connected to the ISP line is much more. In the implementation of this final project, a load balancing and connection was made using 2 ISPs. The method used is the load balancing and failover method which is implemented using a mikrotik routerboard on the RT RW NET Dusun Klatakan network. With these two methods, all requests are based on the client that will enter the router that has been configured using the previous load balancing and failover method, so that the router will set the path based on the client through ISP 1 or ISP 2 in order to be able to back up each other's internet connections. The test results show the occurrence of equal access to access in a balanced way, so that there is no overload at one ISP.

Phase reassignment for load balance in low-voltage distribution networks

The uncertain nature of mapping user tasks to Virtual Machines (VMs) causes system failure or execution delay in Cloud Computing. To maximize cloud resource throughput and decrease user response time, load balancing is needed. Possible load balancing is needed to overcome user task execution delay and system failure. Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration. Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs. Thus, the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism (HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly. This load balancing approach improved performance by considering average network latency, dependability, and throughput. This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation, assign jobs to VMs with more solution diversity, and prevent the solution from reaching a local optimality. Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan, 16.21% increase in mean throughput, and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA, HD-WOA, and Binary Bird Swap.

The rapid development of the Internet requires a counterweight in maintaining connectivity and network stability. connectivity becomes one of the aspects that take priority in a network, and therefore the Internet connection on demand to always be stable and interference free, but not always a connection running smoothly and stable. Usually there are a variety of disorders within a network, hence the need for bakcup management of the network that are running so that if one impaired then there will be a backup. One that can be done is by using load balancing. Subyek taken in this study to focus on the implementation of the source network backup or backup Internet from the dependence of the internet service provider or ISP provider. Load balancing method using Equal Cost Multi-Path, research methods that used are library research, observation and interviews network of PT.Nipindo. As for the design begins with installing mikrotik here in after may be applied load balancing. Technical test carried out by using a ping test is performed to determine whether the connection is running well or not. The result of applying load balancing method shows ECMP load balancing goes well. Load balancing does not change the physical structure of an existing network, so it can produce optimal connections when an increase in traffic due to the balanced distribution of bandwidth.

Cloud computing involves virtualization, distributed computers, networking, software, and web services. Clouds have clients, datacenters, and servers. It has fault tolerance, high availability, scalability, flexibility, little user overhead, cheap ownership cost, on-demand services, etc. These difficulties require a powerful load balancing algorithm. Memory, CPU, latency, or network-load. Load balancing distributes demand to avoid overloaded distributed system nodes and optimises resource use and job response time. Load balancers ensure that processors and network nodes perform similarly. Methods initiated by sender, recipient, or symmetric. Using the divisible load scheduling theorem, a load balancing method will optimise throughput and latency for clouds of different sizes.

Load balancing has become an issue which should be focused on. Existing researches on load balancing, however, have their inadequacies, such as only supporting simply static methods in many of main J2EE application servers without dynamic nature and adaptive ability. In view of the deficiency above, a secondary positioning self-adaptive method is presented in this paper, and according to the idea of modular and plug-in design in JBoss, this load balancing method is implemented on the form of MBean and has been embedded in JBoss. In addition, using the design pattern of interceptor and proxy decision-making mechanism, two chains of interceptor are designed and realized so that load balancing support a double-level positioning for a request. The performance of this method is tested in JBoss at last, and the results show this method can balance the workloads effectively. Moreover, this method can be served as a reference for realizing self-adaptive load balancing.

We describe the design of a flexible load balancing framework and runtime software system for supporting the development of adaptive applications on distributed-memory parallel computers. The runtime system supports a global namespace, transparent object migration, automatic message forwarding and routing, and automatic load balancing. These features can be used at the discretion of the application developer in order to simplify program development and to eliminate complex bookkeeping associated with mobile data objects. An evaluation of this system in the context of a three-dimensional tetrahedral advancing front parallel mesh generator shows that overall runtime improvements of 15 percent compared to common stop-and-repartition load balancing methods, 30 percent compared to explicit intrusive load balancing methods, and 42 percent compared to no load balancing are possible on large processor configurations. At the same time, the overheads attributable to the runtime system are a fraction of 1 percent of the total runtime. The parallel advancing front method is a coarse-grained and highly adaptive application and therefore exercises all of the features of the runtime system.

Background: In this paper, we have surveyed the load modification and the trust capability in the cloud computing data centers. Method: The components of harmony search Algorithm include the harmony memory, the pitch adjustment rate and the random selection. The harmony memory checks and selects the responses. HMCR (Harmony Memory Considering Rate) is used for showing the possibility of selection from the memory and the pitch adjustment rate is used for causing a new harmony. Findings: Standard deviation and the resource exploitation average are the most important criteria at the load balancing. In this paper, the proposed Algorithm has been compared with the Genetic Algorithm and the simulation results show that the proposed Algorithm has a better competence than the Genetic Algorithm as the HSD (Harmony Search Degertekin ) rate of the proposed method is less than the HSD rate of Genetic Algorithm and the average of utilization from resources in the proposed method is more as well as with the increasing number of tasks, the performance of the algorithm is improved. Application/Improvement: Using this method of load balancing, the satisfaction of users is maximized, the time of response is minimized and the utilization of resources is increased.

The present trend in papermaking is towards higher machine speeds and improved paper quality. This requires papermaking machine drive system to improve its speed, provide higher stability and assure higher precision. So how to get a more realistic model and design a good drive control system is very important. A novel nonlinear load balance control method is presented in this paper, which is a more realistic load balance method because of including a larger number of variables. It can acquire identical or even higher performance with compare to linear balance method. The results of simulation indicated the nonlinear load balance method validity. A high-performance drive control system, which consists of advanced programmable computer controllers (PCC), smart servo drivers, also is discussed. With transfer data at rate of 100 Mbps, electrical cam and time-isolated multitask operating system, the novel drive system make higher performance motion control more easily to realize. The results showed the drive system presented was high precise, high reliable and easily extendable

The Internet of Things (IoT) is a network of different objects that refers to an environment in which intelligent devices around us can connect to the Internet and exchange information together. A large number of generated events from IoT objects causes overhead on the network. Therefore, to optimize the usage of IoT network, it is essential to provide solutions for network problems including scalability, routing, reliability, security, energy conservation, network lifetime, congestion, heterogeneity, and quality of service (QoS). In this regard, load balancing as an efficient method takes a significant role in distributing loads among different routes. Imbalance traffic load across the network causes high latency in some routes and loss of data packets and decreases packet delivery ratio. Although load balancing has a critical importance in the IoT, there is still a lack of an organized and comprehensive review about analyzing and examining its remarkable methods. Therefore, this paper by adopting a systematic manner aims to address this gap. In this research, the load balancing methods are categorized into two main categories including centralized and distributed and their merits and demerits are specified. Moreover, vital parameters, the challenges, and open issues in this scope are also discussed. Thus, future authors will be able to develop more effective load balancing mechanisms.

The main methodologies used in load balancing of electrical distribution system have been reviewed in this paper. The following load balancing techniques have been covered: (i) Dynamic leap-frog method, (ii) Dynamic water filling approach, (iii)Fuzzy logic with Newton Raphson optimization method and (iv) Network reconfiguration method. The work reported by the researchers have been presented based on (a) load balancing index (b) current balancing index (c) power loss calculation (d) switching positions (e) results and (f) algorithms implemented. Classification of various load balancing methods used by different researches has been done. The results have been published based on the comparison from different authors. Application of various methods as applied to different cities is also presented for consideration.

Firewalls are installed at network perimeters to secure organization's network as alternatives lo general gateways. Because of potential performance problems on the gateways, load balancing technique has been applied. However, compared to general gateways, firewalls require more intelligent load balancing method lo process massive network traffic because of their relatively complex operations. In this paper, we analyze the inherent problems of existing simple load balancing methods for firewalls and propose the interval weighted load balancing (IWLB) to enhance the processing of massive network traffics. The IWLB deals with network traffics in consideration of the characteristics of application protocols to achieve more effective load balancing. We observed that the IWLB outperforms other simple load balancing methods during our simulation. Therefore, we expect that the IWLB is suitable to balancing loads for multiple firewalls at a network perimeter.