Existing Load Balancing Schemes Research Articles

Energy-Efficient Resource Allocation for D2D-V2V Communication with Load Balancing

The significance of vehicle-to everything (V2X) communication in ensuring road safety is undeniable. In addition, real-time vehicle communication requires an ample amount of spectrum resources. However, the existing spectrum resources are seriously scarce, and the utilization rate is not high, leading to high delays in V2X communication and other unfavorable factors in the case of fast-moving vehicles, bringing great safety risks to driving. Load balancing is one of the most effective methods to improve spectrum utilization. However, the existing load balancing schemes merely focus on static conditions, with a lack of joint scheduling schemes, which cannot support the communication framework of dynamic V2X. To address both of these issues, in this paper, a new communication method is proposed. In addition, this paper studies a joint load balancing scheme of mobility vehicle-to-vehicle (V2V) and user association under incomplete channel state information (CSI) and realizes the load balancing management of a cross-cell V2X network. An algorithm combining power control and resource allocation mode selection is proposed. In particular, according to different coverage areas, different allocation algorithms are adopted to maximize the overall system efficiency. The simulation results show that this strategy can maintain low latency and effectively improve the system energy efficiency of vehicle users.

Load Balancing With Deadline-Driven Parallel Data Transmission in Data Center Networks

With the explosive growth of the Internet of Things (IoT), an increasing amount of sensor data generated by soft real-time IoT applications has been moved to data centers for storage and data analysis. Large amounts of these data are required to be processed within a given deadline to ensure application performance. Therefore, meeting the transmission deadlines of data flows for soft real-time applications has always been crucial yet challenging to current data centers. Recent progress has demonstrated that adopting parallel data transmission over multipath data center network combining with effective load balancing can achieve a high bisection network bandwidth, thus speeding up the network transfer of data flows. Nevertheless, the deadline miss ratios (DMRs) of these flows are not lowered as expected since the existing load balancing schemes are naturally agnostic to the deadline requirement. They are either unable to reroute traffic flexibly or aimlessly reroute these deadline-restrained flows, regardless of their urgent levels and path conditions. To address these inefficiencies, we propose a deadline-aware load-balancing scheme, namely, DLB, which perceives the deadline requirements and helps the urgent flows to timely switch to those faster transmission paths to complete quickly. Specifically, DLB computes the urgent level for each flow in real time to judge if the switch needs to make proactive rerouting. When a flow is nonurgent, DLB does not proactively change its transmission path, leaving more available paths to those flows with higher urgent levels. When a flow becomes extremely urgent, it immediately switches to those light-loaded paths to finish its data transmission before its deadline as far as possible. Experimental results of NS2 simulations and real testbed implementations show that DLB reduces the DMRs by up to 50% compared to the state-of-the-art data center load-balancing schemes, while only induces trivial overhead during deployment.

Hybrid SDN Networks: A Multi-parameter Server Load Balancing Scheme

Software-defined networking (SDN) provides many benefits, including traffic programmability, agility, and network automation. However, budget constraints burdened with technical (e.g., scalability, fault tolerance, security issues) and, sometimes, business challenges (user acceptance and confidence of network operators) make providers indecisive for full SDN deployment. Therefore, incremental deployment of SDN functionality through the placement of a limited set of SDN devices among traditional devices represents a rational and efficient environment that can offer customers modern and more data-intensive services. A unique challenge is the flexible distribution of loads on the servers that serve these services in network environments. The research in this paper focuses on developing a new load balancing scheme utilizing a hybrid SDN environment built with a minimal set of SDN devices (controller and one switch). We propose a novel load balancing scheme to monitor current server load indicators and apply multi-parameter metrics for scheduling connections to balance the load on the servers as efficiently as possible. The base of the new load balancing scheme is continuous monitoring of server load indicators and implementations of multi-parameter metrics (CPU load, I/O Read, I/O Write, Link Upload, Link Download) for scheduling connections. The testing performed on servers aims to balance the server’s load as efficiently as possible. The obtained results have shown that this mechanism achieves better results than existing load balancing schemes in traditional and SDN networks. Moreover, a proposed load balancing scheme can be used with various services and applied in any client-server environment.

RPL Based Routing Protocols for Load Balancing in IoT Network

RPL is a directing convention for remote organizations with low force utilization and large defenseless to parcel misfortune. It is a proactive convention dependent on distance vectors and works on IEEE 802.15.4. RPL can uphold a wide assortment of connection layers, including IoT, which is a technology that taking hold of research and industries with a fast tramp. It is a collection of actuators and sensors that collect data which can be processed to produce actual information. Important parameters allied to human body and physical environment data such that humidity, temperature, pressure, pollution etc. have immense significance for computerization, failure recognition, well timed, and appropriate cure. In this manner, IoT network offered ascend to keen urban communities, home mechanization, savvy wellbeing, present day travel strategic and some more. There is a distance vector normalization Routing Protocol for Low force and Lossy organization (RPL) for IoT sending, which relies upon different course improvement Objective functions (OF). These capacities rely upon different networks in the vein of energy like Received Sign Strength Indicator (RSSI) and Expected Transmission tally (ETX) for course streamlining. Course enhancement is influenced by issue of burden adjusting. In this paper, an inclusive survey of existing load balancing schemes, matrices, Objective Functions and different RPL based Routing protocols with reference to load imbalance is represented and highlighted when load balancing merged with the RPL, how it had a great impact.

Energy Efficient Resource Migration Based Load Balance Mechanism for High Traffic Applications IoT

The biggest challenge for the network service providers is the day to day advancement of technologies which makes them difficult to manage the traditional networks. This day to day advancement has worked as a motivation to vendors for developing, deploying and migrating their services, installments of new hardware, trained people and up gradation of infrastructure which involves a huge cost and time. These frequent changes demand a new network architecture which supports future technologies and solves all these issues named as the proposal of networks defined by software. A large amount of data is being generated and through the internet, we interact with the world using our smart devices such as tablets, sensors, and smartphones using the concepts of Internet of Things (IoT). Along with continuous growth and development, there is a continuous heterogenous and ever-increasing demands of services. This leads to a cause of emerging challenge of load balancing of networks for meeting up with highly demanding requirements (e.g., high performance, lower latency, high throughput, and high availability) of IoT and 5G network applications. For meeting up highly increasing demands, various proposal of load balancing techniques comes forward, in which highly dedicated balancers of loads are being required for ever service in some of them, or for every new service, manual recognition of device is required. In the conventional network, on the basis of the local information in the network, load balancing is being established. However, the production of more optimized load balancers and a global view for the network is being contained by SDN controllers. So, these well-known techniques are quite time-consuming, expensive and impractical as well as service types aren’t being considered by various existing load balancing schemes. Through this paper, researchers focus on an SDN based load balancing (SBLB) service, in which minimized response time and maximized resource utilization are being considered for the user on cloud servers. The proposed scheme is being constituted by an application module which runs along with a SDN controller and server pools that connect to the controller through SDN enabled switches. The application module contains a dynamic load balancing module, a monitoring module and a service classification module. All messages are being handled in real time and host pool are being maintained by the Controller. The performance of the proposed scheme has been validated by experimental results. Through various experiments, results are being concluded that usage of SBLB results in significant decrease in average response and reply time.

SDN-Based Load Balancing Service for Cloud Servers

With the continuous growth, heterogeneity, and ever increasing demand of services, load balancing of cloud servers is an emerging challenge to meet highly demanding requirements (e.g., data rates, latency, quality of service) of 5G network applications. Although various load balancing techniques have been proposed, some of these techniques either require installation of dedicated additional load balancers for each service, or manual reconfiguration of the device to handle new services is desired. These techniques are expensive, time-consuming, and impractical. Moreover, most of the existing load balancing schemes do not consider service types. This article presents an SDN-based load balancing (SBLB) service for cloud servers to maximize resource utilization and minimize response time of users. The constituents of the proposed scheme are an application module that runs on top of an SDN controller and server pools that connect to the controller through OpenFlow switches. The application module consists of a service classification module, a dynamic load balancing module, and a monitoring module. The controller handles all messages, manages host pools, and maintains the load of host in real time. Experimental results validate the performance of the proposed scheme. Through experimental results, SBLB demonstrates significant decrease in average response time and reply time.

Fog-Assisted Operational Cost Reduction for Cloud Data Centers

In this paper, we intend to reduce the operational cost of cloud data centers with the help of fog devices, which can avoid the revenue loss due to wide-area network propagation delay and save network bandwidth cost by serving nearby cloud users. Since fog devices may not be owned by a cloud service provider, they should be compensated for serving the requests of cloud users. When taking economical compensation into consideration, the optimal number of requests processed locally by each fog device should be decided. As a result, existing load balancing schemes developed for cloud data centers can not be applied directly and it is very necessary to redesign a cost-ware load balancing algorithm for the fog-cloud system. To achieve the above aim, we first formulate a fog-assisted operational cost minimization problem for the cloud service provider. Then, we design a parallel and distributed load balancing algorithm with low computational complexity based on Proximal Jacobian Alternating Direction Method of Multipliers (PJ-ADMM). Finally, extensive simulation results show the effectiveness of the proposed algorithm.

Guaranteeing Fault-Tolerant Requirement Load Balancing Scheme Based on VM Migration

Virtualization is an important enabling technology for many large data centers and cloud computing environments, and virtual machine (VM) migration plays a key role in the load balancing among the hosts of the data center. However, the existing load balancing schemes based on VM migration have serious influence on the fault-tolerant level of the services in the data center, and thus the reliability of the services cannot be guaranteed. In this paper, a novel guaranteeing fault-tolerant requirement load balancing scheme (GFTLBS) is proposed. GFTLBS migrates the VMs to balance the load without violating the fault-tolerant requirement of all services. The simulation results show that the scheme can guarantee the fault-tolerant requirements of all services while keeping the load balance.

Replica-aided load balancing in overlay networks

In recent years, there have been rapid advances in network infrastructure and technologies for end-user communication. However, because of network dynamics and resource limitation, providing scalable end-user communication services is challenging when the applications are utilized on a large-scale. To address this challenge, a replica-aided load balancing scheme (RALB) is proposed for enabling the nodes in an overlay networks to support the communication applications for a large number of users. This paper makes three unique contributions. First, we study the existing load balancing schemes and identify their weakness in handling time-varying workloads with frequent load fluctuations. Second, we introduce a sophisticated cost model for load balancing cost estimation, which captures the dependencies between the factors (e.g., the load, message number, and link latency). Third, we propose a performance tuning technique to minimize the load balancing cost. The extensive experiments show that RALB effectively reduces the load imbalance and eliminates the load balancing cost when compared to the existing load balancing schemes.