LPLB: A Novel Approach for Loop Prevention and Load Balancing in Ethernet Ring Networks

Traditional Ethernet networks use the rapid spanning tree protocol (RSTP) or the enhanced RSTP (eRSTP) to ensure a loop-free topology and provide redundant links as backup paths in case an active link has failed. However, when a failure occurs, the RSTP/eRSTP require a significant amount of reconfiguration time in order to find an alternative path. The RSTP/eRSTP are also limited by the number of nodes in a ring network, and their performance degrade when the number of nodes increases; the media redundancy protocol (MRP), which is used in industrial networks, has the same issues. In this paper, we introduce a new algorithm, called loop prevention and fast recovery (LPFR), which can be applied to Ethernet ring networks to provide a loop-free topology. When a failure occurs, LPFR requires only a very short amount of time to switch to an alternative path. LPFR needs a maximum of 6.1 ms for recovery time, versus ＜ 100 ms for the RSTP/eRSTP in a ring size of 20 nodes and ＜ 200 ms for the MRP in a ring size of 50 nodes. The LPFR offers a reduction in recovery time of up to 93.9 % compared to the RSTP/eRSTP, and 96.9 % compared to the MRP. However, in most cases, LPFR requires zero recovery time for such switching. In addition, in most situations, no frames are lost when a node switches to an alternative path. Unlike the RSTP/eRSTP and MRP, LPFR provides a better way for distributing the sent traffic among network links, which in turn improves network performance, reduces the probability of bottleneck occurrences, and reduces the frame latency between the source and the destination. This is because LPFR always sends the frame through the fastest path. The LPFR algorithm can run on a wide variety of ring sizes, which is not the case for the RSTP/eRSTP and MRP. Finally, the LPFR will use the Ethernet standard frame layout without any modifications or changes. This will allow all of the standard Ethernet devices and networks to be directly integrated into the LPFR networks without any proxies.

The traditional load balancers suffer from inflexibility and difficulty to manage network flows and they are very expensive hardware dedicated devices. Software-Defined Networking (SDN) gives a promising solution for traditional load balancer limitations. SDN is a new paradigm which enables programmability and centralized control for the network which offers inexpensive and flexible solutions. This paper aims to develop a new load balancing approach using SDN. We propose a “Bandwidth-based” load balancing approach that distributes the network requests among multiple servers based on the servers' bandwidth consumption. The performance of the proposed scheme is evaluated and compared with different load balancing schemes (Round-robin and Connections-based) under a mininet emulation and a Raspberry Pi-based implementation. Emulation and hardware implementation results reveal a better performance of the proposed approach compared to the two reference schemes.

Wireless sensor networks (WSNs) consist of spatially distributed low power sensor nodes and gateways along with sink to monitor physical or environmental conditions. In cluster-based WSNs, the Cluster Head is treated as the gateway and gateways perform the multiple activities, such as data gathering, aggregation, and transmission etc. Due to improper clustering some sensor nodes and gateways are heavily loaded and dies early. This decreases lifetime of the network. Moreover, sensor nodes and gateways are constrained by energy, processing power and memory. Hence, to design an efficient clustering is a key challenge in WSNs. To solve this problem, in this paper we proposed (1) a clustering algorithm based on the shuffled complex evolution of particle swarm optimization (SCE-PSO) (2) a novel fitness function by considering mean cluster distance, gateways load and number of heavily loaded gateways in the network. The experimental results are compared with other state-of-the-art load balancing approaches, like score based load balancing, node local density load balancing, simple genetic algorithm, novel genetic algorithm. The experimental results shows that the proposed SCE-PSO based clustering algorithm enhanced WSNs lifetime when compared to other load balancing approaches. Also, the proposed SCE-PSO outperformed in terms of load balancing, execution time, energy consumption metrics when compared to other existing methods.

No abstract available.

With the rapid development of Internet of Things (IoT) technology, the number of nodes in wireless sensor networks (WSNs) is explosively increasing, and the scale of network is increased gradually. Traditional single-layer non-clustering network is no longer suitable for current WSNs, which results in high maintenance cost and fast deterioration of network performance. By analyzing the impact of existing static and dynamic clustering schemes on network performance, it is concluded that additional factors need to be considered to improve the overall performance of the network, such as residual energy of nodes, number of neighbor nodes and load balancing. Therefore, an adaptive multi-layer clustering networking strategy based on capability weights is proposed. Based on the real-time changes of each cluster density, node load and residual energy, the node capacity weights are updated dynamically according to the actual network performance, then the cluster heads are renewed adaptively. By comparing the performance metrics in the experiments, proposed strategy can effectively reduce the load of key nodes such as cluster head, and improves the network performance metrics such as average transmission delay, average transmission hops and load balancing.

DHT networks based on consistent hashing functions have an inherent load uneven distribution problem. The objective of DHT load balancing is to balance the workload of the network nodes in proportion to their capacity so as to eliminate traffic bottleneck. It is challenging because of the dynamism nature of DHT networks and time-varying load characteristics. In this paper, we present a hash-based proximity clustering approach for load balancing in heterogeneity DHTs. In the approach, DHT nodes are classified as regular nodes and supernodes according to their computing and networking capacities. Regular nodes are grouped and associated with supernodes via consistent hashing of their physical proximity information on the Internet. The supernodes form a self-organized and churn resilient auxiliary network for load balancing. The hierarchical structure facilitates the design and implementation of a locality-aware randomized load balancing algorithm. The algorithm introduces a factor of randomness in the load balancing processes in a range of neighborhood so as to deal with both the proximity and dynamism. Simulation results show the superiority of the approach, in comparison with a number of other DHT load balancing algorithms. The approach performs no worse than existing proximity-aware algorithms and exhibits strong resilience to the effect of churn. It also greatly reduces the overhead of resilient randomized load balancing algorithms due to the use of proximity information.

We proposed a new load balancing mechanism, called LBAM (load balancing based on pseudo-anycast and pseudo-mobility in IPv6), by which sessions can be distributed across a pool of servers for maximum performance. Load balancing is needed in many fields, such as Web servers, FTP server and NAT gateway, and there exist several approaches for load balancing. However, current approaches have problems such as poor scalability, inability to balance session flow, long latency time, and topological constraint on server pools. In this paper, we describe how LBAM works in principle without the above problems. We also present our simulation work using NS-2 and discuss performance comparison between LBAM and other load balancing mechanisms. The results show that LBAM has a very advanced performance and scalability. Finally, the ubiquitous applications of LBAM in NGI (next generation Internet) are presented.

A computer network can be defined as many computing devices connected via a communication medium like the internet. Computer network development has proposed how humans and devices communicate today. These networks have improved, facilitated, and made conventional forms of communication easier. However, it has also led to uptick in-network threats and assaults. In 2022, the global market for information technology is expected to reach $170.4 billion. However, in contrast, 95% of cyber security threats globally are caused by human action. These networks may be utilized in several control systems, such as home-automation, chemical and physical assault detection, intrusion detection, and environmental monitoring. The proposed literature review presents a wide range of information on Wireless Social Networks (WSNs) and Internet of Things (IoT) frameworks. The aim is first to be aware of the existing issues (issues with traditional methods) and network attacks on WSN and IoT systems and how to defend them. The second is to review the novel work in the domain and find its limitations. The goal is to identify the area’s primary gray field or current research divide to enable others to address the range. Finally, we concluded that configuration. Message Rapid Spanning Tree Protocol (RSTP) messages have higher efficiency in network performance degradation than alternative Bridge Data Unit Protocol (BPDU) forms. The research divides our future research into solutions and newly developed techniques that can assist in completing the lacking component. In this research, we have selected articles from 2015 to 2021 to provide users with a comprehensive literature overview.

Exponential growth in the demand for network capacity has led to extensive research on advanced cellular network technology. A heterogeneous network in which traditional well-planned macro cell deployment is overlaid by small-scale unplanned base stations is one effective solution for next-generation networks. However, the cell association techniques currently used in macro-only cellular networks are not suitable for next-generation heterogeneous networks. Finding effective methods to handle the cell association problem in this new type of network is a hot topic of research in this field. This paper provides an overview of the cell association problem in heterogeneous networks and discusses the main issues that need to be addressed by an efficient cell association technique in order to maximize the network throughput. It has been shown that an efficient cell association scheme in heterogeneous networks must balance the load among different cells while minimizing the inter-cell interference at the same time. Jointly considering these two objectives is a challenge currently being investigated by researchers. An overview on load balancing and interference management in heterogeneous networks is provided in this paper. A review of the existing literature shows that there is a need for an efficient distributed solution in which load balancing approaches are observed and at the same time users prone to harmful interference are protected. A framework for modeling the heterogeneity of this type of network is presented, a simulation is performed in order to verify the effects of different parameters, and, finally, the problem is formulated. Future research directions are also provided in the paper.

The wireless networks have a very bright future in networks and communications because of which they have taken a high interest of the researchers. As the users increased the purpose to use MANETs, they also became more diverse and wide due to which better performance is needed in MANETs. QoS is needed for applications for an efficient communication and load balancing is a feature in the routing protocol that can help in a better use of the resources and can help to increase the performance of the network. We propose a new approach for load balancing in AOMDV routing protocol for MANETs that can enhance the network performance by selecting paths using the temporal load on the intermediate nodes and by distributing the load amongst the free nodes while transmission of data, which is proved by simulations in NS-2.

Lots of real-time applications of wireless sensor network requires maximization of network lifetime. Many clustering approaches have been proposed but they suffer from uneven clusters which eventually make the network load unbalanced. In this work, we have suggested a two-stage energy proficient balanced clustering method which will balance the network load. We considered the parameters residual energy, intra-cluster cost, inter cluster cost, communication distance. We compared our proposed protocol with a recent clustering protocol CH-leach. Simulation results show that the proposed algorithm achieves better load balance, increase the network lifetime with energy balance clusters and lower node death rate.

In this paper we study the problem of dynamic load balancing in broadcast WDM networks by retuning a subset of transceivers in response to changes in the overall traffic pattern. Assuming an existing wavelength assignment and some information regarding the new traffic demands, we present two approaches to obtaining a new wavelength assignment such that (a) the new traffic load is balanced across the channels, and (b) the number of transceivers that need to be retuned is minimized. The latter objective is motivated by the fact that tunable transceivers take a non-negligible amount of time to switch between wavelengths during which parts of the network are unavailable for normal operation. Our main contribution is a new approximation algorithm for the load balancing problem that provides for tradeoff selection, using a single parameter, between the two conflicting goals. This algorithm leads to a scalable approach to reconfiguring the network since, in addition to providing guarantees in terms of load balancing, the expected number of retunings scales with the number of channels, not the number of nodes in the network.

The tremendous advancement in distributed computing and Internet of Things (IoT) applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud computing. Thus, suitable and effective applications could be performed to satisfy the applications’ latency requirement. Resource allocation techniques are essential aspects of fog networks which prevent unbalanced load distribution. Effective resource management techniques can improve the quality of service metrics. Due to the limited and heterogeneous resources available within the fog infrastructure, the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT network. There has been limited research on resource management strategies in fog networks in recent years, and a limited systematic review has been done to compile these studies. This article focuses on current developments in resource allocation strategies for fog-IoT networks. A systematic review of resource allocation techniques with the key objective of enhancing QoS is provided. Steps involved in conducting this systematic literature review include developing research goals, accessing studies, categorizing and critically analysing the studies. The resource management approaches engaged in this article are load balancing and task offloading techniques. For the load balancing approach, a brief survey of recent work done according to their sub-categories, including stochastic, probabilistic/statistic, graph theory and hybrid techniques is provided whereas for task offloading, the survey is performed according to the destination of task offloading. Efficient load balancing and task-offloading approaches contribute significantly to resource management, and tremendous effort has been put into this critical topic. Thus, this survey presents an overview of these extents and a comparative analysis. Finally, the study discusses ongoing research issues and potential future directions for developing effective management resource allocation techniques.

Several approaches for load balancing in distributed systems were introduced, however, most of them require prior knowledge of the environments operation conditions and/or constant monitoring of these conditions at run time. That allows the applications to adjust the load and redistribute the tasks when necessary. These techniques were designed with the assumption that there is no high communication delay in discovering dynamic load behaviors for the rescheduling purposes. This paper proposes a new delay-tolerant dynamic load balancing technique that can be used effectively for reducing the execution time of some distributed tasks while minimizing the control overhead. Such tasks include downloading large files from replicated FTP servers and executing parallel applications on multiple independent distributed servers. This technique we call DDOps (Dual Direction Operations) allows the parallel/distributed application to make use of available resources efficiently while not requiring any significant control overhead. In our approach, load balancing is automatically inherent from the technique. Since the tasks are handled from opposite directions, processing will continue until the workers meet at some point which indicates all tasks are done. Thus DDOps is most suitable for non-dedicated heterogeneous distributed environments where resources vary in specifications, locations, and operating conditions. The experimental results in file download and parallel computations all show how efficient DDOps is and how well it balances the load among the different tasks.

Routing and wavelength assignment (RWA) is one of the key issues in the wavelength-routed optical networks. Although some RWA algorithms have been well performed to meet the need of certain networks requirement, they usually neglect the performance of the whole networks, especially the load balancing of the whole networks. This is quite likely to lead to some links bearing excessive ligthpaths and traffic load, while other links being at an idle state. In this paper, the load distribution vector ( LDV ) is introduced to describe the links load of the networks firstly. Then by means of minimizing the LDV of the networks, the load balancing of the whole networks is tried to improve. Based on this, a heuristic load balancing (HLB) strategy is presented. Moreover, a novel RWA algorithm adopting the heuristic load balancing strategy is developed, as well as two other RWA algorithms adopting other load balancing strategies. At last, the simulations of the three RWA algorithms with different load balancing strategies are done for comparison on the basis of both the regular topology and the irregular topology networks. The simulation results show that the key performance parameters such as the average variance of links, the maximum link load and the number of established lightpath are improved by means of our novel RWA algorithm with the heuristic load balancing strategy.