A comprehensive survey of load balancing techniques in software-defined network

Wireless Sensor Networks (WSNs) are formed by a large collection of power-conscious wireless-capable sensors without the support of pre-existing infrastructure, possibly by unplanned deployment. With a sheer number of sensor nodes, their unattended deployment and hostile environment very often preclude reliance on physical configuration or physical topology. It is, therefore, often necessary to depend on the logical topology. Logical topologies govern how a sensor node communicates with other nodes in the network. In this way, logical topologies play a vital role for resource-constraint sensor networks. It is thus more intuitive to approach the constraint minimizing problems from (logical) topological point of view. Hence, this paper aims to study the logical topologies of WSNs. In doing so, a set of performance metrics is identified first. We identify various logical topologies from different application protocols of WSNs, and then compare the topologies using the set of performance metrics.

https://www.mdpi.com/1424-8220/12/11/14887/pdf

A Qualitative Comparison of Different Logical Topologies for Wireless Sensor Networks

The space–air–ground integrated network (SAGIN) is considered to be a significant framework for realizing the vision of “6G intelligent connection of all things.” A typical SAGIN consists of three parts: a space-based network composed of various orbiting satellites, an air-based network composed of aircraft, and a traditional ground-based network. Considering the cost of satellite launch, the network needs to be flexible and controllable. In order to ensure that the ground can handle satellite anomalies in real time by program, it is necessary to introduce in-orbit programmable networks, such as the software-defined network (SDN). In the network management architecture, if the controller plane in the SDN adopts the flat management scheme, the expansion of the control plane is limited due to the low efficiency of data synchronization among controllers. Compared with controller deployments on terrestrial networks, multicontroller deployments in the SAGIN face the following problems: the dynamic change of the satellite network topology, the large-scale network nodes, the increase or decrease in the number of aerial vehicles, and the unbalanced distribution of ground users. Therefore, it is of great significance to study how to optimize the deployment of multiple controllers in the SDN-enabled SAGIN. This article introduces an SDN into the SAGIN and designs a hierarchical domain-based SDN-enabled SAGIN architecture. A multicontroller deployment strategy for the hierarchical domain-based SDN-enabled SAGIN is proposed. First, we divide the SDN control plane into two layers, i.e., the primary controller layer is deployed on the ground network and the secondary on the space-based network. The SDN data plane is composed of space-based, air-based, and ground-based networks. Second, considering the average network delay and the controller load, a multiobjective optimization model is constructed. To determine the number of controllers and the relative positions of switch nodes and controllers, the clustering algorithm based on k-means is adopted to initially divide the data plane. Finally, to improve the global search ability of the algorithm, a multiobjective optimization algorithm based on a genetic algorithm is adopted. The simulation results show that the proposed strategy is effective in reducing the average network delay and improving the controller load balance. Compared to other algorithms, the average network delay is reduced by 13.3% and the controller load is improved by 10.33%.

Hierarchical Domain-Based Multicontroller Deployment Strategy in SDN-Enabled Space–Air–Ground Integrated Network

The space–air–ground Integrated Network (SAGIN) is considered to be a significant framework for realizing the vision of “6G intelligent connection of all things”. The birth of 6G SAGIN also brings many problems, such as ultra-dense dense networks, leading to a decrease in the efficiency of traditional flat network management, and traditional satellite networking solidified network functions, etc. Therefore, combining the 6G SAGIN network with the software-defined network (SDN) is an excellent solution. However, the satellite network topology changes dynamically and the ground user unbalanced distribution leads to the unbalanced load of the SDN controller, which further leads to the increased communication delay and throughput drop, etc. For these problems, a hierarchical multi-controller deployment strategy of an SDN-based 6G SAGIN is proposed. Firstly, the delay model of the network, the load model of the SDN controller, and a loss value as a measure of whether the network delay and controller load are optimal are defined. Then, using the distribution relationship between the SDN controller and the switch node as the solution space, and taking the loss value as the optimization goal, a multi-controller deployment strategy based on the simulated annealing algorithm is used to search for the optimal solution space. Lastly, considering the network topology changes dynamically and the SDN controller imbalance, a switch migration strategy oriented toward load balancing is proposed. We aimed to determine the controller deployment plan through the above two points, balance the controller load, and then improve the network performance. The simulation results show that the controller load is increased by about 7.71% compared to OCLDS, and the running time is increased by 17.7% compared to n-k-means.

/pdf/multi-controller-deployment-in-sdn-enabled-6g-space-air-2cf2aqkf.pdf

Multi-Controller Deployment in SDN-Enabled 6G Space-Air-Ground Integrated Network

The Internet of things (IoT) extends the Internet space by allowing smart things to sense and/or interact with the physical environment and communicate with other physical objects (or things) around us. In IoT, sensors, actuators, smart devices, cameras, protocols, and cloud services are used to support many intelligent applications such as environmental monitoring, traffic monitoring, remote monitoring of patients, security surveillance, and smart home automation. To optimize the usage of an IoT network, certain challenges must be addressed such as energy constraints, scalability, reliability, heterogeneity, security, privacy, routing, quality of service (QoS), and congestion. To avoid congestion in IoT, efficient load balancing (LB) is needed for distributing traffic loads among different routes. To this end, this survey presents the IoT architectures and the networking paradigms (i.e., edge–fog–cloud paradigms) adopted in these architectures. Then, it analyzes and compares previous related surveys on LB in the IoT. It reviews and classifies dynamic LB techniques in the IoT for cloud and edge/fog networks. Lastly, it presents some lessons learned and open research issues.

/pdf/dynamic-load-balancing-techniques-in-the-iot-a-review-jwoo3ck1.pdf

Dynamic Load Balancing Techniques in the IoT: A Review

Energy consumption is a key design criterion for the routing protocols in Wireless Sensor Networks (WSN). It is very important when designing a WSN to think of a routing protocol that makes the best use of the severely limited resources. Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. This paper proposes a routing protocol that we called REBMR: Rumor as an Energy-Balancing Multipath Routing Protocol. REBMR aims at lower energy consumption than algorithms that flood the whole network with query or event messages.

Rumor as an Energy-Balancing Multipath Routing Protocol for Wireless Sensor Networks

With the proliferation of wireless sensor networks, it has become expedient to secure the communication links between two sensor nodes. Due to the resource constraints of wireless sensor networks, traditional key management schemes such as the Diffie-Hellman and public key schemes are not applicable in wireless sensor networks. Our work seeks to improve on the Pairwise scheme and the Random pairwise scheme by Chang, Perrig and Song[6].Compared with the pairwise scheme, our scheme significantly reduces the memory and computational overheads in the pairwise scheme while maintaining the same resilience against node capture and connectivity and it has better connectivity than that of Chan et al[6] and other group key management schemes such as [14]and [16].

Groupwise Pairwise Scheme for Wireless Sensor Networks

In the current technology driven era, the use of devices that connect to the internet has increased significantly. Consequently, there has been a significant increase in internet traffic. Some of the challenges that arise from the increased traffic include, but are not limited to, multiple clients on a single server (which can result in denial of service (DoS)), difficulty in network scalability, and poor service availability. One of the solutions proposed in literature, to mitigate these, is the use of multiple servers with a load balancer. Despite their common use, load balancers, have shown to have some disadvantages, like being vendor specific and non-programmable. To address these disadvantages and improve internet traffic, there has been a paradigm shift which resulted in the introduction of software defined networking (SDN). SDN allows for load balancers that are programmable and provides the flexibility for one to design and implement own load balancing strategies. In this survey, we highlight the key elements of SDN and OpenFlow technology and their effect on load balancing. We provide an overview of the various load balancing schemes in SDN. The overview is based on research challenges, existing solutions, and we give possible future research directions. A summary of emulators/mathematical tools commonly used in the design of intelligent load balancing SDN algorithms is provided. Finally, we outline the performance metrics used to evaluate the algorithms.

/pdf/intelligent-load-balancing-techniques-in-software-defined-2utsblej6o.pdf

Intelligent Load Balancing Techniques in Software Defined Networks: A Survey

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Papers

Rumor as an Energy-Balancing Multipath Routing Protocol for Wireless Sensor Networks

Groupwise Pairwise Scheme for Wireless Sensor Networks

Intelligent Load Balancing Techniques in Software Defined Networks: A Survey