Enhancing the performance of futurewireless networks with software-defined networking

Feng, Mingjie; Mao, Shiwen; Jiang, Tao

doi:10.1631/fitee.1500336

Cited by 18 publications

(12 citation statements)

References 81 publications

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“…They considered the point-to-point method in their scheme for a source node to build a route to the destination node and exchange information in the network. Feng et al [31] proposed the software-defined wireless network (SDWN) scheme to address the issue of load balancing in WSNs through a centralized controller. Hamrioui et al [32] proposed the Load Balancing Algorithm for IoT devices, which is known as LBA-le routing protocol.…”

Section: Literature Reviewmentioning

confidence: 99%

An Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks to Maximize Their Lifespan in an Operational Environment

et al. 2020

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Owing to the limited resources of sensor nodes, we propose an efficient hybrid routing scheme using a dynamic cluster-based static routing protocol (DCBSRP), leveraging the ad hoc on-demand distance vector (AODV) routing protocol and low-energy adaptive clustering hierarchy (LEACH) protocol. In the proposed scheme, the cluster head (CH) nodes are formed dynamically for a fixed interval, whereas static routing is applied in the designated clusters by utilizing the AODV routing protocol. The static routing condition of the proposed scheme limits all connected nodes of the cluster for a defined interval of time (T) to share their collected information through a specific CH node. Once the time (T) interval is completed, all ordinary nodes connected with the specific CH are released and they are free to advertise their CH candidateship within the network. Likewise, the node receiving the maximum number of route replies (RREPs) is selected as the next CH node in the vicinity of deployed sensor nodes. However, with the DCBSRP protocol, the recently selected CH node does not advertise its candidateship for five consecutive cycles and acts as an ordinary node. The simulation result shows significant improvement in the lifetime and participation of ordinary nodes in the network until the end-stage of the network. In the proposed scheme, the participation of ordinary nodes in the network is 95.9 %, which not only balances load between participating nodes but also improves the network lifetime in the presence of field-proven schemes. Moreover, the simulation results show an out-performance of rival schemes in terms of communication cost, end to end delay, throughput, packet lost ratio, and energy consumption.

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Section: Literature Reviewmentioning

confidence: 99%

An Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks to Maximize Their Lifespan in an Operational Environment

et al. 2020

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“…However, networking systems have gradually begun to evolve dynamically towards service-oriented architectures that break the chains of an outmoded dependence on monolithic network stacks and conventional hardware advancements. This change has been the objective pursued by Software-Defined Networking (SDN), which introduced a management architecture characterized by the decoupling of the control and data planes across various degrees of centralisation [1,2], thus demonstrating that traditional approaches to network management are no longer adequate. This is especially true when it comes to wireless networks, where the level of complexity, which is due to their error-prone nature, longer delays, and the inefficient and inflexible use of resources, requires the use of advanced network management policies.…”

Section: Introductionmentioning

confidence: 99%

Adaptive ML-Based Frame Length Optimisation in Enterprise SD-WLANs

2020

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Software-Defined Networking (SDN) is gaining a lot of traction in wireless systems with several practical implementations and numerous proposals being made. Despite instigating a shift from monolithic network architectures towards more modulated operations, automated network management requires the ability to extract, utilise and improve knowledge over time. Beyond simply scrutinizing data, Machine Learning (ML) is evolving from a simple tool applied in networking to an active component in what is known as Knowledge-Defined Networking (KDN). This work discusses the inclusion of ML techniques in the specific case of Software-Defined Wireless Local Area Networks (SD-WLANs), paying particular attention to the frame length optimization problem. With this in mind, we propose an adaptive ML-based approach for frame size selection on a per-user basis by taking into account both specific channel conditions and global performance indicators. By relying on standard frame aggregation mechanisms, the model can be seamlessly embedded into any Enterprise SD-WLAN by obtaining the data needed from the control plane, and then returning the output back to this in order to efficiently adapt the frame size to the needs of each user. Our approach has been gauged by analysing a multitude of scenarios, with the results showing an average improvement of 18.36% in goodput over standard aggregation mechanisms.

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“…This system informs the commander about the situation and health status of the soldiers so that the commander could dispatch the aids group, if necessary, and the commands could be given on time. Saving the information about all soldiers and analyzing this data can improve the tactics …”

Section: Introductionmentioning

confidence: 99%

Prolong network lifetime and improve efficiency in WSN‐UAV systems using new clustering parameters and CSMA modification

Tarighi

Farajzadeh

Hematkhah

2020

Int J Communication

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Since unmanned aerial vehicles (UAVs) have been introduced as mobile nodes for data gathering, wireless sensor networks (WSNs) have progressed considerably. The resulting WSN-UAV systems are employed for emergency applications and also for remote monitoring purposes. WSN-UAV systems yield an optimum data gathering method using the WSN. In the proposed method, the nodes' data are transferred using a remotely operated vehicle (drone) rather than the conventional data transferring methods like the direct and hop-to-hop data transmission approaches. Then, the gathered data are delivered in the pre-determined destination point. WSN-UAV systems, in fact, are a special case of the systems with the mobile sink in which the sink path is previously specified and controlled. In this paper, the effects of clustering parameters on the WSNs are studied; then, the network's lifetime is prolonged by applying some parameters. In addition, the network's performance is enhanced to some extent by assigning some changes in the media access control (MAC) layer. Also, the effect of drone's path pattern on the lifetime of the network is studied.clustering, MAC, mobile sink, unmanned aerial vehicle (UAV), wireless sensor network (WSN), WSN-UAV

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Enhancing the performance of futurewireless networks with software-defined networking

Cited by 18 publications

References 81 publications

An Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks to Maximize Their Lifespan in an Operational Environment

An Energy Proficient Load Balancing Routing Scheme for Wireless Sensor Networks to Maximize Their Lifespan in an Operational Environment

Adaptive ML-Based Frame Length Optimisation in Enterprise SD-WLANs

Prolong network lifetime and improve efficiency in WSN‐UAV systems using new clustering parameters and CSMA modification

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