Handover and Load Balancing for Distributed Network Control: Applications in ITS Message Dissemination

Kaul, Anuj; Li, Xue; Santos, Mateus Augusto Silva; Turletti, Thierry

doi:10.1109/icccn.2018.8487373

Cited by 10 publications

(5 citation statements)

References 12 publications

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“…The work in [18] assigns remote controllers to eNBs accounting for user request rates at the cost of increased propagation time to remote controllers. Additionally, dynamic controller assignment as well as vehicle mobility may lead to control delegation between edge controllers, which has been explored in our previous work [13].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Controller Assignment in Software Defined Internet of Vehicles Through Multi-Agent Deep Reinforcement Learning

Yuan

Neto

Rothenberg

et al. 2021

IEEE Trans. Netw. Serv. Manage.

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Section: Related Workmentioning

confidence: 99%

Dynamic Controller Assignment in Software Defined Internet of Vehicles Through Multi-Agent Deep Reinforcement Learning

Yuan

Neto

Rothenberg

et al. 2021

IEEE Trans. Netw. Serv. Manage.

Self Cite

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“…The controller can derive an optimal association solution based on the traffic load and number of users on each access point (AP). The research presented by Kaul et al proposed load balancing handover solution based on allowing a controller to automatically delegate control of a vehicle to another controller as the vehicle moves. Moreover, Nahida et al developed WLAN architecture based on SDN in which the handover algorithm used the RSSI and load of each AP.…”

Section: Related Work On Handover Solutions For Uvanetmentioning

confidence: 99%

“…The limitations of previous literature studies are basically divided into three points. Firstly, RSSI is not reliable parameters to be used in handover management in urban area because interference and noise degrade the quality of RSSI.…”

Section: Related Work On Handover Solutions For Uvanetmentioning

confidence: 99%

An effective handover management based on SINR and software‐defined network over urban vehicular ad hoc networks

Ahmed

2019

Trans Emerging Tel Tech

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Urban vehicular ad hoc network (UVANET) is a modality of high-topology variation MANET where vehicles travel across constrained layout of the roads and tall buildings, which eventually results in shadowing effects. One of the critical challenges in UVANET is the handover process that happens when a vehicle changes its association with the roadside unit. Urban area suffers from high vehicular density at traffic signals, and vehicle slowdowns caused by speed limits, frequent link disconnection caused by signal attenuation due to obstacles.Thus, it is difficult for UVANET to disseminate the packets to their destinations located in a specified area. This paper presents an effective handover management that calculates the signal-to-interference-plus-noise ratio (SINR) to ultimately determine the optimal cluster head for seamless handover in UVANET. It also utilizes the software-defined network to resolve the problem of handover failure in UVANET. The finding in the experimental results shows that the developed association clustering mechanism based on SINR significantly outperforms the baseline association mechanism. More importantly, it can resolve different types of handover problems that improved the quality of service in terms of throughput, handover latency, packet loss ratio, and handover failure ratio, when compared to the baseline handover mechanisms. Trans Emerging Tel Tech. 2019;30:e3787. wileyonlinelibrary.com/journal/ett FIGURE 1 SDN-based VANET handover management architecture. LOS, line-of-sight; SDN, software-defined network; VANET, vehicular ad hoc network; V2R, vehicle-to-roadside unit; V2V, vehicle-to-vehicle the efficiency of communication between vehicles in UVANET. Essentially, the communication in UVANET based on software-defined network (SDN) can be classified into two main types: vehicle-to-vehicle (V2V) and vehicle-to-roadside unit (V2R). 4,5The controller base station has the role of SDN controller, which can guide the vehicles to make handover decisions based on several metrics such as vehicles speed and direction, location of vehicles, received signal strength indication (RSSI), and roadside unit (RSU) congestion. Handover in UVANET is a method to change the management of operative communication from one RSU to another. In seamless handover, the operative communication between vehicles should be continued while they are mobile from one RSU to another without perceptible latency. Many literature research studies proposed various solutions for handover in UVANET; however, they did not revoke the crucial difficulties of handover including quality of connection reduction and degradation of the QoS performance of the UVANET. Moreover, the characteristic of UVANET can cause enormous types of unnecessary handovers, which consumes more energy in order to control traffic congestion and this eventually leads to handover failure. The most crucial problems that cause handover failure in UVANET primarily includes mobility, communications jamming and interference, coverage hole, and data traffic congesti...

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“…Therefore, the computing power needs to increase to reduce the latency. By performing this, power consumption will become a big problem with BS/lightweight infrastructure, but recently, most research has discussed the load balance with the number of VUE and power consumption [ 20 , 21 , 22 , 23 ]. In [ 20 ], they pointed out that growing up with a number of smartphones is a common experience; at the same time, the service requests also become more complex.…”

Section: Introductionmentioning

confidence: 99%

“…It is a challenge to deploy BS/lightweight infrastructure to achieve a win–win for the operator and UE, but they only focus on throughput and signal strength. In [ 21 ], they use the roadside unit (RSU) and receive signal strength to perform the baseline for handover in VANET. These two papers show how load balance is important for BS, and they also defined the loading rate with BS.…”

Section: Introductionmentioning

confidence: 99%

The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle

Huang

Chen

et al. 2022

Sensors

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With the low latency, high transmission rate, and high reliability provided by the fifth-generation mobile communication network (5G), many applications requiring ultra-low latency and high reliability (uRLLC) have become a hot research topic. Among these issues, the most important is the Internet of Vehicles (IoV). To maintain the safety of vehicle drivers and road conditions, the IoV can transmit through sensors or infrastructure to maintain communication quality and transmission. However, because 5G uses millimeter waves for transmission, a large number of base stations (BS) or lightweight infrastructure will be built in 5G, which will make the overall environment more complex than 4G. The lightweight infrastructure also has to be considered together. For these reasons, in 5G, there are two mechanisms for handover, horizontal, and vertical handover; hence, it must be discussed how to handle handover to obtain the best performance for the whole network. In this paper, to address handover selection, we consider delay time, energy efficiency, load balancing, and energy consumption and formulate it as a multi-objective optimization (MOO) problem. At the same time, we propose the handover of the mobile management mechanism based on location prediction combined with heuristic algorithms. The results show that our proposed mechanism is better than the distance-based one for energy efficiency, load, and latency. It optimizes by more than about 20% at most.

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Handover and Load Balancing for Distributed Network Control: Applications in ITS Message Dissemination

Cited by 10 publications

References 12 publications

Dynamic Controller Assignment in Software Defined Internet of Vehicles Through Multi-Agent Deep Reinforcement Learning

Dynamic Controller Assignment in Software Defined Internet of Vehicles Through Multi-Agent Deep Reinforcement Learning

An effective handover management based on SINR and software‐defined network over urban vehicular ad hoc networks

The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle

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