A Probabilistic Analysis of a Leader Election Protocol for Virtual Traffic Lights

Fathollahnejad, Negin; Barbosa, Raul; Karlsson, Johan

doi:10.1109/prdc.2017.56

Cited by 9 publications

(5 citation statements)

References 21 publications

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“…In the process of leader election, the ID value was created randomly without taking into account any other resources. Similarly, in [41], a method for leader selection based on the probabilistic investigation of traffic lights was presented.…”

Section: Related Workmentioning

confidence: 99%

Head Node Selection Algorithm in Cloud Computing Data Center

Kanwal

Iqbal

Irtaza

et al. 2021

Mathematical Problems in Engineering

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Cloud computing provides multiple services such as computational services, data processing, and resource sharing through multiple nodes. These nodes collaborate for all prementioned services in the data center through the head/leader node. This head node is responsible for reliability, higher performance, latency, and deadlock handling and enables the user to access cost-effective computational services. However, the optimal head nodes’ selection is a challenging problem due to consideration of resources such as memory, CPU-MIPS, and bandwidth. The existing methods are monolithic, as they select the head nodes without taking the resources of the nodes. Still, there is a need for the candidate node which can be selected as a head node in case of head node failure. Therefore, in this paper, we proposed a technique, i.e., Head Node Selection Algorithm (HNSA), for optimal head node selection from the data center, which is based on the genetic algorithm (GA). In our proposed method, there are three modules, i.e., initial population generation, head node selection, and candidate node selection. In the first module, we generate the initial population by randomly mapping the task on different servers using a scheduling algorithm. After that, we compute the overall cost and the cost of each node based on resources. In the second module, the best optimal nodes are selected as a head node by applying the genetic operations such as crossover, mutation, and fitness function by considering the available resources. In the selected optimal nodes, one node is chosen as a head node and the other is considered as a candidate node. In the third module, the candidate node becomes the head node in the case of head node failure. The proposed method HNSA is compared against the state-of-the-art algorithms such as Bees Life Algorithm (BLA) and Heterogeneous Earliest Finished Time (HEFT). The simulation analysis shows that the proposed HNSA technique performs better in terms of execution time, memory utilization, service level sgreement (SLA) violation, and energy consumption.

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Section: Related Workmentioning

confidence: 99%

Head Node Selection Algorithm in Cloud Computing Data Center

Kanwal

Iqbal

Irtaza

et al. 2021

Mathematical Problems in Engineering

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“…Surprisingly, there are very few leader selection algorithms designed specifically in the context of vehicular networks applications. [17], [18] proposed leader-selection algorithm for a specific application, known as Virtual Traffic Lights (VTL), though the algorithm designed is in the context of vehicular network, the algorithm is still reactive and doesn't take the aforementioned drawbacks into considerations.…”

Section: Related Workmentioning

confidence: 99%

Leader selection in Vehicular Ad-hoc Networks: a Proactive Approach

Zhang

Jacquemot

Bakirci

et al. 2020

2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

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With the rapid advancement in vehicle-to-vehicle (V2V) communications, there are growing interests in related fields to leverage V2V communications for different applications. A robust leader selection algorithm is required in a number of V2V communications related applications. In this paper, a distributed leader selection algorithm is introduced for vehicular ad-hoc network (VANET) over unreliable V2V communications. The algorithm is simple, light-weighted and tightly integrated with SAE 2735 protocol in vehicular networks. The goal of the algorithm is to provide a robust leader selection method for a group of vehicles to determine a temporary leader locally in very short time, which could benefit a lot of newly proposed applications based on V2V in traffic control and autonomous driving related areas. Theoretical analysis as well as simulation results has verified the convergence time, robustness and other aspects of the algorithm.

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“…For ease of comprehension, the link and crash failure distributions are now reduced to single probabilities, i.e., p l and p c , respectively. The assumption to have identical link failure probabilities for all links is not an uncommon practice in this field of research [13,30,34]. The impact of arbitrary failure distributions on the model are explained in Section 4.5.…”

Section: Notationmentioning

confidence: 99%

Bernoulli Meets PBFT: Modeling BFT Protocols in the Presence of Dynamic Failures

Nischwitz¹,

Esche²,

Tschorsch³

2020

Preprint

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The publication of the pivotal state machine replication protocol PBFT laid the foundation for a large body of BFT protocols. While many successors to PBFT have been developed, there is no general technique to compare these protocols under realistic network conditions such as unreliable links. In this paper, we introduce a probabilistic model for evaluating BFT protocols in the presence of dynamic link and crash failures. Based on modeling techniques from communication theory, the network state of replicas is captured and used to derive the success probability of the protocol execution. To this end, we examine the influence of link and crash failure rates as well as the number of replicas. The model is derived from the communication pattern, making it implementation-independent and facilitating an adaptation to other BFT protocols. The model is validated with a simulation of PBFT and BFT-SMaRt. Further, a comparison in protocol behavior of PBFT, Zyzzyva and SBFT is performed and critical failure thresholds are identified.

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A Probabilistic Analysis of a Leader Election Protocol for Virtual Traffic Lights

Cited by 9 publications

References 21 publications

Head Node Selection Algorithm in Cloud Computing Data Center

Head Node Selection Algorithm in Cloud Computing Data Center

Leader selection in Vehicular Ad-hoc Networks: a Proactive Approach

Bernoulli Meets PBFT: Modeling BFT Protocols in the Presence of Dynamic Failures

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