A revised BROGO algorithm for leader election in wireless sensor and IoT networks

Bounceur, Ahcène; Bezoui, Madani; Euler, Reinhardt; Lalem, Farid; Lounis, Massinissa

doi:10.1109/icsens.2017.8234400

Cited by 6 publications

(6 citation statements)

References 15 publications

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“…Tree-based LE algorithms in IoT are primarily concerned with constructing MST in a distributed fashion. To achieve this objective, a few algorithms are proposed in the literature [9] [6] [8]. These algorithms usually assume that each user node is identified by its unique identifier (e.g., id which is an integer number).…”

Section: Leader Election In Iotmentioning

confidence: 99%

“…The MFA algorithm proposed in [8] exploits the tree-based broadcast technique to elect a leader node. This algorithm uses a few steps to find the leader node with the minimum x-coordinate in the network.…”

Section: Minimum Finding Algorithm (Mfa)mentioning

confidence: 99%

“…The Local Minima Finding Algorithm (LMF) algorithm [8] uses the same principle as the MinFind algorithm to find the local minimum in the network, which indicates the node having no neighbor. However, this algorithm allows nodes to send their coordinates only once, and the decision to determine the local minimum takes place after a node has collected x-coordinate messages for all of its neighboring nodes.…”

Section: Dotromentioning

confidence: 99%

“…The DoTRO algorithm [8] first uses the LMF algorithm to find the local minima in the network. After that, each local minima node initiates the flooding process in order to route its value over the tree.…”

Section: Dotromentioning

confidence: 99%

“…To overcome the reliability issue of the BROGO algorithm, a revised BROGO algorithm with the same message complexity as BROGO is proposed in [8], which is based on the WBS (Wait-Before-Starting) concept proposed in [7]. They also assume the minimum value for election purposes.…”

Section: Revised Brogomentioning

confidence: 99%

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Leader Election in the Internet of Things: Challenges and Opportunities

Rahman

2019

Preprint

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The different functions of a leader node in Ad hoc networks, particularly in Wireless Sensor Networks (WSNs) and Internet of Things (IoT) include generation of keys for encryption/decryption, finding a node with minimum energy or node located in an extreme side of the network. One essential application of IoT is to monitor any dangerous, sensitive or non-accessible site. Such type of application requires the election of a leader located on the extreme left of the network. Indeed, one can then use any leader election (LE) algorithm to find this node, and then start the process of finding its boundary nodes. However, the chosen algorithm must be fault-tolerant and robust since the detection of a node failure under such circumstances becomes impossible. This paper surveys the most significant work performed in this direction, highlights the challenges and proposes possible extensions.

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Section: Leader Election In Iotmentioning

confidence: 99%

Section: Minimum Finding Algorithm (Mfa)mentioning

confidence: 99%

Section: Dotromentioning

confidence: 99%

Section: Dotromentioning

confidence: 99%

Section: Revised Brogomentioning

confidence: 99%

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