FrogSim: distributed graph coloring in wireless ad hoc networks

Hernández, Hugo; Blum, Christian

doi:10.1007/s11235-013-9776-0

Cited by 13 publications

(3 citation statements)

References 17 publications

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“…To prove these results, we model the correlations in sensor activity as edge weights in a graph and different transmission patterns as colors, and show that the coordination problem with deterministic strategies is an instance of a slightly modified Weighted Graph Coloring Problem (WGCP) [10], which is a well-known NP-hard problem. Distributed solutions to the WGCP exist [11], and have been used in communications scenarios [12], but they either require signaling between the nodes or more extensive knowledge of the results of each configuration. On the other hand, the problem we face is due to the extremely limited signaling, as the only information available to the sensors is an acknowledgment (or lack thereof) in case of correct packet reception.…”

Section: Introductionmentioning

confidence: 99%

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

Haque¹,

Chandak²,

Chiariotti³

et al. 2022

Preprint

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The rapid development of Industrial Internet of Things (IIoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited resources. In this work, we define a deceptively simple novel problem that can arise in these scenarios, in which a set of sensors need to communicate a joint observation. This observation is shared by a random subset of the nodes, which need to propagate it to the rest of the network, but coordination is complex: as signaling constraints require the use of random access schemes over shared channels, each sensor needs to implicitly coordinate with others with the same observation, so that at least one of the transmissions gets through without collisions. Unlike the existing medium access control schemes, the goal here is not to maximize total goodput, but rather to make sure that the shared message gets through, regardless of the sender. The lack of any signaling, aside from an acknowledgment or lack thereof from the rest of the network, makes determining the optimal collective transmission strategy a significant challenge. We analyze this coordination problem theoretically, prove its hardness, and provide low-complexity solutions. While a lowcomplexity clustering-based approach is shown to provide nearoptimal performance in certain special cases, for the general scenarios, we model each sensor as a multi-armed bandit (MAB), and provide a learning-based solution. Numerical results show the effectiveness of this approach in a variety of cases.

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Section: Introductionmentioning

confidence: 99%

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

Haque¹,

Chandak²,

Chiariotti³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The coordination problem with deterministic strategies is an instance of a slightly modified weighted graph coloring problem (WGCP) [10], which is a well-known NP-hard problem. Distributed solutions to the WGCP exist [11], and have been used in communications scenarios [12], but they either require signaling between the nodes or more extensive shared feedback. Our scenario allows for extremely limited signaling, as the sensors only receive an acknowledgment (ACK) in case of correct packet reception.…”

Section: Introductionmentioning

confidence: 99%

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

et al. 2022

View full text Add to dashboard Cite

The rapid development of Internet of Things (IoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited resources. In this work, we define a novel problem that can arise in these scenarios, in which a set of sensors need to communicate a joint observation. This observation is shared by a random subset of the nodes, which need to propagate it to the rest of the network, but coordination is complex: as signaling constraints require the use of random access schemes over shared channels, sensors need to implicitly coordinate, so that at least one transmission gets through without collisions. Unlike the majority of existing medium access schemes, the goal is to make sure that the shared message gets through, regardless of the sender. We analyze this coordination problem theoretically and provide low-complexity solutions. While a clustering-based approach is near-optimal if the sensors have prior knowledge, we provide a distributed multi-armed bandit (MAB) solution for the more general case and validate it by simulation.

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“…The evolutionary operators should improve the near-optimal solution obtained from the existing methods [11,22,[25][26][27][57][58][59].…”

mentioning

confidence: 99%

Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem

Marappan

Sethumadhavan

2020

Mathematics

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The graph coloring problem is an NP-hard combinatorial optimization problem and can be applied to various engineering applications. The chromatic number of a graph G is defined as the minimum number of colors required to color the vertex set V(G) so that no two adjacent vertices are of the same color, and different approximations and evolutionary methods can find it. The present paper focused on the asymptotic analysis of some well-known and recent evolutionary operators for finding the chromatic number. The asymptotic analysis of different crossover and mutation operators helps in choosing the better evolutionary operator to minimize the problem search space and computational complexity. The choice of the right genetic operators facilitates an evolutionary algorithm to achieve faster convergence with lesser population size N through an adequate distribution of promising genes. The selection of an evolutionary operator plays an essential role in reducing the bounds for minimum color obtained so far for some of the benchmark graphs. This research also focuses on the necessary and sufficient conditions for the global convergence of evolutionary algorithms. The stochastic convergence of recent evolutionary operators for solving graph coloring is newly analyzed.

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FrogSim: distributed graph coloring in wireless ad hoc networks

Cited by 13 publications

References 17 publications

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem

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