Dynamic Spatial-Correlation-Aware Topology Control of Wireless Sensor Networks Using Game Theory

Hu, Shihong; Li, Guanghui; Huang, Guangyan

doi:10.1109/jsen.2020.3043748

Cited by 14 publications

(4 citation statements)

References 49 publications

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“…In the past, topology control mechanisms have been studied mainly in Wireless Mesh Networks, Wireless Mobile Ad Hoc Networks, and Wireless Sensor Networks. The main objective of this type of mechanism is to modify the network topology to induce connectivity properties and improve the overall network performance [23,24].…”

Section: Related Workmentioning

confidence: 99%

A Spectral Gap-Based Topology Control Algorithm for Wireless Backhaul Networks

González-Ambriz,

Menchaca-Méndez,

Pinacho-Castellanos

et al. 2024

Future Internet

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This paper presents the spectral gap-based topology control algorithm (SGTC) for wireless backhaul networks, a novel approach that employs the Laplacian Spectral Gap (LSG) to find expander-like graphs that optimize the topology of the network in terms of robustness, diameter, energy cost, and network entropy. The latter measures the network’s ability to promote seamless traffic offloading from the Macro Base Stations to smaller cells by providing a high diversity of shortest paths connecting all the stations. Given the practical constraints imposed by cellular technologies, the proposed algorithm uses simulated annealing to search for feasible network topologies with a large LSG. Then, it computes the Pareto front of the set of feasible solutions found during the annealing process when considering robustness, diameter, and entropy as objective functions. The algorithm’s result is the Pareto efficient solution that minimizes energy cost. A set of experimental results shows that by optimizing the LSG, the proposed algorithm simultaneously optimizes the set of desirable topological properties mentioned above. The results also revealed that generating networks with good spectral expansion is possible even under the restrictions imposed by current wireless technologies. This is a desirable feature because these networks have strong connectivity properties even if they do not have a large number of links.

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Section: Related Workmentioning

confidence: 99%

A Spectral Gap-Based Topology Control Algorithm for Wireless Backhaul Networks

González-Ambriz,

Menchaca-Méndez,

Pinacho-Castellanos

et al. 2024

Future Internet

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“…Indicator function having value 1 if the condition in the argument is true and 0 otherwise Although sensor observations are correlated in practice, only a few works investigate scheduling policies that account for dependency among the observations. In resource-constrained WSNs, sensor dependencies have been exploited to achieve energy-efficient routing [12], [13], missing data inference in environmental crowd sensing [14], optimal sensor location selection [15], and reducing traffic load [16]. For a remote estimation WSN where sensors transmit noisy measurements of a Gaussian source process over multiple access channels (MAC), the estimation accuracy is normally restricted by the transmission powers of the sensors and the number of antennas at the remote estimator [17], [18].…”

Section: (•)mentioning

confidence: 99%

Optimal Transmission-Constrained Scheduling of Spatio-Temporally Dependent Observations Using Age-of-Information

et al. 2022

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This paper proposes an optimal scheduling policy for broadcasting spatio-temporally dependent observations to two remote estimators over a finite time horizon. The system comprises a scheduler that can broadcast one observation from one out of two spatio-temporally dependent processes at each time instant. Since the number of broadcasting instants for each sensor is constrained, the scheduler must plan the broadcasting that minimizes the time-averaged estimation error. As the scheduler cannot observe the measurements, it determines the expected estimation error based on the age-of information (AoI). Using AoI as a state variable, we derive a set of optimal scheduling policies that minimizes the average mean squared error (MSE) for any given time horizon. The policies provide the optimal number of transmission instances for each sensor and time-varying AoI thresholds for when to be scheduled. By studying how the MSE evolves with respect to the AoI generated by a given scheduling sequence, we can obtain an optimal policy using a low-complexity numerical method. Numerical results validate the theory and demonstrate how utilizing spatio-temporal dependencies together with AoI can enhance the estimation accuracy in a communication-constrained sensor network.

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“…For balancing invulnerability and energy consumption in WSNs, game theory has become a unique method for developing routing protocols, and its rational behavior can be applied to the systematic analysis of hierarchical networks [ 40 ]. The routing protocols based on game theory have demonstrated more attractive advantages than other protocols regarding network lifetime, energy efficiency, and route establishment time [ 41 ].…”

Section: Related Workmentioning

confidence: 99%

IACRA: Lifetime Optimization by Invulnerability-Aware Clustering Routing Algorithm Using Game-Theoretic Approach for Wsns

Wang

Zhang²,

et al. 2022

Sensors

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Energy limitation is one of the intrinsic shortcomings of wireless sensor networks (WSNs), although it has been widely applied in disaster response, battlefield surveillance, wildfire monitoring, radioactivity detection, etc. Due to the large amount of energy consumed for data transmission, how to prolong the network lifespan by designing various hierarchical routing protocols has attracted more and more attention. As a result, numerous achievements have emerged successively. However, these presented mechanisms can rarely guarantee the satisfactory quality of service (QoS), while lowering the energy cost level of WSNs. Meanwhile, invulnerability is undoubtedly an excellent quantitative index to assess QoS. Therefore, it is critical to develop a practical routing method to optimize network lifetime by considering both invulnerability and energy efficiency. Game theory is suitable for such a critical problem as it can be used in node or at network level to encourage the decision-making capabilities of WSNs. In this paper, a novel invulnerability-aware clustering routing algorithm (IACRA) using game-theoretic method is proposed to solve the predicament. The core features of the addressed game-theory-based routing protocol include integral invulnerability awareness, optimal cluster head selection in hierarchical routing, distance-aware cluster head discovery, and cluster rotation update mechanism for lifetime optimization. Particularly, the integral network invulnerability based on weighted fusion is constructed for further defining the profit model by combining the invulnerability indicators used to evaluate the local and whole network. Meanwhile, the optimal probability function of every node elected as CH in per cluster is established through the game between invulnerability and node energy consumption. In addition, the cluster update mechanism base on cluster rotation is proposed to avoid the rapid death of nodes with large energy consumption for maximizing network lifetime. The experimental results indicated a significant improvement in energy balance as well as in invulnerability compared with the other three kinds of well-known clustering routing protocols including GEEC (Game-theory-based energy efficient clustering routing protocol), HGTD (Hybrid, game-theory-based distributed clustering protocol), and EEGC (Efficient energy-aware and game-theory-based clustering protocol). Concretely, at the 400 communication rounds, the invulnerability of IACRA was higher than that of GEEC, HGTD, and EEGC by 77.56%, 29.45% and 15.90%, respectively, and the average residual energy of IACRA was 8.61%, 18.35% and 6.36% larger than that of GEEC, HGTD, and EEGC, respectively. Based on these results, the proposed protocol can be utilized to increase the capability of WSNs against deterioration of QoS and energy constraints.

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Dynamic Spatial-Correlation-Aware Topology Control of Wireless Sensor Networks Using Game Theory

Cited by 14 publications

References 49 publications

A Spectral Gap-Based Topology Control Algorithm for Wireless Backhaul Networks

A Spectral Gap-Based Topology Control Algorithm for Wireless Backhaul Networks

Optimal Transmission-Constrained Scheduling of Spatio-Temporally Dependent Observations Using Age-of-Information

IACRA: Lifetime Optimization by Invulnerability-Aware Clustering Routing Algorithm Using Game-Theoretic Approach for Wsns

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