A Task Allocation Algorithm Based on Score Incentive Mechanism for Wireless Sensor Networks

Wang, Feng; Han, Guangjie; Jiang, Jinfang; Li, Wei; Shu, Lei

doi:10.1155/2015/286589

Cited by 10 publications

(5 citation statements)

References 20 publications

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“…For example, the mechanism proposed in [19], motivates the agents to exert the effort as desired by the requester/controller and truthfully report their private worker quality and data to the requester. Another task allocation incentive-based mechanism to achieve the network load balance and energy consumption has been proposed for wireless networks in [20]. In this work, a scoring based approach is proposed to reward or punish agents for the given task execution.…”

Section: Related Workmentioning

confidence: 99%

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

Javed,

Khan,

Lehtomäki

et al. 2024

IEEE Open J. Commun. Soc.

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Gathering useful and trustworthy wireless data using crowdsourcing to train/validate machine learning (ML) algorithms can be difficult due to two factors: 1) correctness and reliability of the gathered data from various independent wireless access points (APs) can be unknown, and 2) designing a metric that can capture the value of the collected data for the considered model can be a challenge. To address the challenge of reliable data collection, we propose a game-theoretic crowdsourcing-based wireless data collection mechanism that can be used to reliably collect the data. We also propose a metric that can capture the value of the collected data for the considered model. Our proposed method provides protection against selfish deviations and unlike other game-theoretic works does not make an assumption that the actions of the crowdsourcing agent APs are known to the crowdsourcing entity. We consider a technique that can be used to infer the actions of agent APs and propose that the participants utilize the n-round Win-stay lose shift (WSLS) strategy. In our work, we compare the performance of the proposed strategy against various other game-theoretic strategies, such as always high, always low, WSLS with probability p, and tit for tat. In our performance evaluation, we utilize both real and synthetic wireless channel utilization data. Our results show that the n-round WSLS strategy outperforms the other game-theoretic strategies.

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Section: Related Workmentioning

confidence: 99%

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

Javed,

Khan,

Lehtomäki

et al. 2024

IEEE Open J. Commun. Soc.

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“…In Feng et al, 21 a hybrid task algorithm based on score incentive mechanism (TASIM) for complex task execution in WSNs is proposed. Sensor nodes are ranked based on their residual resources and services capacities.…”

Section: Multi-actuator Task Allocationmentioning

confidence: 99%

Adaptive auction protocol for task assignment in wireless sensor and actuator networks

Wang

Kou

et al. 2020

International Journal of Distributed Sensor Networks

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The development of wireless sensor and actuator network is leading to high complexity networks and subsequently, new challenges in task assignment for effective sensor–actuator coordination. This article proposes an adaptive auction protocol for task assignment in multi-hop wireless actuator networks, considering a scenario where all actuators are immobile and each of them can obtain the target information from sensors. Unlike existing methods that neglect the adaptive auction area required by dynamic networks, the proposed method uses an adaptive factor [Formula: see text] (reflects the adaptive auction area) that is deduced based on the relation between network characteristics and protocol performance. Simulation results show that the adaptive protocol can dynamically change the auction area during the network operation. In addition, comparison with existing methods, such as simple auction protocol, 1 hop simple auction aggregation protocol, and 1 hop simple auction aggregation protocol greedy extension, shows that the adaptive auction protocol can choose the optimal solution at a low communication cost with a high probability, irrespective of the changes in the network.

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“…It is observed that the proposed algorithm can extend the network lifetime. In the literature [31], to balance network load, a task allocation algorithm is proposed based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes' task execution in clusterbased WSNs.…”

Section: Task Collaboration Schemes Of Mwmsnmentioning

confidence: 99%

“…It is observed that the TASIM can balance network load and reduce the network lifetime. Most of the existing task allocation algorithms are based on multi-objective optimization methods, while accounting for the task completion time [31], [32], energy consumption [30], [33], [34], load balancing degree [33], [35], and service reliability [36], [37]. Most of these solutions adopt heuristic methods, which are deterministic and non-retrospective.…”

Section: Task Collaboration Schemes Of Mwmsnmentioning

confidence: 99%

Mobile Wireless Multimedia Sensor Networks Image Compression Task Collaboration Based on Dynamic Alliance

Liu

et al. 2020

IEEE Access

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In mobile wireless multimedia sensor networks' image compression task collaborations, the existing methods do not consider the dynamic changes in the processing ability and the locations of the cooperative nodes. when processing the image compression tasks, these methods will cause frequent interruptions and result in data re-transmission for those tasks. in this paper, an image compression task collaboration algorithm based on dynamic alliance is proposed to solve this problem in mobile wireless multimedia sensor networks. first, a dynamic task alliance is established by the camera node based on the location, computing capability and resource usage of ordinary nodes. then, the location and average moving velocity of the camera nodes and ordinary nodes are considered to calculate the task stable execution time. the image compression task is divided into an image transfer sub task and an image compression sub task based on the task stable execution time. finally, an image compression task collaboration allocation optimization model is established according to the transmission time, the execution time, the execution cost, and the network energy consumption. the gradient method is used to realize the cooperative allocation of image compression tasks. simulation results show that the proposed algorithm can realize task load balancing, reduce the execution time, and network energy consumption. INDEX TERMS Mobile multimedia sensor networks, image compression, task coordination, task decomposition.

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A Task Allocation Algorithm Based on Score Incentive Mechanism for Wireless Sensor Networks

Cited by 10 publications

References 20 publications

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

An Imperfect Monitoring Game-Theoretic Approach for Crowdsourcing Reliable Wireless Data

Adaptive auction protocol for task assignment in wireless sensor and actuator networks

Mobile Wireless Multimedia Sensor Networks Image Compression Task Collaboration Based on Dynamic Alliance

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