RACE: QoI-Aware Strategic Resource Allocation for Provisioning Se-aaS

Misra S, Schober R, Chakraborty A (2022)


Publication Type: Journal article

Publication year: 2022

Journal

Book Volume: 15

Pages Range: 1540-1550

Journal Issue: 3

DOI: 10.1109/TSC.2020.3001078

Abstract

In this paper, the problem of ensuring profitability for multiple sensor-owners in sensor-cloud, while satisfying the service requirements of end-users, is studied. In traditional sensor-cloud, Sensor-Cloud Service Provider (SCSP) solely dictates the service provisioning process. However, the SCSP cannot always ensure high profits for sensor-owners, who incur significant maintenance costs for their sensor-nodes. Contrarily, it is highly essential to meet the Quality-of-Information (QoI) requirements of end-users to ensure their service satisfaction. Existing works proposed a few node allocation schemes which neither consider the cost incurred by sensor-owners nor the QoI of sensed-data in sensor-cloud. To address this problem, a strategic resource allocation scheme, named RACE, is proposed, which introduces the participation of sensor-owners in the node allocation process. First, utility theory is used to calculate the optimum number of nodes to be allocated for a service. Thereafter, single leader multiple followers Stackelberg game is formulated to decide the number of nodes to be contributed by each sensor-owner and the price to be charged. Simulation-based experimental results reveal that, using RACE, the profits of the sensor-owners and those of the SCSP increase by 86.11-89.26 percent and 41.95-80.82 percent, respectively, as compared to the existing benchmark schemes, while considering that each sensor-node is capable of serving multiple applications simultaneously. Moreover, service availability in sensor-cloud increases by 31.70-96.96 percent using RACE.

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How to cite

APA:

Misra, S., Schober, R., & Chakraborty, A. (2022). RACE: QoI-Aware Strategic Resource Allocation for Provisioning Se-aaS. IEEE Transactions on Services Computing, 15(3), 1540-1550. https://doi.org/10.1109/TSC.2020.3001078

MLA:

Misra, Sudip, Robert Schober, and Aishwariya Chakraborty. "RACE: QoI-Aware Strategic Resource Allocation for Provisioning Se-aaS." IEEE Transactions on Services Computing 15.3 (2022): 1540-1550.

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