Abstract
This article proposes an optimal pricing scheme for provisioning sensors-as-a-service (Se-aaS) for catering to applications with multi-tenancy requirements in a sensor-cloud platform. The scheme orchestrates a trade-off analysis between communication range and price in a sensor-cloud platform with range-reconfigurable nodes. The proposed scheme consists of two phases – (a) selection of a neighbor node of a source node, and determination of optimal price for the selected neighbor node. In the first phase, a source node adjusts its communication range and selects its best possible neighbor node using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">selectivity factor</i> of all the neighbor nodes. The selectivity factor considers the determinants such as effective residual energy, effective power consumption, and the number of applications to which the neighbor nodes are associated in the neighbor selection process. In the second phase, we design a utility function to determine the optimal price of the selected neighbor node. We use the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Lagrangian</i> function to model the proposed problem as a mixed-integer linear program (MILP) and obtain the optimal solution using the Karush-Kuhn-Tucker (KKT) conditions. The existing works on pricing in sensor-cloud are deficient in considering the presence of the reconfigurable communication range of sensor nodes. Moreover, based on the value of the communication range, the charged price of the sensor nodes varies. Thus, in this article, we propose a pricing scheme with a trade-off of the reconfigurable communication range of sensor nodes and the charged price incurred in adjusting the communication range. Extensive experimental results show that the proposed scheme performs better compared to the existing pricing schemes for sensor-cloud. In precise, the proposed scheme is capable of increasing the average number of neighbor nodes by at least 1.38 percent. Further, the proposed scheme is capable of reducing the charged price by 10.55 percent, as compared to the existing pricing scheme, DOPH.
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