Dynamic Optimal Pricing for Heterogeneous Service-Oriented Architecture of Sensor-Cloud Infrastructure

Abstract

This paper proposes a dynamic and optimal pricing scheme for provisioning Sensors-as-a-Service (Se-aaS) [1] within the sensor-cloud infrastructure. Existing cloud pricing models are limited in terms of the homogeneity in service-types, and hence, are not compliant for the heterogeneous service oriented architecture of Se-aaS. We propose a new pricing model comprising of two components, applicable for Se-aaS architecture: pricing attributed to Hardware (pH) and pricing attributed to Infrastructure (pI). pH addresses the problem of pricing the physical sensor nodes subject to variable demand and utility of the end-users. It maximizes the profit incurred by every sensor owner, while keeping in mind the end-users' utility. pI mainly focuses on the pricing incurred due to the virtualization of resources. It takes into account the cost for the usage of the infrastructural resources, inclusive of the cost for maintaining virtualization within sensor-cloud. pI maximizes the profit of the sensor-cloud service provider (SCSP) by considering the user satisfaction. Simulation results depict improved performance of pH in comparison to the traditional hardware pricing algorithms, viz. PPM and Sprite, in terms of the residual energy, proximity to the Base Station (BS), Received Signal Strength (RSS), overhead, and cumulative energy consumption. The results also show the tendency of the sensor-owners to converge to the end-user utility, but not exceed it. We also analyze the performance of pI. The results show the optimality in the profit incurred by SCSP and the user satisfaction.

Cloud Computing Model for Agricultural Applications

“…In this paper [14], they proposed a novel architecture that based on SOA computing and sensors virtualization for the efficient management of data at heterogeneous WSNs. In this paper [15], they proposed an optimal and dynamic valuing approach for provisioning SaaS (Sensors-as-a-Service) in a cloud-sensor environment but the present cloud models are inadequate in terms of service type homogeneity. Therefore, they proposed a novel pricing prototype for the comparison of both component that is appropriate for SaaS architecture; pricing attributed to the Infrastructure (PAI) and, pricing attributed to the Hardware (PAH).…”

Design and Implementation of a Sensor-Cloud Platform for Physical Sensor Management on CoT Environments

“…A mathematical formulation of the sensor-cloud is presented, and a paradigm shift of technologies from traditional WSNs to a sensor-cloud architecture is suggested as well. Existing cloud pricing models are limited in terms of the homogeneity in service-types, and in order to address this issue Chatterjee et al [40] propose a new pricing model for the heterogeneous service-oriented architecture of Sensors-as-a-Service (Se-aaS) with the sensor-cloud infraconfiguration. The proposed pricing model comprises two components: pricing attributed to hardware (pH) that focuses on pricing the physical sensor nodes, and pricing attributed to infraconfiguration (pI) that deals with pricing incurred due to the virtualization of resources.…”

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications

“…In [8], the authors propose two different approaches to efficiently virtualize physical sensors into virtual sensors. An optimal pricing model for the IoT-cloud is also introduced in [9]. According to the pricing model, the price of a sensing service is proportional to a number of resources it consumes.…”

“…For example, in [1,2,5,6,7], the authors present architectural design for IoT-cloud. Sensor virtualization and pricing model are discussed in [8,9], while the studies [10,11,12] propose various approaches to optimize data delivery from physical wireless sensor networks to the IoT-cloud.…”