My Account | Careers | Downloads | Blog

PROJECT TITLE :

PRIME: An Optimal Pricing Scheme for Mobile Sensors-as-a-Service

ABSTRACT:

In this article, we propose a pricing scheme for provisioning mobile Sensors-as-a-Service (mSe-aaS) in the mobile sensor-cloud (MSC) architecture. This scheme is given the name PRIME, and its goal is to optimally distribute the financial profit among the various actors of the MSC. MSC introduces a new actor known as the device owner, in contrast to traditional sensor clouds. The device owner is the person whose mobile device hosts the physical sensor nodes. On the other hand, the device and sensor owners earn certain revenues based on the usage of the sensor nodes and the mobile devices, which is done in order to provide mSe-aaS to the end-users. These revenues are determined by the usage of the sensor nodes and the mobile devices. Due to the fact that MSC is a contemporary architecture, there is no predetermined pricing structure for it. In the present work, in order to determine the most effective pricing strategy, we take into account the presence of the device owner, the sensor owner, the Sensor-Cloud Service Provider (SCSP), and the end-user. We use the Lagrangian multiplier method and apply Karush-Kuhn-Tucker (KKT) conditions so that we can design such a strategy. On the other hand, an end-user can choose a SCSP from among the available options using a number of different criteria. PRIME makes it possible for an end-user to choose an appropriate SCSP by providing information regarding the standing of all of the providers who are currently available. Extensive experimental results report that PRIME raises the profit of sensor and device owners by a respective amount of 25.67% and 29.12%. We also examine PRIME in relation to a pricing model that is already in place for conventional sensor-cloud architecture. When compared to the same results obtained by employing the conventional sensor-cloud architecture, we find that the service return achieved by utilizing PRIME is 55.31% higher.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Reinforcement Learning-based Collision Avoidance and Optimal Trajectory Planning in UAV Communication Networks ABSTRACT: In this paper, we investigate optimal trajectory planning for unmanned aerial vehicle (UAV)
PROJECT TITLE : Fast Globally Optimal Transmit Antenna Selection and Resource Allocation Scheme in mmWave D2D Networks ABSTRACT: The process of transmit antenna selection, abbreviated as TAS at base stations, has been the subject
PROJECT TITLE : Optimal Sensor Placement for Source Localization: A Unified ADMM Approach ABSTRACT: Source localization is an important part of many different applications, including radar, wireless communications, and communications
PROJECT TITLE : Optimal Scale Combination Selection Integrating Three-Way Decision With Hasse Diagram ABSTRACT: In the field of machine learning, the multi-scale decision system, also known as MDS, is a useful tool for describing
PROJECT TITLE : Energy and Age Pareto Optimal Trajectories in UAV-assisted Wireless Data Collection ABSTRACT: This article investigates a wireless network that is assisted by an unmanned aerial vehicle (UAV). In such a network,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry