Cache-enabled sensor-cloud: The economic facet

In this work, we propose a dynamic cache-based pricing scheme, named CASH, for service-oriented sensor-cloud. In sensor-cloud, the Sensor-Cloud Service Provider (SCSP) provisions Sensors-as-a-Service (Se-aaS) to multiple end-users based on a pay-per-use model. The service-requests of the end-users have heterogeneous data-rate requirements. In the cache-enabled architecture of sensor-cloud, these service-requests are served by the SCSP using either the Internal or the External cache, which incurs different costs to the SCSP. Thereby, the SCSP tries to maximize its own profit by distributing these service-requests, optimally, among the caches. Additionally, the SCSP ensures that the end-users are minimally charged. Existing literature fails to propose any pricing scheme for service-oriented sensor-cloud, while considering the cost incurred for data caching. In CASH, we propose a dynamic pricing model for sensor-cloud using dynamic coalition formation game with transferable utility. Using CASH, based on the preference relation of the partitions, we determine the optimal internal cache refresh rate, while maximizing the coalition value. Through simulation, we observe that the cost incurred by the SCSP reduces by 34.32–51.15% and the price paid by the end-users decreases by 9.60–17.47% as compared to the existing schemes. Additionally, CASH ensures 9.60–21.85% increase in the profit of the SCSP.