Device Independent Remote Adaptations for Power Optimization using Distributed Middleware

Providing quality of service(QoS) guarantees for power vs. performance tradeoffs in distributed middleware frameworks is a crucial research challenge. Future middleware frameworks need to address the issue of providing acceptable performance guarantees in the presence of low-power mobile devices. Most current energy optimization schemes (e.g. DVS) target individual processing elements(nodes) and lack a global view of the distributed system; therefore the inherent advantages of distribution remains unharnessed. In this work, we introduce a middleware based distributed dynamic voltage scaling scheme (R-DVS) for voltage setting in distributed nodes remotely, while exploiting the knowledge of the global system state. To further optimize the power gains at the devices, an optimal task partitioning and offloading scheme is integrated with R-DVS. This paper makes two significant contributions i) we show through extensive simulations that R-DVS is a viable middleware solution and ii) a middleware framework combining high-level adaptations and low-level power management can yield significant power gains, while retaining the advantages of distribution and device level performance. In our extensive simulations we show, that our approach yields significant energy gains under a correct choice of operating parameters and provides power gains as high as 75% for low power devices.