Showing papers by "G. De Micheli published in 2009"
14 Jun 2009
TL;DR: A Markov-chain-based analytical model of the CAP of the IEEE 802.15.4 MAC is developed and used to evaluate the performance of a simple, yet eiTective, contentionwindow-based service dilTerentiation strategy, in terms of the resulting throughput, average frame service time and access priority for each priority class.
Abstract: The IEEE 802.15.4 standard is poised to become the global standard for low data rate, low energy consumption wireless sensor networks (WSN). By assigning the same sets of contention access parameters for all data frames and nodes, the contention access period (CAP) of the slotted IEEE 802.15.4 medium access control (MAC) currently provides a priorityindependent channel access functionality and no service diiTerentiation. Several recent WSN applications such as wireless body sensor networks, however, may require service dilTerentiation and traf6e prioritization support to accommodate potential highpriority traffic (e.g., alarms or emergency alerts). By allowing dilTerent sets of access parameters and data frame lengths for differentpriority classes, this paper develops a Markov-chain-based analytical model of the CAP of the IEEE 802.15.4 MAC with service dilTerentiatlon, under unsaturated traffic conditions. In particular, given two priority classes, our analytical model is used to evaluate the performance of a simple, yet eiTective, contentionwindow-based service dilTerentiation strategy, in terms of the resulting throughput, average frame service time and access priority for each priority class. The accuracy of the analytical model is validated by extensive ns-2 simulation.
44 citations
01 Oct 2009
TL;DR: A high-level simulation framework is presented that extends power state machines to hardware and software components to explore power management policies including OS-level effects faster than traditional approaches.
Abstract: Design of power management mechanisms of hardware components (CPU, memories) in Embedded Systems needs to be performed at OS level to exploit system-level information. Traditional simulation models do not fit well, being too slow to simulate applications with OS-interaction. In this paper we present a high-level simulation framework that extends power state machines to hardware and software components to explore power management policies including OS-level effects faster than traditional approaches.