Fanxin Kong

Learn More
—While much work has addressed the energy-efficient scheduling problem for uniprocessor or multiprocessor systems, little has been done for multicore systems. We study the multicore architecture with a fixed number of cores partitioned into clusters (or islands), on each of which all cores operate at a common frequency. We develop algorithms to determine a(More)
Wireless sensor networks (WSNs) have been widely deployed and it is crucial to properly control the energy consumption of the sensor nodes to achieve the maximum WSNs' operation time (i.e., <i>lifetime</i>) as they are normally battery powered. In this paper, for sensor nodes that are utilized to monitor oil pipelines, we study the <i>linear sensor(More)
—Power management is becoming an increasingly important issue for Internet services supported by multiple geo-distributed data centers. These data center's energy consumptions and costs are becoming unacceptably high, and placing a heavy burden on both energy resources and the environment. Emerging smart grid provides a feasible way for dynamic and(More)
Megawatt-scale datacenters have emerged to meet the increasing demand for IT applications and services. The hunger for power brings large electricity bills to datacenter operators and causes significant impacts to the environment. To reduce costs and environmental impacts, modern datacenters, such as those of Google and Apple, are beginning to integrate(More)
—Energy conservation is an important issue in the design of embedded systems. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two widely used techniques for saving energy in such systems. In this paper, we address the problem of minimizing multi-resource energy consumption concerning both CPU and devices. A system is assumed to contain(More)
While much work has addressed energy-efficient scheduling for <i>sequential tasks</i> where each task can run on only one processor at a time, little work has been done for parallel tasks where an individual task can be executed by multiple processors simultaneously. In this paper, we develop energy minimizing algorithms for parallel task systems with(More)