Electrical and Computer Engineering Professor C. Mani Krishna’s article, entitled “Managing Battery and Supercapacitor Resources for Real-Time Sporadic Workloads,” was the “Most Accessed” article during May of 2012 for the journal IEEE Embedded Systems Letters. His article was first published in vol. 3, no. 1, Mar. 2011, pp. 32-36, of IEEE Embedded Systems Letters. Professor Krishna was elevated to the honorary rank of Fellow in the Institute of Electrical and Electronics Engineers in 2009 "for contributions to the design and evaluation of real-time systems." Hs research specialty is real-time systems, and he directs the Architecture and Real-time Systems Laboratory (ARTS) with Professor Israel Koren.
Researchers in ARTS seek new architectures for high-performance parallel and distributed computing systems, with a particular emphasis on embedded real-time systems and fault-tolerance in parallel systems.
Krishna earned his bachelor’s degree in electrical engineering from the Indian Institute of Technology in 1979, his M.S. degree from Rensselaer Polytechnic Institute in 1980, and his Ph.D. from the University of Michigan in 1984.
IEEE Embedded Systems Letters provides a forum for rapid dissemination of latest technical advances in embedded systems and related areas in embedded software. The emphasis is on models, methods, and tools that ensure secure, correct, efficient, and robust design of embedded systems and their applications.
Here is the abstract of Professor Krishna’s article in IEEE Embedded Systems Letters:
Batteries and supercapacitors are complementary: batteries have a high energy-to-weight ratio but are limited in the power levels they can support; supercapacitors can provide high levels of power while they have a much lower energy-to-weight ratio. A battery-supercapacitor duo can therefore prove useful in embedded systems serving sporadic, energy-intensive, tasks: the battery charges the capacitor at a low, fairly steady, rate which maximizes the energy that can be drawn from it, while the supercapacitor satisfies the impulse power demands of the application. In this letter, we characterize such energy sources by means of two performance measures: expected time before the first task failure and the fraction of tasks that fail before the battery dies. or the case of rare (but energy-intensive) sporadic tasks, we present semi-Markov models to evaluate these measures. For more frequent task arrivals, we provide simulation results. This letter demonstrates the impact of various parameters on our performance measures: power draw, capacitor sizing, and the battery rest scheduling policy. (July 2012)