Real-Time Systems

Abstract

Since 2004, most of chip vendors have begun to shift their major focus from singlecore to multi-core architecture (W. Wolf. Signal Processing Magazine, IEEE, 26(6):50-54, 2009). One major reason of this shift is that it reaches a physical limit by scaling transistor size and increasing the clock frequency to improve the computing performance on a single-core architecture (Agarwal et al. Proceedings of the 27th International Symposium on, pages 248-259, June 2000), that is, the overall chip cannot be reached within a single clock cycle. Multi-core architecture, however, brings innovative and promising opportunities to further improve the computing performance. By providing multiple processing cores on a single chip, multi-core systems can dramatically increase the computing performance and mitigate the power and thermal issues with the same performance achievement as single-core systems. As multi-core architecture has been more and more dominant in the industrial market, there is an urgent demand for effective and efficient techniques for the design of multi-core systems.In this chapter, we first analyze the thermal behavior on multi-core real-time systems by taking the heat transfer among different cores into consideration. Then we analyze the energy consumption for a given speed scheduling on multi-core systems.

Cloud Workload Allocation Approaches for Quality of Service Guarantee and Cybersecurity Risk Management

“…Furthermore, scheduling real-time requests in embedded system is either using a single-core [66,67] platform or multi-core platform [68][69][70][71]. On the other hand, a cloud provider can schedule requests on a single server [72][73][74], on a cluster of servers [75,76], on a single data center [77,78], or on a set of geographically distributed data centers [79].…”

“…Real-time schedulers can be a single-core [66,67] or on a multi-core [68][69][70][71]. A single-core scheduler has to decide the sequence of requests execution.…”