Multi-mode real-time systems are those which support applications with different modes of operation, where each mode is characterized by a specific set of tasks. At run-time, such systems can, at any time, be requested to switch from its current operating mode to another mode (called "new mode") by replacing the current set of tasks with that of the new-mode. Thereby, ensuring that all the timing requirements are met not only requires that a schedulability test is performed on the tasks of each mode but also that (i) a protocol for transitioning from one mode to another is specified and (ii) a schedulability test for each transition is performed. We propose two distinct protocols that manage the mode transitions upon uniform and identical multiprocessor platforms at run-time, each specific to distinct task requirements. For each protocol, we formally establish schedulability analyses that indicate beforehand whether all the timing requirements will be met during any mode transition of the system. This is performed assuming both Fixed-Task-Priority and Fixed-Job-Priority schedulers.
Among the uniprocessor protocols, the authors of @cite_16 @cite_22 @cite_25 proposed the following protocols. @math A protocol @cite_22 where tasks are assigned priorities according to the Deadline Monotonic Scheduling algorithm and are scheduled with time offsets during the mode change only.
@cite_16 @cite_25 @cite_22
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We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give a linear-time algorithm to compute all non-dominated solutions for the general uniprocessor problem and a fast arbitrarily-good approximation for multiprocessor problems when every job requires the same amount of work. We also show that the multiprocessor problem becomes NP-hard when jobs can require different amounts of work. For total flow, we show that the optimal flow corresponding to a particular energy budget cannot be exactly computed on a machine supporting exact real arithmetic, including the extraction of roots. This hardness result holds even when scheduling equal-work jobs on a uniprocessor. We do, however, extend previous work by to give an arbitrarily-good approximation for scheduling equal-work jobs on a multiprocessor. We revisit the classic problem of spreading a piece of information in a group of @math n fully connected processors. By suitably adding a small dose of randomness to the protocol of Gasieniec and Pelc (Parallel Comput 22:903---912, 1996), we derive for the first time protocols that (i) use a linear number of messages, (ii) are correct even when an arbitrary number of adversarially chosen processors does not participate in the process, and (iii) with high probability have the asymptotically optimal runtime of @math O(logn) when at least an arbitrarily small constant fraction of the processors are working. In addition, our protocols do not require that the system is synchronized nor that all processors are simultaneously woken up at time zero, they are fully based on push-operations, and they do not need an a priori estimate on the number of failed nodes. Our protocols thus overcome the typical disadvantages of the two known approaches, algorithms based on random gossip (typically needing a large number of messages due to their unorganized nature) and algorithms based on fair workload splitting (which are either not time-efficient or require intricate preprocessing steps plus synchronization). The problem of uniprocessor scheduling under conditions of overload is investigated. The system objective is to maximize the number of tasks that complete by their deadlines. For this performance metric it is shown that, in general, any on-line algorithm may perform arbitrarily poorly as compared to a clairvoyant scheduler. Restricted instances of the general problem for which on-line schedulers ran provide a guaranteed level of performance are identified, and on-line algorithms presented for these special cases. >