Imprecise Task Scheduling and Overload Management using OR-ULD J¨ orgen Hansson Dept. of Computer Science Link¨ oping University Sweden jorha@ida.liu.se Marcus Thuresson Omicron Ceti AB Kista Sweden marcus@omicron.se Sang H. Son Dept. of Computer Science University of Virginia Charlottesville, USA son@cs.virginia.edu Abstract This paper evaluates the OR-ULD (Overload Resolution using Utility Loss Density) algorithm for imprecise com- putation workloads, where tasks are decomposed into one mandatory task and one optional task. OR-ULD is a value- driven overload resolution algorithm running in log time, where is the number of tasks. The algorithm is in- voked only in case of transient overloads. By representing error using value-functions, we get a general model for rep- resenting quality tradeoffs. Our performance studies show that, OR-ULD overall performs better than the MF (Manda- tory First) algorithm in reducing the total error and the total weighted error. In addition, OR-ULD minimizes the number of discarded optional tasks. The approach provides the flexibility that enables mul- tiple strategies to be used to resolve overloads, e.g., over- loads may be resolved by replacing transactions with con- tingency transactions, and non-critical regular transactions may be dropped or postponed. Keywords: imprecise computation, overload management, scheduling, total error 1 Introduction It is not always possible to schedule every task so that it meets its deadline. This phenomenon is called a transient overload and represents a system state where the requests for service exceeds available resources for a limited time causing missed task deadlines. Transient overloads may oc- cur when faults in the computational environment reduce computational resources available to the system, or when emergencies arise. Since new tasks may arrive at run-time and since schedulers in dynamic real-time systems are not clairvoyant, dynamic real-time systems are prone to tran- sient overloads. In hard real-time systems it is of outmost importance that all deadlines are met; a missed deadline results in system failure. Since no lateness is allowed there exists an implicit requirement that worst-case execution time and worst-case arrival rates must be used when scheduling tasks with crit- ical time constraints. In firm real-time systems deadlines should be met but occasional violations are acceptable and do not lead to any damage in the environment. A result that is produced too late, i.e., after its deadline, is however of no value to the system. One proposed technique to resolve transient overloads in real-time systems is the imprecise computation model [13, 10, 12, 8]. The proposed technique gives the user an imprecise and approximate result of acceptable quality while important time constraints are met during transient overloads. The imprecise computation model can be uti- lized in a wide variety of applications areas, e.g., databases, networking, machine vision, signal processing, and depend- ability in real-time systems. Hansson et al. [5, 3] proposed a strategy for resolv- ing transient overloads by reallocating resources among tasks that have been admitted to the system. A utility-loss density driven overload resolution algorithm (OR-ULD — Overload Resolution using Utility Loss Density) was de- fined. The algorithm dynamically resolves transient over- loads, in real-time database systems using the proposed strategy. In that work hard real-time transactions have a contingency action that requires fewer resources and less time than the original transaction. When an overload oc- curs, non-critical transactions are discarded in a controlled way, and hard transactions are replaced with their contin- gency action, ensuring the timeliness of hard deadlines. In this work we evaluate the applicability and efficiency of OR-ULD for imprecise task workloads, as defined by Shih et al. [13] and Liu et al. [10]. The problem addressed is overload management of sporadic preemptable imprecise