The complexities of many previous scheduling algorithms for IRIS tasks are too high to apply them to practical systems handling many tasks. The high complexities stem from the fact that the algorithms perform scheduling on all tasks in a system, producing an optimal solution. As a way to reduce the complexity of scheduling, we propose a heuristic on-line scheduling algorithm that schedules the IRIS tasks only in a scheduling window, producing a sub-optimal solution. A scheduling window contains W important tasks determined by a selection policy. The performance of the proposed algorithm is verified by simulation.

We propose a heuristic session allocation algorithm for switch with multiple output links, named SCDF (Shortest Class Delay First) algorithm. The proposed SCDF algorithm allocates a new session to an output link with the smallest estimated average packet delay among those of sessions that belong to the same class. The empirical study proves that SCDF shows the best performance comparing those of other competitive algorithms, in terms of balancing packet delay difference and maximizing throughput.

This letter proposes a modified Pairwise test case generation algorithm. The proposed algorithm produces additional test cases that may not be covered by Pairwise algorithm due to the dependency between internal modules of software systems. The algorithm produces additional cases utilizing internal module dependencies. The algorithm effectively increases the coverage of testing without significantly increasing the number of test cases.

We propose a feedback controller to efficiently control web requests especially on overloaded networks. The controller is designed based on a feedback closed loop that prevents overload of web server and enforces target CPU utilization via controlling the amount of input web requests. The main contribution of this letter is the use of feedback control theory to design the controller that delicately regulates web requests even under the dynamic changes in processing power of web server. In contrast with many previous heuristic methods, the proposed controller uses a systematic approach to adaptively control web requests taking account of the dynamic behavior of web server. Simulation results performed in overloaded cases show that the proposed controller lets web server effectively control input web requests and reach its CPU utilization to desired levels in relatively small settling times.