Combining Optimisation and Simulation Using Logic-Based Benders Decomposition

Operations research practitioners frequently want to model complicated functions that are are difficult to encode in their underlying optimisation framework. A common approach is to solve an approximate model, and to use a simulation to evaluate the true objective value of one or more solutions. We propose a new approach to integrating simulation into the optimisation model itself. The idea is to run the simulation at each incumbent solution to the master problem. The simulation data is then used to guide the trajectory of the optimisation model itself using logic-based Benders cuts. We test the approach on a class of stochastic resource allocation problems with monotonic performance measures. We derive strong, novel Benders cuts that are provably valid for all problems of the given form. We consider two concrete examples: a nursing home shift scheduling problem, and an airport check in counter allocation problem. While previous papers on these applications could only approximately solve realistic instances, we are able to solve them exactly within a reasonable amount of time. Moreover, while those papers account for the inherent variance of the problem by including estimates of the underlying random variables as model parameters, we are able to compute sample average approximations to optimality with up to 100 scenarios.Comment: 30 page

Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems

A cyber-physical system (CPS) employs tight integration of, and coordination between computational, networking, and physical elements. Wireless sensor-actuator networks provide a new communication technology for a broad range of CPS applications such as process control, smart manufacturing, and data center management. Sensing and control in these systems need to meet stringent real-time performance requirements on communication latency in challenging environments. There have been limited results on real-time scheduling theory for wireless sensor-actuator networks. Real-time transmission scheduling and analysis for wireless sensor-actuator networks requires new methodologies to deal with unique characteristics of wireless communication. Furthermore, the performance of a wireless control involves intricate interactions between real-time communication and control. This thesis research tackles these challenges and make a series of contributions to the theory and system for wireless CPS. (1) We establish a new real-time scheduling theory for wireless sensor-actuator networks. (2) We develop a scheduling-control co-design approach for holistic optimization of control performance in a wireless control system. (3) We design and implement a wireless sensor-actuator network for CPS in data center power management. (4) We expand our research to develop scheduling algorithms and analyses for real-time parallel computing to support computation-intensive CPS

Scheduling of re-entrant flow shops

Bibliography: p. 34.Stephen C. Graves...[et al.

Real-Time Estelle

Estelle is one of the standardized Formal Description Techniques for the specification of communication protocols and distributed systems. Unfortunately, Estelle is not capable to express real-time requirements or characteristics of services or protocols which is especially important in the context of distributed multimedia systems. In this paper, we introduce an extension to Estelle called Real-Time Estelle that allows to describe real-time systems. We introduce the syntax of the new language and propose both an operational and a descriptive semantics. Examples show the usefulness of the approach. We also discuss ways to implement Real-Time Estelle specifications

Energy-Centric Scheduling for Real-Time Systems

Energy consumption is today an important design issue for all kinds of digital systems, and essential for the battery operated ones. An important fraction of this energy is dissipated on the processors running the application software. To reduce this energy consumption, one may, for instance, lower the processor clock frequency and supply voltage. This, however, might lead to a performance degradation of the whole system. In real-time systems, the crucial issue is timing, which is directly dependent on the system speed. Real-time scheduling and energy efficiency are therefore tightly connected issues, being addressed together in this work. Several scheduling approaches for low energy are described in the thesis, most targeting variable speed processor architectures. At task level, a novel speed scheduling algorithm for tasks with probabilistic execution pattern is introduced and compared to an already existing compile-time approach. For task graphs, a list-scheduling based algorithm with an energy-sensitive priority is proposed. For task sets, off-line methods for computing the task maximum required speeds are described, both for rate-monotonic and earliest deadline first scheduling. Also, a run-time speed optimization policy based on slack re-distribution is proposed for rate-monotonic scheduling. Next, an energy-efficient extension of the earliest deadline first priority assignment policy is proposed, aimed at tasks with probabilistic execution time. Finally, scheduling is examined in conjunction with assignment of tasks to processors, as parts of various low energy design flows. For some of the algorithms given in the thesis, energy measurements were carried out on a real hardware platform containing a variable speed processor. The results confirm the validity of the initial assumptions and models used throughout the thesis. These experiments also show the efficiency of the newly introduced scheduling methods