SchedViz is a tool for gathering and visualizing kernel scheduling traces on Linux machines. It helps to:

• quantify task starvation due to round-robin queueing,
• identify primary antagonists stealing work from critical threads,
• determine when core allocation choices yield unnecessary waiting,
• evaluate different scheduling policies,
• and much more.

As the name implies, Task spooler is a Unix batch system that can be used to add the Linux commands to the queue and execute them one after the other in numerical order (ascending order, to be precise). This can be very useful when you have to run a lots of commands, but you don't want to waste time waiting for one command to finish and run the next command. You can queue it all up and Task Spooler will execute them one by one. In the mean time, you can do other activities.

by Truong X. Nghiem, Rahul Mangharam

Peak power consumption is a universal problem across energy control systems in electrical grids, buildings, and industrial automation where the uncoordinated operation of multiple controllers result in temporally correlated electricity demand surges (or peaks). While there exist several different approaches to balance power consumption by load shifting and load shedding, they operate on coarse grained time scales and do not help in de-correlating energy sinks. The Energy System Scheduling Problem is particularly hard due to its binary control variables. Its complexity grows exponentially with the scale of the system, making it impossible to handle systems with more than a few variables.

We developed a scalable approach for fine-grained scheduling of energy control systems that novelly combines techniques from control theory and computer science. The original system with binary control variables are approximated by an averaged system whose inputs are the utilization values of the binary inputs within a given period. The error between the two systems can be bounded, which allows us to derive a safety constraint for the averaged system so that the original system's safety is guaranteed. To further reduce the complexity of the scheduling problem, we abstract the averaged system by a simple single-state single-input dynamical system whose control input is the upper-bound of the total demand of the system. This model abstraction is achieved by extending the concept of simulation relations between transition systems to allow for input constraints between the systems. We developed conditions to test for simulation relations as well as algorithms to compute such a model abstraction. As a consequence, we only need to solve a small linear program to compute an optimal bound of the total demand. The total demand is then broken down, by solving a linear program much smaller than the original program, to individual utilization values of the subsystems, whose actual schedule is then obtained by a low-level scheduling algorithm. Numerical simulations in Matlab show the effectiveness and scalability of our approach.

Coordinated Electric Vehicle Charging Control with Aggregator Power Trading and Indirect Load Control
James J.Q. Yu, Junhao Lin, Albert Y.S. Lam, Victor O.K. Li
(Submitted on 4 Aug 2015)

Due to the increasing concern on greenhouse gas emmissions and fossil fuel security, Electric Vehicles (EVs) have attracted much attention in recent years. However, the increasing popularity of EVs may cause stability issues to the power grid if their charging behaviors are uncoordinated. In order to address this problem, we propose a novel coordinated strategy for large-scale EV charging. We formulate the energy trade among aggregators with locational marginal pricing to maximize the aggregator profits and to indirectly control the loads to reduce power network congestion. We first develop a centralized iterative charging strategy, and then present a distributed optimization-based heuristic to overcome the high computational complexity and user privacy issues. To evaluate our proposed approach, a modified IEEE 118 bus testing system is employed with 10 aggregators serving 30 000 EVs. The simulation results indicate that our proposed approach can effectively increase the total profit of aggregators, and enhance the power grid stability. 

Subjects: Systems and Control (cs.SY)

I'm trying to schedule a repeating event to run every minute in Python 3...