bot_exp.py 文件源码

def prepare(self, simulation):
        num_tasks = len(self.tasks)

        # build ECT matrix
        ECT = np.zeros((num_tasks, len(self.hosts)))
        for t, task in enumerate(self.tasks):
            stage_in = task.parents[0]
            for h, host in enumerate(self.hosts):
                if stage_in.amount > 0:
                    ect = stage_in.get_ecomt(self.master, host) + task.get_eet(host)
                else:
                    ect = task.get_eet(host)
                ECT[t][h] = ect
        # print(ECT)

        # build schedule
        task_idx = np.arange(num_tasks)
        for _ in range(0, len(self.tasks)):
            min_hosts = np.argmin(ECT, axis=1)
            min_times = ECT[np.arange(ECT.shape[0]), min_hosts]

            if self.strategy == ListHeuristic.MIN_FIRST:
                t = np.argmin(min_times)
            elif self.strategy == ListHeuristic.MAX_FIRST:
                t = np.argmax(min_times)
            elif self.strategy == ListHeuristic.SUFFERAGE:
                if ECT.shape[1] > 1:
                    min2_times = np.partition(ECT, 1)[:,1]
                    sufferages = min2_times - min_times
                    t = np.argmax(sufferages)
                else:
                    t = np.argmin(min_times)

            task = self.tasks[int(task_idx[t])]
            h = int(min_hosts[t])
            host = self.hosts[h]
            ect = min_times[t]

            self.host_tasks[host.name].append(task)
            logging.debug("%s -> %s" % (task.name, host.name))

            task_idx = np.delete(task_idx, t)
            ECT = np.delete(ECT, t, 0)
            stage_in = task.parents[0]
            if stage_in.amount > 0:
                task_ect = stage_in.get_ecomt(self.master, host) + task.get_eet(host)
            else:
                task_ect = task.get_eet(host)
            ECT[:,h] += task_ect
            # print(ECT)