# Reducing Dynamic Power Consumption in Mixed-Critical Real-Time Systems
## 1 Introduction  
Real-time systems take some inputs and produce outputs in a time-bound manner. Meeting deadline is the core concept of a real-time system such that missing a deadline may collapse the whole system. A real-time system has fragile uses such as an airline command system, which is so highly critical that a single failure can cause a major explosion. Similarly, a real-time system is employed in satellite receivers for collecting highly important information and failures can misguide and result in a major collapse [1]. Daily home appliances such as microwave, AC, electric power system, and refrigerator, etc. can also employ a real-time system. In a real-time system, the term mixed-critically means that high-critical tasks must meet their deadlines at the cost of missing deadlines for certain low-criticality tasks. Therefore mixed-criticality can be used as a tool for assuring the system failure needed for different components. In the literature, mixed-criticality is identified as mission-criticality and LO- (low-criticality) criticality. The mission-criticality (hard real-time) failures can cause major damage in the systems such as loss of flight control, receiving wrong information via radar system, and misguiding satellite data. On the other hand, LO-criticality (soft real-time) is relaxed critical and can be considered less destructive such that deadlines can be violated occasionally. A mixed-criticality system \((MCS)\) is characterized to execute in each of two modes, high and low critical mode [2]. Each task is described by the shortest arrival time of a task (period denoted by \(P\)),deadline (denoted by \(D\)), and Worst case execution time \(WCET\) one per criticality level, denoted by \((C_{i}(LO)\) and \(C_{i}(HI)\). The condition of the basic \(MCS\) model is the system beginning in the LO-criticality mode and can stay in that mode given all jobs execute within their low-criticality computation times \((C_{i}(LO)\). If any job executes for its \((C_{i}(LO)\) execution time without any signal, the system directly moves to high-criticality (HI)-criticality mode. In HI-criticality mode, LO-criticality jobs should not be executed but some level of service should be maintained if at all possible as LO-criticality tasks are still critical. In this scheme [PERSON], [PERSON], and [PERSON] [3; 4; 5] consider a simple protocol for mode switch situations for controlling the time of the change of mode back to low-criticality, which is to wait until the CPU is idle and then safely be made. Producing a somewhat more efficient scheme, [PERSON] [6] extends this approach that can be applied to a globally scheduling multi-processor system in which the CPU may never get to an ideal tick. In a dual criticality level that has just shifted into a HI-criticality mode and hence no LO-criticality tasks are computed, its protocol is to first wait when the HI-criticality task has completed its high computation time and then wait for the next high priority task, and this continues until the lowest priority job is inactive and it is then safe to reintroduce all low-criticality jobs. If there is a further misbehavior of low computation bound the protocol drops all low-criticality jobs if any jobs compute more then its \((C_{i}(LO)\) value. Dynamic voltage and frequency scaling (DVFS) is a commonly-used technique for reducing the overall energy consumption, which is minimized in a large-scale data processing environment. This technique is based on utilizing two common parameters such as processor voltage and processor frequency to reduce power consumption. DVFS enable processor maximum power consumption, which can be accomplished by decreasing the operating frequency level of a processor. However, a scale-down of the processor's CPU frequency causes a delay in task completion time. Much of the literature has been focused on reducing power consumption in embedded systems. A similar technique, real-time dynamic voltage and frequency scaling (RT-DVFS), studied reducing power consumption for periodic and aperiodic tasks.