## 2 Related Work  
Real-time IoT systems also commonly known as RT-IoT [22]. At their core, RT-IoT often intersects with traditional real-time systems and modern CPS. In RT-IoT, the embedded devices are controlled remotely and thus enable conventional real-time systems to be controlled remotely. In recent years, the scope of real-time systems has been broadened, and numerous real-time applications and frameworks have been proposed for IoT and CPS systems to remotely control and schedule real-time jobs [23; 24; 25]. Scheduling problem on IoT has lately attracted many researchers, and notable efforts have been put forward in this regard. Much like in traditional real-time systems, in IoT, one primary issue is how to deal with constrained devices and design context-aware strategies [26; 27]. Techniques like \"Normally-off\" sensors are proposed to limit the power consumption of IoT devices by activating sensors only on specific events. When sensors finished performing designated tasks, they are turned off to control the power they consume in idle state [26]. Likewise, in a more recent work, an energy-efficient packet scheduling is proposed for IoT application [27]. Energy and power are often portrayed as an optimisation variable, and different scheduling techniques are applied to minimise these variables. The analysis of power-consumption in embedded devices has been vital in general real-time systems and modern RT-IoT systems. [PERSON] et al. [28] first analysed the correlation between power and energy, and claimed that power and energy consumption of embedded devices is a function of CPU clock cycles. Therefore, the focus of the later researchers was to design scheduling strategies which consume less CPU clock cycles and hence less power and energy. One primary driver for high CPU clock-cycles is the poor design of periods of input tasks which lead to a high value of hyper-period. Therefore, the hyper-period optimisation is the focus of many researchers to optimise the power and energy [20; 21; 29]. As discussed that a high value of hyper-period is produced due to the poor design of tasks' periods, therefore, the period is considered a key parameter in the design of the input tasks for real-time systems. The design period was initially considered as an optimisation problem [30]. In such formulations, the performance of the system is captured through an exponentially decreasing function. Furthermore, the period is modelled as an optimisation variable that can have any values within a certain feasible range to ensure the schedulability of the system. In scheduling theory, there are two broad categories of systems, dynamic-priority and static-priority. RM algorithm is based on static-priority and computes the priority of an input task based on its period. The smaller the period will be, the higher will be the priority and vice versa. On the other hand, the EDF is a dynamic-priority algorithm in which the priority of the input task dynamically changes as the scheduling advances. To choose the optimal period for given task sets, [PERSON] et al. [31] proposed an algorithm that makes use of scheduling methods based on fixed priority. This algorithm serves as the foundation for many other algorithms, and several researchers have extended this algorithm to improve its performance. Ref. [32] have considered the stability radius as the critical performance criteria and they have developed an algorithm for assigning optimal period to the tasks, i.e., state feedback controllers. [PERSON] et al. [33] presented a scheme based on feasibility constraints to select given tasks' deadlines and periods. Multiple tasks having overlapping execution time will result in a conflict that is addressed through formulation for an optimisation problem by proposing a convex approximation scheme based on deadline space of EDF. [PERSON] et al.