A Systematic Survey of Multiprocessor Real-Time Scheduling and Synchronization Protocol

Background: Nowadays, there is an immense increase in the demand for high power computation of real-time workloads and the trend towards multi-core and multiprocessor CPUs. The real-time system needs to be implemented upon multiprocessor platforms. Introduction: The nature of processors in an embedded real-time system is changing day by day. The two most significant challenges in a multiprocessor environment are scheduling and synchronization. The popularity of real-time multi-core systems has exploded in recent years, driving the rapid development of a variety of methods for multiprocessor scheduling of essential tasks, on the other hand, these systems have constraints when it comes to maintaining synchronization in order to access shared resources. Method: This research work presents a systematic review of different existing scheduling algorithms and synchronization protocols for shared resources in a real-time multiprocessor environment. The manuscript also presents a study based on various metrics of resource scheduling and comparison among different resource scheduling techniques. Result and Conclusion: The survey classifies open issues, key challenges, and likely useful research directions. Finally, we accept that there is still a lot of capacity in getting better resource management and further maintaining the overall quality. The paper considers such a future path of research in this field.

EDF-Adaptive: A New Semipartitioned Scheduling Algorithm for Multiprocessor Real-Time

Most of the multiprocessor real-time scheduling algorithms follow the partitioned approach, the global approach, or the semipartitioned approach which is a hybrid of the first two by allowing a small subset of tasks to migrate. EDF-fm (Earliest Deadline First-based Fixed and Migrating) and EDF-os (Earliest Deadline First-based Optimal Semipartitioned) are semipartitioned approaches and were proposed for soft real-time sporadic task systems. Despite their desirable property that migrations are boundary-limited such as they can only occur at job boundaries, EDF-fm and EDF-os are not always optimal and have higher tardiness and cost of overheads due to task migration. To address these issues, in this paper, we classify the systems into different types according to the utilization of their tasks and propose a new semipartitioned scheduling algorithm, earliest deadline first-adaptive, dubbed as EDF-adaptive. Our experiments show that EDF-adaptive can achieve better performance than EDF-fm and EDF-os, in terms of system utilization and tardiness overhead. It is also proved that EDF-adaptive is able to lessen the task migration overhead, by reducing the number of migrating jobs and the number of processors to which a task is migrated.

Climate and Environmental Benefit Study of PV Resource Development: Case Study of Angola

Vigorously promoting the development of photovoltaic (PV) resources is a positive measure taken by humanity in response to the changes in global climate and environment. At the same time, combining photovoltaic power generation systems with traditional power generation systems, using the advantages of different power generation systems to achieve real-time scheduling optimization has become an urgent problem to be solved in engineering applications. This paper attempts to study the climate and environmental benefits of the development of photovoltaic resource in Africa by taking Angola as an example based on actual project data. According to the characteristics, load requirements, seasonal characteristics and actual engineering background of Tombwa in Angola, a baseline Scenario and four comparative Scenarios were established, and the operating costs of the five Scenarios in local rainy season and dry season were obtained respectively. The cost of electricity for the five Scenarios calculated subsequently. Through real-time scheduling and optimization of the software, the emission characteristics of CO2, NOx and CO under five Scenarios are obtained, and the climate benefits and environmental benefits of the five scenarios are further analyzed and compared. The results show that the development of photovoltaic resources in Angola has good climate and environmental benefits. In addition, the combine application of diesel, PV and battery power system will be the most effective of the five Scenarios to reduce the CO2 emissions with the lowest levelized cost of electricity (LCOE) of 0.38 yuan/kwh, as a cost-effective solution in remote areas of Angola, Africa.

Real Time Scheduling of Nonidentical Multiple Batch Processors with Machine Eligibility Restriction

This study addresses a new problem on scheduling of nonidentical multiple diffusion furnaces (NMDF) with machine eligibility restriction (MER) along with important real-life problem characteristics such as multiple and incompatible job-families, different release time, different due-date, non-agreeable release time & due-date, and occurrences of randomly and dynamically generated real time events (jobs and/or resources related) to minimize total weighted tardiness. Due to the computational difficulty in obtaining an optimal solution for large real-life sized scheduling of NMDF, an alternate solution procedure: heuristic algorithm based on due-date based dispatching rule, called due-date based heuristic algorithm (DDHA) is constructed in this study. Though there has been extensive scheduling research relating to the use of existing dispatching rules in semiconductor manufacturing along with/without new dispatching rules, there is no comparative analysis of all due-date based dispatching rules for real time scheduling (RTS) of NMDF-MER. Hence, this study proposes 20 variants of DDHA, considering various due-date based dispatching rules, for RTS-NMDF-MER and compares their performance. A suitable experimental design is developed and randomly generated 270 instances to represent the research problem considered in this study. From the empirical and statistical analysis carried out in this study, the better performing DDHA(s), for RTS-NMDF-MER, are identified.

Optimal Dispatch of Multi-Energy Integrated Micro-Energy Grid: A Model Predictive Control Method

In order to reduce the impacts caused by large-scale renewable energy resources accessing the utility grid, the micro-energy grid system, as a natural extension of the microgrid in the energy internet era, is proposed and developed to provide a new solution for the optimal utilization of renewable energy resources. In this paper, a multi-energy integrated micro-energy system is proposed which contains wind, PV, bedrock energy storage, magnetic levitation electric refrigeration, solid oxide fuel cell, solar thermal collector, energy storage, and V2G technologies, and detailed models of the energy generation/conversion/storage devices are formulated. Besides this, the uncertainties of renewable energy resources and cold/heat/electricity loads are considered, and the optimal dispatch problem of the micro-energy system is established from day-ahead and real-time time scales based on a model predictive control method. The day-ahead optimal scheduling aims at economic optimization and guides real-time scheduling, and real-time scheduling utilizes rolling optimization and a feedback correction mechanism to effectively correct the deviation of renewable energy generations and loads at a real-time horizon, which improves the optimization control accuracy, follows the day-ahead dispatch plan, and ensures the economics of real-time scheduling at the same time.