Quantum Optimization of Resource Distribution Management for Multi-Task, Multi-Subtasks

This paper proposes a new optimization strategy for resource distribution management based on a quantum algorithm, as a way to reduce the computational complexity in finding the optimum deployment scenario, taking into consideration the required conditions and constraints of the resource distribution system. We show that the quantum method computes the results in minimum time and outperforms on the other classical algorithms in terms of computational complexity

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

System-level modeling and analysis of multimedia-soc platforms

Ph.DDOCTOR OF PHILOSOPH

Optimal Task Rate Selection in Fixed Priority Systems

The design phase of any real-time system requires balancing the limited computational resources against the functional requirements and the performance of the application. The optimal design solution can be obtained by solving an optimization problem where the system performance is maximized within the schedulability constraints. In this paper, we provide a procedure that finds the task activation rates maximizing a performance function within the deadline constraints in systems scheduled by fixed priorities. First, we describe the exact feasibility region in the domain of task frequencies. Then, we introduce a procedure that starts by finding an initial solution, and incrementally improves it by using an original branch and bound search, until the global optimum is reached. Experiments show that our algorithm finds the optimal task periods for practical problems with a remarkable speedup, if compared with existing techniques. When the size of the problem makes the global search intractable, the experiments show that the algorithm can still find a high quality solution in the very early steps

Optimal Task Rate Selection in Fixed Priority Systems

The design phase of any real-time system requires balancing the limited computational resources against the functional requirements and the performance of the application. The optimal design solution can be obtained by solving an optimization problem where the system performance is maximized within the schedulability constraints. In this paper, we provide a procedure that finds the task activation rates maximizing a performance function within the deadline constraints in systems scheduled by fixed priorities. First, we describe the exact feasibility region in the domain of task frequencies. Then, we introduce a procedure that starts by finding an initial solution, and incrementally improves it by using an original branch and bound search, until the global optimum is reached. Experiments show that our algorithm finds the optimal task periods for practical problems with a remarkable speedup, if compared with existing techniques. When the size of the problem makes the global search intractable, the experiments show that the algorithm can still find a high quality solution in the very early steps