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The Network Calculus theory has been designed to compute upper bounds on delay and backlog in data networks. A lot of results have been developed to address different aspects. However, they are not all compatible with each other since they make different assumptions on the continuity of a core aspect of the model (the cumulative curves). However, real systems may mix several mechanisms. When modeling such a system, one has to choose one continuity hypothesis and limit the analysis to a subset of existing results. This paper addresses the continuity problem and argues formally that continuity issues are mathematical details that can be solved as long as the min-plus properties are used (minimal and maximal service, shaping). Conversely, it gives a counter-example for properties based on strict service, requiring a generalisation of the backlogged interval notion.

"The fundamental laws necessary for the mathematical treatment of large part of physics and the whole of chemistry are thus completely known, and the difficulty lies only in the fact that application of these laws leads to equations that are too complex to be solved." - Dirac 1929 The digital world of Internet of Things (IoT) will provide a high-resolution depiction of our physical world through measurements and other data - even high-definition "video," if you consider streaming data frames coming from a myriad of sensors embedded in everything we use. This depiction will have captured our interactions with the physical world and the interactions of digitally enhanced machines and devices. Tensors, as generalizations of vectors and matrices, provide a natural and scalable framework for handling data with such inherent structures and complex dependencies. Scalable tensor methods have attracted considerable amount of attention, with successes in a series of learning tasks, such as learning latent variable models, relational learning, spatio-temporal forecasting as well as training [19] and compression [20] of deep neural networks. In a Dagstuhl Perspectives Workshop on Tensor Computing for IoT, we validated the fundamental suitability of tensor methods for handling the massive amounts of data coming from connected cyber-physical systems (CPS). The multidisciplinary discourse among academics, industrial researchers and practitioners in the IoT/CPS domain and in the field of machine learning and tensor methods, exposed open issues that need to be addressed to reap value from the technological opportunity. This Manifesto summarizes the immediate action fields for advancement: IoT Tensor Data Benchmarks, Tensor Tools for IoT, and the evolution of a Knowledge Hub. The activities will also be channeled to create best practices and a common tensor language across the disciplines. In a not so distant future, basic infrastructures for living will be mainly data-driven, automa

Electronically controlled systems have become pervasive in modern society and are increasingly being used to control safety-critical applications, such as medical devices and transportation systems. At the same time, these systems are increasing in complexity at an alarming rate, making it difficult to produce system designs with guaranteed robust performance. Cyber-physical systems (CPS) is a new multi-disciplinary field aimed at providing a rigorous framework for designing and analyzing these systems, and recent developments in CPS-related fields provide techniques to increase robustness in the design and analysis of complex systems. This seminar brought together researchers from both academia and industry working in hybrid control systems, mechatronics, formal methods, and real-time embedded systems. Participants identified and discussed newly available techniques related to robust design and analysis that could be applied to open issues in the area of CPS and identified open issues and research questions that require collaboration between the communities. This report documents the program and the outcomes of Dagstuhl Seminar 16362 "Robustness in Cyber-Physical Systems".

Ethernet Switches are widely used in real-time distributed systems as a solution to guarantee the real-time behavior in communication. In this solution there are still some limitations which are the important obstacles obtaining timeliness in the network. These limitations are the limited number of priority levels as well as the possibility of memory overruns with consequent messages. The mentioned limitations can be eliminated using a master/slave technique along with FTT paradigm. The FTT-SE protocol which is a technique based on the master/slave and FTT methods was proposed to overcome the mentioned limitations. However, the FTT-SE protocol has been investigated for a small network architecture with a single switch and master node. Extension of this solution to larger networks is still an open issue. Three different architectures were suggested to scale the FTT-SE to large scale network. In this thesis we propose a solution that extends the FTT-SEprotocol while keeping the real-time behavior of the network. In this solution, we divided the network into a set of sub-networks, each contains one switch, set of slave nodes and one master node that connected to the associated switch in the network. Moreover, the switches are connected together directly without gateways and form a tree topology network. The solution includes both synchronous and asynchronous traffic in the network. We also show that the timeliness of the traffic can still be enforced. Moreover, to validate the solution we have designed and implemented a simulator based on the Matlab/Simulink which is a tool to evaluate different network architecture using Simulink blocks. All transmission can be visualized by the ordinary Scope block in the Simulink. Moreover, the end-to-end delay for all messages is calculated after the simulation running to show the response time of the network. Furthermore, the response time analysis is done for both synchronous and asynchronous messages in this thesis according to

Ethernet Switches are widely used in real-time distributed systems as a solution to guarantee the real-time behavior in communication. In this solution there are still some limitations which are the important obstacles obtaining timeliness in the network. These limitations are the limited number of priority levels as well as the possibility of memory overruns with consequent messages. The mentioned limitations can be eliminated using a master/slave technique along with FTT paradigm. The FTT-SE protocol which is a technique based on the master/slave and FTT methods was proposed to overcome the mentioned limitations. However, the FTT-SE protocol has been investigated for a small network architecture with a single switch and master node. Extension of this solution to larger networks is still an open issue. Three different architectures were suggested to scale the FTT-SE to large scale network. In this thesis we propose a solution that extends the FTT-SEprotocol while keeping the real-time behavior of the network. In this solution, we divided the network into a set of sub-networks, each contains one switch, set of slave nodes and one master node that connected to the associated switch in the network. Moreover, the switches are connected together directly without gateways and form a tree topology network. The solution includes both synchronous and asynchronous traffic in the network. We also show that the timeliness of the traffic can still be enforced. Moreover, to validate the solution we have designed and implemented a simulator based on the Matlab/Simulink which is a tool to evaluate different network architecture using Simulink blocks. All transmission can be visualized by the ordinary Scope block in the Simulink. Moreover, the end-to-end delay for all messages is calculated after the simulation running to show the response time of the network. Furthermore, the response time analysis is done for both synchronous and asynchronous messages in this thesis according to

Time-redundancy techniques are commonly used in real-time systems to achieve fault tolerance without incurring high energy overhead. However, reliability requirements of hard real-time systems that are used in safety-critical applications are so stringent that time-redundancy techniques are sometimes unable to achieve them. Standby sparing as a hardware-redundancy technique can be used to meet high reliability requirements of safety-critical applications. However, conventional standby-sparing techniques are not suitable for low-energy hard real-time systems as they either impose considerable energy overheads or are not proper for hard timing constraints. In this paper we provide a technique to use standby sparing for hard real-time systems with limited energy budgets. The principal contribution of this paper is an online energy-management technique which is specifically developed for standby-sparing systems that are used in hard real-time applications. This technique operates at runtime and exploits dynamic slacks to reduce the energy consumption while guaranteeing hard deadlines. We compared the low-energy standby-sparing (LESS) system with a low-energy time-redundancy system (from a previous work). The results show that for relaxed time constraints, the LESS system is more reliable and provides about 26% energy saving as compared to the time-redundancy system. For tight deadlines when the time-redundancy system is not sufficiently reliable (for safety-critical application), the LESS system preserves its reliability but with about 49% more energy consumption., Funding Agencies|Engineering and Physical Sciences Research Council, U.K.|EP/E035965/1|Research Vice-Presidency of the Sharif University of Technology

In this paper we investigate various options for modeling real-time network communication in an existing industrial component model, the rubus component model (RCM). RCM is used to develop resource-constrained real-time and embedded systems in many domains, especially automotive. Our goal is to extend RCM for the development of distributed embedded and real-time systems that employ real-time networks for communication among nodes (processors). The aim of exploring modeling options is to develop generic component types for RCM capable of modeling real-time networks used in the industry today. The selection of new component types is based on many factors including compliance with the industrial modeling standards, compatibility with the existing modeling objects in RCM, capability of modeling legacy systems and legacy communications, ability to model and specify timing related information (properties, requirements and constraints), ease of implementation and automatic generation of new components, and ability of the modeled application to render itself to early timing analysis. © 2011 Springer Science+Business Media B.V., 4th International Conference on Human-Centric Computing, HumanCom'11 and the 6th International Conference on Embedded and Multimedia Computing, EMC'11; Enshi;11 August 2011 through13 August 2011

Real-time applications such as e-commerce, flight control, chemical and nuclear control, and telecommunication are becoming increasingly sophisticated in their data needs, resulting in greater demands for real-time data services that are provided by real-time databases. Since the workload of real-time databases cannot be precisely predicted, they can become overloaded and thereby cause temporal violations, resulting in damage or even a catastrophe. Imprecise computation techniques address this problem and allow graceful degradation during overloads. In this paper, we present a framework for QoS specification and management consisting of a model for expressing QoS requirements, an architecture based on feedback control scheduling, and a set of algorithms implementing different policies and behaviors. Our approach gives a robust and controlled behavior of real-time databases, even for transient overloads and with inaccurate runtime estimates of the transactions. Further, performance experiments show that the proposed algorithms outperform a set of baseline algorithms that uses feedback control.

Instruction memoization is a promising technique to reduce the power consumption and increase the performance of future low-end/mobile multimedia systems. Power and performance efficiency can be improved by reusing instances of an already executed operation. Unfortunately, this technique may not always be worth the effort due to the power consumption and area impact of the tables required to leverage an adequate level of reuse. In this paper, we introduce and evaluate a novel way of understanding multimedia floating-point operations based on the fuzzy computation paradigm: performance and power consumption can be improved at the cost of small precision losses in computation. By exploiting this implicit characteristic of multimedia applications, we propose a new technique called tolerant memoization. This technique expands the capabilities of classic memoization by associating entries with similar inputs to the same output. We evaluate this new technique by measuring the effect of tolerant memoization for floating-point operations in a low-power multimedia processor and discuss the trade-offs between performance and quality of the media outputs. We report energy improvements of 12 percent for a set of key multimedia applications with small LUT of 6 Kbytes, compared to 3 percent obtained using previously proposed techniques., Peer Reviewed, Postprint (published version)