No description available.

International Telemetering Conference Proceedings / October 22-25, 1984 / Riviera Hotel, Las Vegas, Nevada / Software for real-time (time critical) control applications has been shown in military and industry studies to be a very expensive type of software effort. This type of software is not typically addressed in discussions of software architecture design methods and techniques, therefore the software engineer is usually left with a sparse design “tool kit” when confronted with overall system design involving time critical and/or control problems. This paper outlines the successful application of data flow and transaction analysis design methods to achieve a structured yet flexible software architecture for a fairly complex antenna controller used in automatic tracking antenna systems. Interesting adaptations of, and variations on, techniques described in the literature are discussed; as are issues of modularity, coupling, morphology, global data handling, and evolution (maintenance). Both positive and negative aspects of this choice of design method are outlined, and the importance of a capable real-time executive and conditional compilation and assembly is stressed.

A dissertation submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering / A multi-layered expert system shell that specifically addresses real-time issues is designed and implemented. The architecture of this expert system shell supports the concepts of parallelism, concurrent computation and competitive reasoning in that it allows several alternatives to be explored simultaneously. An inference engine driven by a hybrid of forward and backward chanining methods is used to achieve real-time response, and certainty factors are used for uncertainty management. Real-time responsiveness is improved by allowing the coexistence of procedural and declarative knowledge within the same system. A test bed that was set up in order to investigate the performance of the implemented shell is described. It was found in the performance analysis that the proposed system meets the real-time requirements as specified in this research. / Andrew Chakane 2018

This thesis looks in depth at telephony server clusters, the modern switchboards at the core of a packet-based telephony service. The most widely used de facto standard protocols for telecommunications are the Session Initiation Protocol (SIP) and the Real Time Protocol (RTP). SIP is a signaling protocol used to establish, maintain, and tear down communication channel between two or more parties. RTP is a media delivery protocol that allows packets to carry digitized voice, video, or text. SIP telephony server clusters that provide communications services, such as an emergency calling service, must be scalable and highly available. We evaluate existing commercial and open source telephony server clusters to see how they differ in scalability and high availability. We also investigate how a scalable SIP server cluster can be built on a cloud computing platform. Elasticity of resources is an attractive property for SIP server clusters because it allows the cluster to grow or shrink organically based on traffic load. However, simply deploying existing clusters to cloud computing platforms is not good enough to take full advantage of elasticity. We explore the design and implementation of clusters that scale in real-time. The database tier of our cluster was modified to use a scalable key-value store so that both the SIP proxy tier and the database tier can scale separately. Load monitoring and reactive threshold-based scaling logic is presented and evaluated. Server clusters also need to reduce processing latency. Otherwise, subscribers experience low quality of service such as delayed call establishment, dropped calls, and inadequate media quality. Cloud computing platforms do not guarantee latency on virtual machines due to resource contention on the same physical host. These extra latencies from resource contention are temporary in nature. Therefore, we propose and evaluate a mechanism that temporarily distributes more incoming calls to responsive SIP proxies, based on measurements of the processing delay in proxies. Availability of SIP server clusters is also a challenge on platforms where a node may fail anytime. We investigated how single component failures in a cluster can lead to a complete system outage. We found that for single component failures, simply having redundant components of the same type are enough to mask those failures. However, for client-facing components, smarter clients and DNS resolvers are necessary. Throughout the thesis, a prototype SIP proxy cluster is re-used, with variations in the architecture or configuration, to demonstrate and address issues mentioned above. This allows us to tie all of our approaches for different issues into one coherent system that is dynamically scalable, is responsive despite latency varations of virtual machines, and is tolerant of single component failures in cloud platforms.

This research addressed the design and implementation of a polynomial-complexity deadlock avoidance controller for a flexible manufacturing cell modeled using Colored Petri Nets. The cell model is robust to changes in the part types to be manufactured in the system and is automatically generated using the interaction of the resources in the cell and the technological capabilities of the machines. The model also captures dynamic routing flexibility options. The framework introduced separates the cell model from the control logic allowing the system designer to implement and test various control algorithms using the same cell model. The controller adopts the neighborhood deadlock avoidance policy to resolve deadlocks and control the resource allocation decisions within the system. The evaluation of the performance of systems controlled by not maximally permissive algorithms is important in determining the applicability of the control algorithms. There are many polynomial time deadlock avoidance algorithms proposed for the control of general resource allocation systems. However, the permissiveness of these algorithms is not quantified and the applicability of these algorithms in terms of effective resource utilization remains unanswered. The performance of automated manufacturing cells controlled using the neighborhood deadlock avoidance policy is benchmarked by comparing its performance with other control policies.

Thesis (M.S.)--Ohio University, June, 2007. / Title from PDF t.p. Includes bibliographical references.

Multimedia applications such as video streaming and Voice over IP are becoming common today with the tremendous growth of the Internet. General purpose operating systems thus are required to support these applications. These multimedia applications have some timing constraints that need to be satisfied for good quality. For example, video streaming applications require that each video frame be decoded in time to be displayed every 33.3 milliseconds. In order to satisfy these timing requirements, general purpose operating systems need to have fine-grained scheduling. Current general purpose operating systems unfortunately are designed to maximize throughput to serve traditional data-oriented applications and have coarse-grained scheduling and timers. Time Sensitive Linux (TSL), designed by Goel, et al., solves this problem with fine-grained timers and schedulers. The scheduler for TSL is implemented at a very low level. The controller that implements the algorithm for resource allocation is implemented at a higher level. This controller can easily be modified to implement new control algorithms. Successful implementation of resource allocation to satisfy timing constraints of multimedia applications requires two problems to be addressed. First, the resources required by the application to satisfy the timing constraints should not exceed the total available resources in the system. Second, the controller must adapt to changing needs of the applications and allocate enough resources to satisfy the timing constraints of each application over time. The first problem has been addressed elsewhere using intelligent data dropping with TSL. We focus on the second problem in this thesis. We design a proportion-period controller in this thesis for allocating CPU to multimedia video applications with timing constraints. The challenges for the controller design include the coarse granularity of the time-stamp markings of the video frames, the unpredictable decoding completion times of the frames, the large variations in the decoding times of the frames, and the limit of the control actuation to positive values. We set up the problem in a state space. We design a predictive estimating controller to allocate the proportion of the CPU to a thread when its long term error is small. When the decoding process is running behind by more than a certain threshold, we switch to a different controller to drive the error back to a small value. This controller is the solution to a dynamic optimization LQR tracking problem. / Graduation date: 2003

No description available.

As control systems are becoming more and more complex, system complexity is rapidly becoming a limiting factor in the efficacy of established techniques for control systems design. To cope with the growing complexity, control architectures often have a hierarchical structure. At the base of the system pyramid lie feedback loops with simple closed-loop control laws. These are followed, at a higher level, by discrete control logics. Such hierarchical systems typically have a hybrid nature. A common approach to addressing these types of complexity consists of decomposing, in the time domain, the control task into a number of modes, i.e. control laws dedicated to carrying out a limited task. This type of control generally involves switching laws among the various modes, and its design poses a major challenge in many application domains. The primary goal of this thesis is to develop a unified framework for addressing this challenge. To this end, the contribution of this thesis is threefold: 1. An algorithmic framework for how to optimize the performance of switched autonomous systems is derived. The optimization concerns both the sequence in which different modes appear in and the duration of each mode. The optimization algorithms are presented together with detailed convergence analyses. 2. Control strategies for how to optimize switched autonomous systems operating in real time, and when the initial state of the system is unknown, are presented. 3. A control strategy for how to optimally navigate an autonomous mobile robot in real-time is presented and evaluated on a mobile robotics platform. The control strategy uses optimal switching surfaces for when to switch between different modes of operations (behaviors).

This thesis provides a real-time algorithmic optimal control framework for autonomous switched systems. Traditional optimal control approaches for autonomous switched systems are open-loop in nature. Therefore, the switching times of the system can not be adjusted or adapted when the system parameters or the operational environments change. This thesis aims to close this loop, and apply adaptations to the optimal switching strategy based on new information that can only be captured on-line. One important contribution of this work is to provide the means to allow feedback (in a general sense) to the control laws (i.e. the switching times) of the switched system so that the control laws can be updated to maintain optimality of the switching-time control inputs. Furthermore, convergence analyses for the proposed algorithms are presented. The effectiveness of the real-time algorithms is demonstrated by an application in optimal formation and coverage control of a networked system. This application is implemented on a realistic simulation framework consisting of a number of Unmanned Aerial Vehicles (UAVs) that interact in a virtual 3D world.