Real-time image transmission is crucial to an emerging class of distributed embedded systems operating in open network environments. Examples include avionics mission replanning over Link-16, security systems based on wireless camera networks, and online collaboration using camera phones. Meeting image transmission deadlines is a key challenge in such systems due to unpredictable network conditions. In this paper, we present the design, modeling, and analysis of CAMRIT, a Control-based Adaptive Middleware framework for Real-time Image Transmission in distributed real-time embedded systems. CAMRIT features a distributed feedback control loop that meets image transmission deadlines by dynamically adjusting the quality of image tiles. We derive an analytic model that captures the dynamics of a moderately distributed middleware architecture. A control theoretic methodology is applied to systematically design a control algorithm with analytic assurance of system stability and performance, despite significant uncertainties in network bandwidth. CAMRIT has been successfully implemented as middleware service on top of the TAO real-time CORBA ORB. Experimental results demonstrate that CAMRIT can provide robust real-time guarantees under varying bandwidth for a representative application scenario.

A growing number of applications, often with firm or soft real-time requirements, are integrated on the same System on Chip, in the form of either hardware or software intellectual property. The applications are started and stopped at run time, creating different use-cases. Resources, such as interconnects and memories, are shared between different applications, both within and between use-cases, to reduce silicon cost and power consumption. The functional and temporal behaviour of the applications is verified by simulation and formal methods. Traditionally, designers resort to monolithic verification of the system as whole, as the applications interfere in shared resources, and thus affect each other’s behaviour. Due to interference between applications, the integration and verification complexity grows exponentially in the number of applications, and the task to verify correct behaviour of concurrent applications is on the system designer rather than the application designers. In this work, we propose a Composable and Predictable Multi-Processor System on Chip (CoMPSoC) platform template. This scalable hardware and software template removes all interference between applications through resource reservations. We demonstrate how this enables a divide-and-conquer design strategy, where all applications, potentially using different programming

Computing systems, ranging from small battery-operated embedded systems to more complex general purpose systems, are designed to satisfy various computation demands in some acceptable time. In doing so, the system is responsible for scheduling jobs/requests in a dynamic fashion. In addition, with power consumption recently becoming a critical issue, most systems are also responsible for their own power management. In some rare cases, the exact arrival time and execution time of jobs/requests is known, leading to precise scheduling algorithms and power management schemes. However, more often than not, there is no a-priori knowledge of the workload. This work evaluates dynamic voltage scaling (DVS) policies for power management in systems with unpredictable workloads. A clear winner is identified, a policy that reduces the energy consumption one order of magnitude compared to no power management and up to 40% (in real-life traces) and 50% (in synthetic workloads) compared to the second-best evaluated scheme.

A number of algorithms have been presented for handling software decoding of MPEG-2 streams based on buffering or rate adjustment focusing on providing good average quality. The potentially arising drops in quality are tolerated, e.g., in transmissions over the Internet; they cannot be accepted in high quality consumer products: these mandate real-time methods. When resources, such as processing power or network bandwidth, are limited and not all frames can be handled, best effort decoders incur unnecessary quality decrease while wasting resources.

We propose a method for fine grain QoS control of dataflow applications. We assume that the application software is described as the composition of actions (C-functions) with quality level parameters. The method allows to compute a QoS controller from this description, and average execution times, worst case execution times and deadlines for its actions. The controller computes dynamically feasible schedules and quality assignments for their actions. Furthermore, the control policy ensures optimal time budget utilization. A prototype tool implementing the method is shown as well as experimental results for a non trivial example. The results show the interest of fine grain QoS control for video encoders. 1.

Resource reservations are a very popular choice to schedule multimedia tasks. However, the high variability of the resource requirements hinders a static choice of the scheduling parameters. In this paper we address this problem by a combination of two strategies: adaptive reservations and resource reclaiming. The first one operates “locally” (using the information of a single task), the second one operates “globally ” distributing unused bandwidth between the tasks. In this paper, we show by analytical results and by extensive simulations that the two techniques can be safely and usefully combined. 1.

In this paper, we present a software architecture to support soft real-time applications, such as multimedia streaming and telecommunication systems, in open embedded systems. Examples of such systems are consumer electronic devices (as cellular phones, PDAs, etc.), as well as multimedia servers (video servers, VoIP servers, etc.) and telecommunication infrastructure devices. For such applications, it is important to keep under control the resource utilization of every task, otherwise the Quality of Service experienced by the users may be degraded. Our proposal is to combine a resource reservation scheduler (that allows us to partition the CPU time in a reliable way) and a feedback based mechanism for dynamically adjusting the CPU fraction (bandwidth) allocated to a tasks. In particular, our controller enables specified Quality of Service (QoS) levels for the application while keeping the allocated bandwidth close to its actual needs. The adaptation mechanism consists of the combination of a prediction and of a feedback correction that operates locally on each task. The consistency of the system is preserved by a supervisor component that manages overload conditions and enacts security policies. We implemented the framework in AQuOSA, a software architecture that runs on top of the Linux kernel. We provide extensive experimental validation of our results and offer evaluation of the introduced overhead, which is remarkably lower than the one introduced by other different solutions. I.

Abstract—Multimedia applications are often characterised by implicit temporal constraints but, in many cases, they are not programmed using any specialised real-time API. These “Legacy applications ” have no way to communicate their temporal constraints to the OS kernel, and their quality of service (QoS), being necessarily linked to the temporal behaviour, fails to satisfy acceptable standards. In this paper we propose an innovative way for dealing with these applications, based on the combination of an on-line identification mechanism (which extracts from high-level observations such important parameters as the execution rate) and an adaptive scheduler (specialised for legacy applications) that identifies the correct amount of CPU needed by each application. Preliminary experimental results are reported, proving the effectiveness of the proposed idea in providing a widely used multimedia player on Linux with appropriate QoS guarantees, through an appropriate choice of the scheduling parameters. Finally, a detailed road-map is presented with the possible extensions to the approach. I.

We consider the problem of power-aware Quality of Service (QoS) control for soft real-time embedded systems. Applications can have time-varying and scarcely known resource requirements, and can be activated and terminated at any time. However, they have the capability to switch among a discrete set of operation modes with different QoS levels and resource requirements. In addition, the platform provides resources with power-scaling capabilities and may be subject to power constraints. We present a QoS control architecture achieving optimum trade-offs between overall QoS and power consumption of the system, based on two nested control loops. The external one decides dynamically the optimum configuration for the system, in terms of application QoS modes and resource power modes, while the internal one modulates the resource allocations on a job by job basis, so as to respect timing constraints. We demonstrate the effectiveness of the approach by extensive simulations with trace data of real multimedia applications.

We present a quality management method for multimedia applications. The method takes as input an application software composed of actions. The execution times of actions are unknown increasing functions of quality level parameters. The method allows the construction of a Quality Manager which computes adequate action quality levels so as to meet QoS requirements for a given platform. These include deadlines for the actions as well as quality maximization and smoothness. We extend and improve results of a previous paper by focusing on the reduction of overhead due to quality management. We propose a symbolic quality management method using speed diagrams, a representation of the system’s dynamics. Instead of numerically computing a quality level for each action, the Quality Manager changes action quality levels based on the knowledge of constraints characterizing control relaxation regions. These are sets of states in which quality management for a given number of steps can be relaxed without degrading quality. We provide experimental results for quality management of an MPEG encoder, in particular performance benchmarks for both numeric and symbolic quality management. 1