Resource Management in Multimedia Networked Systems

Error-free multimedia data processing and communication includes providing guaranteed services such as the colloquial telephone. A set of problems have to be solved and handled in the control-management level of the host and underlying network architectures. We discuss in this paper \u27resource management\u27 at the host and network level, and their cooperation to achieve global guaranteed transmission and presentation services, which means end-to-end guarantees. The emphasize is on \u27network resources\u27 (e.g., bandwidth, buffer space) and \u27host resources\u27 (e.g., CPU processing time) which need to be controlled in order to satisfy the Quality of Service (QoS) requirements set by the users of the multimedia networked system. The control of the specified resources involves three actions: (1) properly allocate resources (end-to-end) during the multimedia call establishment, so that traffic can flow according to the QoS specification; (2) control resource allocation during the multimedia transmission; (3) adapt to changes when degradation of system components occurs. These actions imply the necessity of: (a) new services, such as admission services, at the hosts and intermediate network nodes; (b) new protocols for establishing connections which satisfy QoS requirements along the path from send to receiver(s), such as resource reservation protocol; (c) new control algorithms for delay, rate and error control; (d) new resource monitoring protocols for reporting system changes, such as resource administration protocol; (e) new adaptive schemes for dynamic resource allocation to respond to system changes; and (f) new architectures at the hosts and switches to accommodate the resource management entities. This article gives an overview of services, mechanisms and protocols for resource management as outlined above

On the integration of application level and resource level QoS control for real-time applications

We consider a dynamic set of soft real-time applications using a set of shared resources. Each application can execute in different modes, each one associated with a level of Quality of Service (QoS). Resources, in their turn, have different modes, each one with a speed and a power consumption, and are managed by a Reservation Based scheduler enabling a dynamic allocation of the fraction of resources (bandwidth) assigned to each application. To cope with dynamic changes of the application, we advocate an adaptive resource allocation policy organised in two nested feedback loops. The internal loop operates on the scheduling parameter to obtain a resource allocation that meets the temporal constraints of the applications. The external loop operates on the QoS level of the applications and on the power level of the resources to strike a good trade-off between the global QoS and the energy consumption. This loop comes into play whenever the workload of the application exceeds the bounds that permit the internal loop to operate correctly, or whenever it decreases below a level that permit more aggressive choices for the QoS or substantial energy saving

Real-time scheduling for media processing using conditionally guaranteed budgets

In dit proefschrift behandelen we een planningsprobleem dat haar oorsprong vindt in het kosteneffectief verwerken van verschillende media door software in consumentenapparaten, zoals digitale televisies. De laatste jaren zijn er trends gaande van analoge naar digitale systemen, en van verwerking van digitale signalen door speci??eke, toepassingsgerichte hardware naar verwerking door software. Voor de verwerking van digitale media door software wordt gebruik gemaakt van krachtige programmeerbare processoren. Om te kunnen wedijveren met bestaande oplossingen is het van belang dat deze programeerbare hardware zeer kosteneffectief wordt gebruikt. Daarnaast dienen de bestaande eigenschappen van deze consumenten apparaten, zoals robuustheid, stabiliteit, en voorspelbaarheid, behouden te blijven als er software wordt gebruikt. Verder geldt dat er gelijktijdig meerdere media stromen door een consumenten apparaat verwerkt moeten kunnen worden. Deze uitdaging is binnen de onderzoekslaboratoria van Philips aangegaan in het zogenoemde Video-Quality-of-Service programma, en het werk dat in dit proefschrift beschreven wordt is binnen dat programma ontstaan. De binnen dat programma gekozen aanpak is gebaseerd op schaalbare algoritmen voor de verwerking van media, budgetten voor die algoritmen, en software dat de instelling van die algoritmen en de grootte van de budgetten aanpast tijdens de verwerking van de media. Ten behoeve van het kosteneffectief gebruik van de programmeerbare processoren zijn de budgetten krap bemeten. Dit proefschrift geeft een uitvoerige beschrijving van die aanpak, en van een model van een apparaat dat de haalbaarheid van die aanpak aantoont. Vervolgens laten we zien dat die aanpak leidt tot een probleem wanneer er gelijktijdig meerdere stromen worden verwerkt die verschillende relatieve relevanties hebben voor de gebruiker van het apparaat. Om dit probleem op te lossen stellen we het nieuwe concept van voorwaardelijk gegarandeerde budgetten voor, en beschrijven we hoe dat concept kan worden gerealiseerd. De technieken voor het analyseren van het planningprobleem voor budgetten zijn gebaseerd op bestaande technieken voor slechtste-gevals-analyse voor periodieke real-time taken. We breiden die bestaande technieken uit met technieken voor beste-gevals-analyse zodat we apparaten die gebruik maken van dit nieuwe type budget kunnen analyseren

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

A Scalable and Adaptive Network on Chip for Many-Core Architectures

In this work, a scalable network on chip (NoC) for future many-core architectures is proposed and investigated. It supports different QoS mechanisms to ensure predictable communication. Self-optimization is introduced to adapt the energy footprint and the performance of the network to the communication requirements. A fault tolerance concept allows to deal with permanent errors. Moreover, a template-based automated evaluation and design methodology and a synthesis flow for NoCs is introduced

Management of Cloud Infastructures: Policy-Based Revenue Optimization

Competition on global markets forces many enterprises to make use of new applications, reduce process times and at the same time cut the costs of their IT-infrastructure. To achieve this, it is necessary to maintain a high degree of flexibility with respect to the IT-infrastructure. Facing this challenge the idea of Cloud computing has been gaining interest lately. Cloud services can be accessed on demand without knowledge of the underlying infrastructure and have already succeeded in helping companies deploy products faster. Using Cloud services the New York Times managed to convert scanned images containing 11 million articles into PDF within 24 hours at a cost of merely 240 US-$. However Cloud providers will only offer their services, if they can realize sufficient benefit. To achieve this, the efficiency of Cloud infrastructure management must be increased. To this end we propose the use of concepts from revenue management and further enhancements

Generalizing List Scheduling for Stochastic Soft Real-time Parallel Applications

Advanced architecture processors provide features such as caches and branch prediction that result in improved, but variable, execution time of software. Hard real-time systems require tasks to complete within timing constraints. Consequently, hard real-time systems are typically designed conservatively through the use of tasks? worst-case execution times (WCET) in order to compute deterministic schedules that guarantee task?s execution within giving time constraints. This use of pessimistic execution time assumptions provides real-time guarantees at the cost of decreased performance and resource utilization. In soft real-time systems, however, meeting deadlines is not an absolute requirement (i.e., missing a few deadlines does not severely degrade system performance or cause catastrophic failure). In such systems, a guaranteed minimum probability of completing by the deadline is sufficient. Therefore, there is considerable latitude in such systems for improving resource utilization and performance as compared with hard real-time systems, through the use of more realistic execution time assumptions. Given probability distribution functions (PDFs) representing tasks? execution time requirements, and tasks? communication and precedence requirements, represented as a directed acyclic graph (DAG), this dissertation proposes and investigates algorithms for constructing non-preemptive stochastic schedules. New PDF manipulation operators developed in this dissertation are used to compute tasks? start and completion time PDFs during schedule construction. PDFs of the schedules? completion times are also computed and used to systematically trade the probability of meeting end-to-end deadlines for schedule length and jitter in task completion times. Because of the NP-hard nature of the non-preemptive DAG scheduling problem, the new stochastic scheduling algorithms extend traditional heuristic list scheduling and genetic list scheduling algorithms for DAGs by using PDFs instead of fixed time values for task execution requirements. The stochastic scheduling algorithms also account for delays caused by communication contention, typically ignored in prior DAG scheduling research. Extensive experimental results are used to demonstrate the efficacy of the new algorithms in constructing stochastic schedules. Results also show that through the use of the techniques developed in this dissertation, the probability of meeting deadlines can be usefully traded for performance and jitter in soft real-time systems