On the use of code mobility mechanisms in real-time systems

Applications with soft real-time requirements can benefit from code mobility mechanisms, as long as those mechanisms support the timing and Quality of Service requirements of applications. In this paper, a generic model for code mobility mechanisms is presented. The proposed model gives system designers the necessary tools to perform a statistical timing analysis on the execution of the mobility mechanisms that can be used to determine the impact of code mobility in distributed real-time applications

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible

Iterative refinement approach for QOS-Aware service configuration

In heterogeneous environments, diversity of resources among the devices may affect their ability to perform services with specific QoS constraints, and drive peers to group themselves in a coalition for cooperative service execution. The dynamic selection of peers should be influenced by user’s QoS requirements as well as local computation availability, tailoring provided service to user’s specific needs. However, complex dynamic real-time scenarios may prevent the possibility of computing optimal service configurations before execution. An iterative refinement approach with the ability to trade off deliberation time for the quality of the solution is proposed. We state the importance of quickly finding a good initial solution and propose heuristic evaluation functions that optimise the rate at which the quality of the current solution improves as the algorithms have more time to run

The capacity exchange protocol

This paper proposes a new strategy to integrate shared resources and precedence constraints among real-time tasks, assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a capacity sharing and stealing mechanism to efficiently exchange bandwidth among tasks to minimise the degree of deviation from the ideal system’s behaviour caused by inter-application blocking. The proposed Capacity Exchange Protocol (CXP) is simpler than other proposed solutions for sharing resources in open real-time systems since it does not attempt to return the inherited capacity in the same exact amount to blocked servers. This loss of optimality is worth the reduced complexity as the protocol’s behaviour nevertheless tends to be fair and outperforms the previous solutions in highly dynamic scenarios as demonstrated by extensive simulations. A formal analysis of CXP is presented and the conditions under which it is possible to guarantee hard real-time tasks are discussed

A capacity sharing and stealing strategy for open real-time systems

This paper focuses on the scheduling of tasks with hard and soft real-time constraints in open and dynamic real-time systems. It starts by presenting a capacity sharing and stealing (CSS) strategy that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) reclaiming unused reserved capacity when jobs complete in less than their budgeted execution time and (ii) stealing reserved capacity from inactive non-isolated servers used to schedule best-effort jobs. CSS is then combined with the concept of bandwidth inheritance to efficiently exchange reserved bandwidth among sets of inter-dependent tasks which share resources and exhibit precedence constraints, assuming no previous information on critical sections and computation times is available. The proposed Capacity Exchange Protocol (CXP) has a better performance and a lower overhead when compared against other available solutions and introduces a novel approach to integrate precedence constraints among tasks of open real-time systems

Handling QoS dependencies in distributed cooperative real-time systems

Due to the growing complexity and adaptability requirements of real-time embedded systems, which often exhibit unrestricted inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand. This paper proposes an iterative refinement approach for a service’s QoS configuration taking into account services’ inter-dependencies and quality constraints, and trading off the achieved solution’s quality for the cost of computation. Extensive simulations demonstrate that the proposed anytime algorithm is able to quickly find a good initial solution and effectively optimises the rate at which the quality of the current solution improves as the algorithm is given more time to run. The added benefits of the proposed approach clearly surpass its reducedoverhead

Optimising and adapting the QoS of a dynamic set of inter-dependent tasks

Due to the growing complexity and adaptability requirements of real-time systems, which often exhibit unrestricted Quality of Service (QoS) inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may be inter-dependent. This paper focuses on optimising a dynamic local set of inter-dependent tasks that can be executed at varying levels of QoS to achieve an efficient resource usage that is constantly adapted to the specific constraints of devices and users, nature of executing tasks and dynamically changing system conditions. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions

Capacity sharing and stealing in serverbased real-time systems

A dynamic scheduler that supports the coexistence of guaranteed and non-guaranteed bandwidth servers is proposed. Overloads are handled by an efficient reclaiming of residual capacities originated by early completions as well as by allowing reserved capacity stealing of non-guaranteed bandwidth servers. The proposed dynamic budget accounting mechanism ensures that at a particular time the currently executing server is using a residual capacity, its own capacity or is stealing some reserved capacity, eliminating the need of additional server states or unbounded queues. The server to which the budget accounting is going to be performed is dynamically determined at the time instant when a capacity is needed. This paper describes and evaluates the proposed scheduling algorithm, showing that it can efficiently reduce the mean tardiness of periodic jobs. The achieved results become even more significant when tasks’ computation times have a large variance

Building adaptable, QoS-aware dependable embedded systems

Most of today’s embedded systems are required to work in dynamic environments, where the characteristics of the computational load cannot always be predicted in advance. Furthermore, resource needs are usually data dependent and vary over time. Resource constrained devices may need to cooperate with neighbour nodes in order to fulfil those requirements and handle stringent non-functional constraints. This paper describes a framework that facilitates the distribution of resource intensive services across a community of nodes, forming temporary coalitions for a cooperative QoSaware execution. The increasing need to tailor provided service to each application’s specific needs determines the dynamic selection of peers to form such a coalition. The system is able to react to load variations, degrading its performance in a controlled fashion if needed. Isolation between different services is achieved by guaranteeing a minimal service quality to accepted services and by an efficient overload control that considers the challenges and opportunities of dynamic distributed embedded systems

Dynamic QoS-Aware coalition formation

Users of wireless devices increasingly demand access to multimedia content with speci c quality of service requirements. Users might tolerate di erent levels of service, or could be satis ed with di erent quality combinations choices. However, multimedia processing introduces heavy resource requirements on the client side. Our work tries to address the growing demand on resources and performance requirements, by allowing wireless nodes to cooperate with each other to meet resource allocation requests and handle stringent constraints, opportunistically taking advantage of the local ad-hoc network that is created spontaneously, as nodes move in range of each other, forming a temporary coalition for service execution. Coalition formation is necessary when a single node cannot execute a speci c service, but it may also be bene cial when groups perform more e ciently when compared to a single s node performance