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Many modern applications require high-performance platforms to deal with a variety of algorithms requiring massive calculations. Moreover, low-cost powerful hardware (e.g., GPU, PPU) and CPUs with multiple cores have become abundant, and can be combined in heterogeneous architectures. To cope with this, reconfigurable computing is a potential paradigm as it can provide flexibility to explore the computational resources on hybrid and multi-core desktop architectures. The workload can optimally be (re)distributed over heterogeneous cores along the lifecycle of an application, aiming for best performance. As the first step towards a run-time reconfigurable load-balancing framework, application requirements and crosscutting concerns related to timing play an important role for task allocation decisions. In this paper, we present the use of aspect-oriented paradigms to address non-functional application timing constraints in the design phase. The DERAF aspectspsila framework is extended to support reconfiguration requirements; and a strategy for load-balancing is described. In addition, we present preliminary evaluation using an Unmanned Aerial Vehicle (UAV) based surveillance system as case study.

Modern surveillance systems, such as those based on the use of Unmanned Aerial Vehicles, require powerful high- performance platforms to deal with many different algorithms that make use of massive calculations. At the same time, low- cost and high-performance specific hardware (e.g., GPU, PPU) are rising and the CPUs turned to multiple cores, characteriz- ing together an interesting and powerful heterogeneous execu- tion platform. Therefore, reconfigurable computing is a poten- tial paradigm for those scenarios as it can provide flexibility to explore the computational resources on heterogeneous cluster attached to a high-performance computer system platform. As the first step towards a run-time reconfigurable workload bal- ancing framework targeting that kind of platform, application time requirements and its crosscutting behavior play an impor- tant role for task allocation decisions. This paper presents a strategy to reallocate specific tasks in a surveillance system composed by a fleet of Unmanned Aerial Vehicles using aspect- oriented paradigms in order to address non-functional applica- tion timing constraints in the design phase. An aspect support from a framework called DERAF is used to support reconfigu- ration requirements and provide the resource information needed by the reconfigurable load-balancing strategy. Finally, for the case study, a special attention on Radar Image Process- ing will be given.

The use of sensor networks in different kinds of sophisticated applications is emerging due to several advances in sensor/embedded system technologies. However, the integration and coordination of heterogeneous sensors is still a challenge, especially when the target application environment is susceptible to changes. Such systems must adapt themselves in order to fulfil increasing requirements. Especially the handling of real-time requirements is a challenge in this context in which different technologies are applied to build the overall system. Moreover, these changing scenarios require services located at different places during the system runtime. Thus a support for adaptability is needed. Timing and precision requirements play an important role in such scenarios. Besides, QoS management must provide the necessary support to offer the flexibility demanded in such scenarios. In this paper we present the real-time perspective of a middleware that aims at providing the support required by sophisticated heterogeneous sensor network applications. We propose to address the real-time concerns by using the OMG Data Distribution Service for Real-time Systems approach, but with a more flexible approach that fits in the heterogeneous environment in which the proposed middleware is intended to be used. We also present a coordination protocol to support the proposed approach. ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Supported by KK Foundation.