A Hierarchical Approach for Energy-Aware Distributed Embedded Intelligent Video Surveillance

Maier, Arnold; Rinner, Bernhard; Schwabach, Helmut

doi:10.1109/icpads.2005.26

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…The current implementation mainly focuses in the implementation of the multicriterion optimizer and the dynamic service manager for power-aware reconfiguration of both the DSPs and host processor. The DPM of the DSPs is based on the generic implementation presented in [7]. On the host processor, DPM is implemented by a Linux-driver that is coupled with the operating system's scheduler and implements frequency scaling and other low-power features on the PXA255.…”

Section: Methodsmentioning

confidence: 99%

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Online multi-criterion optimization for dynamic power-aware camera configuration in distributed embedded surveillance clusters

Maier

Rinner

Schriebl

et al. 2006

20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06)

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Intelligent video surveillance (IVS) systems are based on the recent development of so called embedded smart cameras. Delivering a good service quality in IVS usually results in a higher level of computing activity and therefore in increased power consumption.This work presents PoQoS, a novel approach that aims in maximizing the service quality (i.e., the number of IVSservices and their QoS) while minimizing the system's power consumption. PoQoS enables power-aware reconfiguration of services and hardware resources in distributed logical clusters of embedded smart cameras. In order to find optimal camera configurations during operation, Po-QoS integrates PoSeGA, an online genetic multi-criterion optimization algorithm. A configuration manager properly selects among optimized camera configurations and consequently initializes intra-camera or intra-cluster poweraware reconfiguration with respect to application-and situation-specific context.The evaluation of PoQoS on the PoQoCam, a powerefficient embedded smart camera platform, shows the feasibility of the presented approach.

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Section: Methodsmentioning

confidence: 99%

“…In [7], we introduced PoQoS, a hierarchical approach for QoS-driven dynamic power management in IVS systems. It focuses on the use of several pre-defined modes that are managed by a central hosting unit.…”

Section: An Improved Approach For Dynamic Power-aware Cluster Reconfimentioning

confidence: 99%

Online multi-criterion optimization for dynamic power-aware camera configuration in distributed embedded surveillance clusters

Maier

Rinner

Schriebl

et al. 2006

20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06)

Self Cite

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“…One source of triggers for these reconfigurations are alarms generated by the analysis algorithms. Another possibility for triggering a reconfiguration are events raised by internal system-level services like the load distribution service , the power management facility [Maier et al 2005], or a failure management service. as by adding crucial entries in the algorithm's resource descriptions to address all critical system resources.…”

Section: Dynamic Loading and Reconfigurationmentioning

confidence: 99%

A novel software framework for embedded multiprocessor smart cameras

Doblander¹,

Zoufal²,

Rinner

2009

ACM Trans. Embed. Comput. Syst.

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Distributed smart cameras (DSC) are an emerging technology for a broad range of important applications including smart rooms, surveillance, entertainment, tracking, and motion analysis. By having access to many views and through cooperation among the individual cameras, these DSCs have the potential to realize many more complex and challenging applications than singlecamera systems.This article focuses on the system-level software required for efficient streaming applications on single smart cameras as well as on networks of DSCs. Embedded platforms with limited resources do not provide middleware services well known on general-purpose platforms. Our software framework supports transparent intra-and interprocessor communication while keeping the memory and computation overhead very low. The software framework is based on a publisher-subscriber architecture and provides mechanisms for dynamically loading and unloading software components as well as for graceful degradation in case of software-and hardware-related faults. The software framework has been completely implemented and tested on our embedded smart cameras consisting of an ARM-based network processor and several digital signal processors. Two case studies demonstrate the feasibility of our approach.

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“…Surveillance systems have been categorized into generations and at present, Third Generation Surveillance Systems (3GSSs) 1 7 , the use of agents for prolonging the operational lifespan of visual sensor networks has as yet not been explored. And it is this that motivates this paper.…”

Section: Related Researchmentioning

confidence: 99%

Engineering Ambient Visual Sensors

O’Hare¹,

Grady²,

Jurdak³

et al. 2007

Information Sciences 2007

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Visual sensors are an indispensable prerequisite for those AmI environments that require a surveillance component. One practical issue concerns maximizing the operational longevity of such sensors as the operational lifetime of an AmI environment itself is dependent on that of its constituent components. In this paper, the intelligent agent paradigm is considered as a basis for managing a camera collective such that the conflicting demands of power usage optimization and system performance are reconciled.

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A Hierarchical Approach for Energy-Aware Distributed Embedded Intelligent Video Surveillance

Cited by 6 publications

References 6 publications

Online multi-criterion optimization for dynamic power-aware camera configuration in distributed embedded surveillance clusters

Online multi-criterion optimization for dynamic power-aware camera configuration in distributed embedded surveillance clusters

A novel software framework for embedded multiprocessor smart cameras

Engineering Ambient Visual Sensors

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