Title :
Efficient distribution of visual processing tasks in multi-camera visual sensor networks
Author :
Eriksson, Emil ; Pacifici, Valentino ; Dan, Gyorgy
Author_Institution :
Sch. of Electr. Eng., KTH R. Inst. of Technol., Stockholm, Sweden
fDate :
June 29 2015-July 3 2015
Abstract :
Multi-camera visual sensor networks (VSNs) require large computational resources in order to perform visual analysis in real-time. One way to match the computational needs is to augment the VSN with dedicated processing nodes that do in-network processing, but this requires careful allocation of loads from the sensor nodes in order to ensure low processing times. In this paper we formulate the problem of load allocation and completion time minimization in a VSN as an optimization problem. We propose a distributed algorithm for load allocation, and evaluate its performance in terms of completion time and convergence compared to a Greedy algorithm. Simulations show that the proposed algorithm converges faster, but at the cost of increased completion times. Nonetheless, combined with appropriate coordination, the proposed algorithm achieves low completion times at low complexity.
Keywords :
cameras; computational complexity; distributed algorithms; feature extraction; image sensors; minimisation; VSN; completion time minimization; computational resources; convergence; distributed algorithm; in-network processing; load allocation; low complexity; multicamera visual sensor networks; optimization problem; processing nodes; sensor nodes; visual analysis; visual feature extraction; visual processing tasks; Convergence; Distributed algorithms; Feature extraction; Minimization; Optimization; Resource management; Visualization; Distributed optimization; Divisible load theory; Sensor networks; Visual feature extraction;
Conference_Titel :
Multimedia & Expo Workshops (ICMEW), 2015 IEEE International Conference on
Conference_Location :
Turin
DOI :
10.1109/ICMEW.2015.7169817