Adaptive Multimedia Mining on Distributed Stream Processing Systems

Abstract

We present an application for distributed semantic concept detection in multimedia streams. The streams are mined using Support Vector Machine based concept detectors (classifiers) deployed on a distributed stream processing system. We organize the classifiers into a hierarchical topology based on semantic relationships between the concepts of interest, and use the system resource manager to place the topology across a set of processing nodes. We then develop distributed game theoretic optimization strategies for dynamic adaptation of individual classifier operating characteristics in order to maximize end-to-end application utility under varying resource availability. As part of this paper, we will demonstrate the principles behind large-scale multimedia stream mining, and showcase the design, development, deployment, and distributed adaptation of such applications on a large scale cluster.A video demonstration of the system can be found at: http:// childman.bol.ucla.edu/ICDM/demovideoicdm2009.swf

Foresighted tree configuration games in resource constrained distributed stream mining sensors

“…Since action y à j (orŷ j ) instead of x à j (orx j ) incurs higher costs for c j (or c j ), the condition in (22) can be expressed as…”

“…We demonstrate that the foresighted strategy outperforms the myopic strategy, and also show that the foresighted strategies lead to utility that approaches the centralized optimal solution, as the coalition size and the number of actions increase. An actual implementation of the proposed myopic strategy based on IBM System S processing core middleware [7] was demonstrated in [22]. This paper is organized as follows.…”

DSPBench: A Suite of Benchmark Applications for Distributed Data Stream Processing Systems

“…The main areas identified from the set of 50 resulting papers were: sensor networks, advertising, finance, telecommunication, social networks, synthetic applications, and network monitoring. The percentage of papers in our set belonging to the different areas is depicted in Figure 2 and the complete list can be found in Table 2 Area Papers Finance [25], [26], [27], [28] Network Monitoring [29], [30], [31], [32] Synthetic [33], [34], [35], [36], [37], [38] Traffic Monitoring [39], [40], [41], [42], [43] Advertising [29], [30], [15], [44], [45], [46], [47] Sensor Network [48], [49], [50], [51], [52], [53], [11], [54] Social Network [55], [56], [57], [58], [59], [60], [61], [62], [63], [18] Telecom…”