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Achieving Scalability for Task Scheduling in a Large Camera Network



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Achieving Scalability for Task Scheduling in a Large Camera Network Submission No 1568988865 ABSTRACT dow of opportunities The time taken for Camera networks are increasingly being planning and constructing these video ac deployed for security In most of these quisitions and scheduling cameras poses camera networks video sequences are cap significant scalability challenges for large tured transmitted and archived continu camera networks We present a scalable ously from all cameras creating enormous algorithm that constructs schedules in which stress on available transmission bandwidth multiple tasks can be satisfied simultane storage space and computing facilities We ously by a given camera This is accom describe intelligent control system for schedul plished using a plane sweep algorithm that ing Pan Tilt Zoom cameras to capture video reduces an otherwise exponential problem only when task specific requirements can to polynomial time Additional scalability be satisfied These videos are collected in issues arise when these constructed time real time during predicted temporal win intervals are used to schedule the cameras We describe two scheduling algorithms Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page To copy otherwise to republish to post on servers or to redistribute to lists requires prior specific permission and or a fee ACM Multimedia 06 Santa Barbara CA USA Copyright 200X ACM X XXXXX XX X XX XX 5 00 a greedy algorithm and another based on Dynamic Programming DP We analyze their approximation factors and present sim that include security traffic monitoring etc ulations that show that the DP method is These systems typically consist of a large advantageous for large camera networks number of cameras which can either be in terms of



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