@article {18159,
	title = {A Scalable Multiuser Framework for Video Over OFDM Networks: Fairness and Efficiency},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {16},
	year = {2006},
	month = {2006/10//},
	pages = {1217 - 1231},
	abstract = {In this paper, we propose a framework to transmit multiple scalable video programs over downlink multiuser orthogonal frequency division multiplex (OFDM) networks in real time. The framework explores the scalability of the video codec and multidimensional diversity of multiuser OFDM systems to achieve the optimal service objectives subject to constraints on delay and limited system resources. We consider two essential service objectives, namely, the fairness and efficiency. Fairness concerns the video quality deviation among users who subscribe the same quality of service, and efficiency relates to how to attain the highest overall video quality using the available system resources. We formulate the fairness problem as minimizing the maximal end-to-end distortion received among all users and the efficiency problem as minimizing total end-to-end distortion of all users. Fast suboptimal algorithms are proposed to solve the above two optimization problems. The simulation results demonstrated that the proposed fairness algorithm outperforms a time division multiple (TDM) algorithm by 0.5 3 dB in terms of the worst received video quality among all users. In addition, the proposed framework can achieve a desired tradeoff between fairness and efficiency. For achieving the same average video quality among all users, the proposed framework can provide fairer video quality with 1 1.8 dB lower PSNR deviation than a TDM algorithm},
	keywords = {algorithm;video, codec;video, coding;video, communication;, deviation;downlink, deviation;OFDM, distortion;multidimensional, diversity;multiple, division, end-to-end, framework;time, Frequency, modulation;diversity, multiple, multiplex, multiuser, network;efficiency, networks;video, objectives;optimization, of, OFDM, orthogonal, over, problem;fairness, problem;maximal, problems;quality, programs;multiuser, PSNR, QUALITY, reception;image, resolution;optimisation;quality, scalable, service, service;scalable, service;video, systems;optimal, video},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2006.883513},
	author = {Su,Guan-Ming and Han,Zhu and M. Wu and Liu,K. J.R}
}
@conference {13245,
	title = {Scalable image-based multi-camera visual surveillance system},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {205 - 212},
	abstract = {We describe the design of a scalable and wide coverage visual surveillance system. Scalability (the ability to add and remove cameras easily during system operation with minimal overhead and system degradation) is achieved by utilizing only image-based information for camera control. We show that when a pan-tilt-zoom camera pans and tilts, a given image point moves in a circular and a linear trajectory, respectively. We create a scene model using a plan view of the scene. The scene model makes it easy for us to handle occlusion prediction and schedule video acquisition tasks subject to visibility constraints. We describe a maximum weight matching algorithm to assign cameras to tasks that meet the visibility constraints. The system is illustrated both through simulations and real video from a 6-camera configuration.},
	keywords = {ACQUISITION, algorithm;, camera;, constraints;, feature, hidden, image-based, MATCHING, maximum, multi-camera, occlusion, pan-tilt-zoom, PLAN, prediction;, processing;, removal;, scalable, scheduling;, signal, Surveillance, surveillance;, system;, task, video, view;, visibility, visual, weight},
	doi = {10.1109/AVSS.2003.1217923},
	author = {Lim,Ser-Nam and Davis, Larry S. and Elgammal,A.}
}
@conference {18182,
	title = {Communication-friendly encryption of multimedia},
	booktitle = {Multimedia Signal Processing, 2002 IEEE Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {292 - 295},
	abstract = {This paper discusses encryption operations that selectively encrypt content-carrying segments of multimedia data stream. We propose and analyze three techniques that work in different domains, namely, a syntax-aware selective bitstream encryption tool with bit stuffing, a generalized index mapping encryption tool with controlled overhead and an intra-bitplane encryption tool compatible with fine granularity scalable coding. The designs of these proposed encryption operations take into consideration the inherent structure and syntax of multimedia sources and have improved friendliness to communications, compression and computation.},
	keywords = {bit, bitstream, coding;, Communication, communication;, compression, compression;, COMPUTATION, controlled, cryptography;, data, encryption, encryption;, fine, friendliness;, granularity, image, index, intrabitplane, MAPPING, multimedia, operation;, overhead;, scalable, selective, sources, stream;, stuffing;, syntax-aware, syntax;, tool;},
	doi = {10.1109/MMSP.2002.1203303},
	author = {M. Wu and Mao,Yinian}
}
@article {11913,
	title = {Rover: scalable location-aware computing},
	journal = {Computer},
	volume = {35},
	year = {2002},
	month = {2002/10//},
	pages = {46 - 53},
	abstract = {All the components necessary for realizing location-aware computing are available in the marketplace today. What has hindered the widespread deployment of location-based systems is the lack of an integration architecture that scales with user populations. The authors have completed the initial implementation of Rover, a system designed to achieve this sort of integration and to automatically tailor information and services to a mobile user{\textquoteright}s location. Their studies have validated Rover{\textquoteright}s underlying software architecture, which achieves system scalability through high-resolution, application-specific resource scheduling at the servers and network. The authors believe that this technology will greatly enhance the user experience in many places, including museums, amusement and theme parks, shopping malls, game fields, offices, and business centers. They designed the system specifically to scale to large user populations and expect its benefits to increase with them.},
	keywords = {amusement, application-specific, architecture;, automation;, business, business;, computing;, data, entertainment;, handheld, humanities;, integration, LAN;, location-aware, malls;, mobile, museums;, office, parks;, processing;, resource, Rover;, scalability;, scalable, scheduling;, shopping, software, system, theme, units;, user;, wireless},
	isbn = {0018-9162},
	doi = {10.1109/MC.2002.1039517},
	author = {Banerjee,S. and Agarwal,S. and Kamel,K. and Kochut, A. and Kommareddy,C. and Nadeem,T. and Thakkar,P. and Trinh,Bao and Youssef,A. and Youssef, M. and Larsen,R.L. and Udaya Shankar,A. and Agrawala, Ashok K.}
}
@conference {12306,
	title = {Scalable peer finding on the Internet},
	booktitle = {Global Telecommunications Conference, 2002. GLOBECOM {\textquoteright}02. IEEE},
	volume = {3},
	year = {2002},
	month = {2002/11//},
	pages = {2205 - 2209 vol.3 - 2205 - 2209 vol.3},
	abstract = {We consider the problem of finding nearby application peers over the Internet. We define a new peer-finding scheme (called Tiers) that scales to large application peer groups. Tiers creates a hierarchy of the peers, which allows an efficient and scalable solution to this problem. The scheme can be implemented entirely in the application-layer and does not require the deployment of either any additional measurement services, or well-known reference landmarks in the network. We present detailed evaluation of Tiers and compare it to one previously proposed scheme called Beaconing. Through analysis and detailed simulations on 10,000 node Internet-like topologies we show that Tiers achieves comparable or better performance with a significant reduction in control overheads for groups of size 32 or more.},
	keywords = {application, application-layer;, Beaconing;, CONTROL, finding;, Internet-like, Internet;, measurement, network, overhead, peer, peer-finding, peers;, protocol;, protocols;, reduction;, scalable, scheme;, services;, simulations;, solution;, Tiers;, topologies;, topology;},
	doi = {10.1109/GLOCOM.2002.1189023},
	author = {Banerjee,S. and Kommareddy,C. and Bhattacharjee, Bobby}
}
@article {12307,
	title = {Scalable secure group communication over IP multicast},
	journal = {Selected Areas in Communications, IEEE Journal on},
	volume = {20},
	year = {2002},
	month = {2002/10//},
	pages = {1511 - 1527},
	abstract = {We introduce and analyze a scalable rekeying scheme for implementing secure group communications Internet protocol multicast. We show that our scheme incurs constant processing, message, and storage overhead for a rekey operation when a single member joins or leaves the group, and logarithmic overhead for bulk simultaneous changes to the group membership. These bounds hold even when group dynamics are not known a priori. Our rekeying algorithm requires a particular clustering of the members of the secure multicast group. We describe a protocol to achieve such clustering and show that it is feasible to efficiently cluster members over realistic Internet-like topologies. We evaluate the overhead of our own rekeying scheme and also of previously published schemes via simulation over an Internet topology map containing over 280 000 routers. Through analysis and detailed simulations, we show that this rekeying scheme performs better than previous schemes for a single change to group membership. Further, for bulk group changes, our algorithm outperforms all previously known schemes by several orders of magnitude in terms of actual bandwidth usage, processing costs, and storage requirements.},
	keywords = {access, algorithm;, authentication;, Bandwidth, communication;, CONTROL, costs;, cryptography;, dynamics;, group, group;, Internet, Internet-like, Internet;, IP, logarithmic, map;, membership;, message, Multicast, multicast;, network, overhead;, PROCESSING, protocol, protocols;, rekeying, requirements;, routers;, routing;, scalable, secure, security;, server;, simulation;, storage, Telecommunication, topologies;, Topology, topology;, transport, usage;},
	isbn = {0733-8716},
	doi = {10.1109/JSAC.2002.803986},
	author = {Banerjee,S. and Bhattacharjee, Bobby}
}
@conference {14955,
	title = {Efficient Algorithms for Atmospheric Correction of Remotely Sensed Data},
	booktitle = {Supercomputing, 1995. Proceedings of the IEEE/ACM SC95 Conference},
	year = {1995},
	month = {1995///},
	pages = {12 - 12},
	abstract = {Remotely sensed imagery has been used for developing and validating various studies regarding land cover dynamics. However, the large amounts of imagery collected by the satellites are largely contaminated by the effects of atmospheric particles. The objective of atmospheric correction is to retrieve the surface reflectance from remotely sensed imagery by removing the atmospheric effects. We introduce a number of computational techniques that lead to a substantial speedup of an atmospheric correction algorithm based on using look-up tables. Excluding I/O time, the previous known implementation processes one pixel at a time and requires about 2.63 seconds per pixel on a SPARC-10 machine, while our implementation is based on processing the whole image and takes about 4-20 microseconds per pixel on the same machine. We also develop a parallel version of our algorithm that is scalable in terms of both computation and I/O. Experimental results obtained show that a Thematic Mapper (TM) image (36 MB per band, 5 bands need to be corrected) can be handled in less than 4.3 minutes on a 32-node CM-5 machine, including I/O time.},
	keywords = {Atmospheric, AVHRR;, computing;, correction;, high, I/O;, Parallel, performance, processing;, remote, scalable, sensing;, TM;},
	doi = {10.1109/SUPERC.1995.242453},
	author = {Fallah-Adl,H. and JaJa, Joseph F. and Liang,Shunlin and Kaufman,Y.J. and Townshend,J.}
}
@article {15022,
	title = {Scalable data parallel algorithms for texture synthesis using Gibbs random fields},
	journal = {Image Processing, IEEE Transactions on},
	volume = {4},
	year = {1995},
	month = {1995/10//},
	pages = {1456 - 1460},
	abstract = {This article introduces scalable data parallel algorithms for image processing. Focusing on Gibbs and Markov random field model representation for textures, we present parallel algorithms for texture synthesis, compression, and maximum likelihood parameter estimation, currently implemented on Thinking Machines CM-2 and CM-5. The use of fine-grained, data parallel processing techniques yields real-time algorithms for texture synthesis and compression that are substantially faster than the previously known sequential implementations. Although current implementations are on Connection Machines, the methodology presented enables machine-independent scalable algorithms for a number of problems in image processing and analysis},
	keywords = {algorithms;maximum, algorithms;parallel, algorithms;scalable, algorithms;texture, analysis;image, CM-2;Thinking, CM-5;fine-grained, compression;image, compression;texture, Connection, data, estimation;model, estimation;parallel, field;Thinking, fields;Markov, likelihood, machine, Machines;Gibbs, machines;random, Parallel, parameter, processes;, processes;data, processing;image, processing;machine-independent, random, representation;real-time, scalable, synthesis;Markov, texture;maximum},
	isbn = {1057-7149},
	doi = {10.1109/83.465111},
	author = {Bader, D.A. and JaJa, Joseph F. and Chellapa, Rama}
}
