@inbook {12536,
	title = {Knowledge Extraction from Surveillance Sensors},
	booktitle = {Wiley Handbook of Science and Technology for Homeland SecurityWiley Handbook of Science and Technology for Homeland Security},
	year = {2009},
	month = {2009///},
	publisher = {John Wiley \& Sons, Inc.},
	organization = {John Wiley \& Sons, Inc.},
	keywords = {multi-camera tracking, multi-modal fusion, recognition, sensor networks, Surveillance},
	isbn = {9780470087923},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/9780470087923.hhs510/abstract;jsessionid=D0D752EF5D04327BE003BDFBD2F96134.d01t03},
	author = {Chellapa, Rama and Veeraraghavan,Ashok and Sankaranarayanan,Aswin C.}
}
@conference {13385,
	title = {Minimizing Communication Cost in Distributed Multi-query Processing},
	booktitle = {IEEE 25th International Conference on Data Engineering, 2009. ICDE {\textquoteright}09},
	year = {2009},
	month = {2009/04/29/March},
	pages = {772 - 783},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Increasing prevalence of large-scale distributed monitoring and computing environments such as sensor networks, scientific federations, Grids etc., has led to a renewed interest in the area of distributed query processing and optimization. In this paper we address a general, distributed multi-query processing problem motivated by the need to minimize the communication cost in these environments. Specifically we address the problem of optimally sharing data movement across the communication edges in a distributed communication network given a set of overlapping queries and query plans for them (specifying the operations to be executed). Most of the problem variations of our general problem can be shown to be NP-Hard by a reduction from the Steiner tree problem. However, we show that the problem can be solved optimally if the communication network is a tree, and present a novel algorithm for finding an optimal data movement plan. For general communication networks, we present efficient approximation algorithms for several variations of the problem. Finally, we present an experimental study over synthetic datasets showing both the need for exploiting the sharing of data movement and the effectiveness of our algorithms at finding such plans.},
	keywords = {Approximation algorithms, Communication networks, Computer science, Cost function, Data engineering, distributed communication network, distributed databases, distributed multi-query processing, grid computing, Large-scale systems, NP-hard, optimisation, Polynomials, Publish-subscribe, publish-subscribe systems, Query optimization, Query processing, sensor networks, Steiner tree problem, Tree graphs, trees (mathematics)},
	isbn = {978-1-4244-3422-0},
	doi = {10.1109/ICDE.2009.85},
	author = {Li,Jian and Deshpande, Amol and Khuller, Samir}
}
@conference {16506,
	title = {Capturing Approximated Data Delivery Tradeoffs},
	booktitle = {Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on},
	year = {2008},
	month = {2008/04//},
	pages = {1471 - 1473},
	abstract = {This paper presents a middleware data delivery setting with a proxy that is required to maximize the completeness of captured updates, specified in its clients{\textquoteright} profiles, while minimizing at the same time the delay in delivering the updates to clients. The two objectives may conflict when the monitoring budget is limited. Therefore, any solution should consider this tradeoff in satisfying both objectives. We term this problem the "proxy dilemma" and formalize it as a biobjective optimization problem. Such problem occurs in many contemporary applications, such as mobile and sensor networks, and poses scalability challenges in delivering up-to-date data from remote resources to meet client specifications. We present a Pareto set as a formal solution to the proxy dilemma. We discuss the complexity of generating a Pareto set for the proxy dilemma and suggest an approximation scheme to this problem.},
	keywords = {approximation scheme, approximation theory, biobjective optimization problem, Middleware, middleware data delivery tradeoffs, mobile networks, Pareto optimisation, Pareto set, proxy dilemma problem, sensor networks},
	doi = {10.1109/ICDE.2008.4497593},
	author = {Roitman,H. and Gal,A. and Raschid, Louiqa}
}
@article {12241,
	title = {A scalable key management and clustering scheme for wireless ad hoc and sensor networks},
	journal = {Future Generation Computer Systems},
	volume = {24},
	year = {2008},
	month = {2008/10//},
	pages = {860 - 869},
	abstract = {This paper describes a scalable key management and clustering scheme for secure group communications in ad hoc and sensor networks. The scalability problem is solved by partitioning the communicating devices into subgroups, with a leader in each subgroup, and further organizing the subgroups into hierarchies. Each level of the hierarchy is called a tier or layer. Key generation, distribution, and actual data transmissions follow the hierarchy. The distributed, efficient clustering approach (DECA) provides robust clustering to form subgroups, and analytical and simulation results demonstrate that DECA is energy-efficient and resilient against node mobility. Comparing with most other schemes, our approach is extremely scalable and efficient, provides more security guarantees, and is selective, adaptive and robust.},
	keywords = {ad hoc networks, clustering, Group communications, Key management, sensor networks},
	isbn = {0167-739X},
	doi = {10.1016/j.future.2008.03.007},
	url = {http://www.sciencedirect.com/science/article/pii/S0167739X08000782},
	author = {Li,Jason H. and Bhattacharjee, Bobby and Yu,Miao and Levy,Renato}
}
@article {13361,
	title = {Data Management in the Worldwide Sensor Web},
	journal = {IEEE Pervasive Computing},
	volume = {6},
	year = {2007},
	month = {2007///},
	pages = {30 - 40},
	abstract = {Advances in hardware and miniaturization technologies have led to a rapid increase in the number of large-scale sensor network deployments around the world, bringing us closer to the vision of a worldwide sensor web. Exploiting the sensor web to its full potential, however, raises several hard data management challenges. Addressing these challenges requires a concerted multidisciplinary effort encompassing many computer science fields. This article outlines some of the key data management challenges of a worldwide sensor web. It also presents recent advances in data management research that aim to address these challenges. Hopefully, the scientific, ubiquitous computing, and sensor network communities will adopt some of these solutions for managing their data. The article also attempts to bring many of the remaining open issues to the attention of the database community. This article is part of a special issue on Building a Sensor-Rich World.},
	keywords = {data modeling, data streams, data uncertainty, distributed systems, interoperability, sensor networks},
	isbn = {1536-1268},
	author = {Balazinska,Magdalena and Deshpande, Amol and Franklin,Michael J. and Gibbons,Phillip B. and Gray,Jim and Hansen,Mark and Liebhold,Michael and Nath,Suman and Szalay,Alexander and Tao,Vincent}
}
@conference {13382,
	title = {MauveDB: supporting model-based user views in database systems},
	booktitle = {Proceedings of the 2006 ACM SIGMOD international conference on Management of data},
	series = {SIGMOD {\textquoteright}06},
	year = {2006},
	month = {2006///},
	pages = {73 - 84},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Real-world data --- especially when generated by distributed measurement infrastructures such as sensor networks --- tends to be incomplete, imprecise, and erroneous, making it impossible to present it to users or feed it directly into applications. The traditional approach to dealing with this problem is to first process the data using statistical or probabilistic models that can provide more robust interpretations of the data. Current database systems, however, do not provide adequate support for applying models to such data, especially when those models need to be frequently updated as new data arrives in the system. Hence, most scientists and engineers who depend on models for managing their data do not use database systems for archival or querying at all; at best, databases serve as a persistent raw data store.In this paper we define a new abstraction called model-based views and present the architecture of MauveDB, the system we are building to support such views. Just as traditional database views provide logical data independence, model-based views provide independence from the details of the underlying data generating mechanism and hide the irregularities of the data by using models to present a consistent view to the users. MauveDB supports a declarative language for defining model-based views, allows declarative querying over such views using SQL, and supports several different materialization strategies and techniques to efficiently maintain them in the face of frequent updates. We have implemented a prototype system that currently supports views based on regression and interpolation, using the Apache Derby open source DBMS, and we present results that show the utility and performance benefits that can be obtained by supporting several different types of model-based views in a database system.},
	keywords = {Query processing, regression, sensor networks, statistical models, uncertain data, views},
	isbn = {1-59593-434-0},
	doi = {10.1145/1142473.1142483},
	url = {http://doi.acm.org/10.1145/1142473.1142483},
	author = {Deshpande, Amol and Madden,Samuel}
}
@article {16794,
	title = {Processing approximate aggregate queries in wireless sensor networks},
	journal = {Information Systems},
	volume = {31},
	year = {2006},
	month = {2006/12//},
	pages = {770 - 792},
	abstract = {In-network data aggregation has been recently proposed as an effective means to reduce the number of messages exchanged in wireless sensor networks. Nodes of the network form an aggregation tree, in which parent nodes aggregate the values received from their children and propagate the result to their own parents. However, this schema provides little flexibility for the end-user to control the operation of the nodes in a data sensitive manner. For large sensor networks with severe energy constraints, the reduction (in the number of messages exchanged) obtained through the aggregation tree might not be sufficient. In this paper, we present new algorithms for obtaining approximate aggregate statistics from large sensor networks. The user specifies the maximum error that he is willing to tolerate and, in turn, our algorithms program the nodes in a way that seeks to minimize the number of messages exchanged in the network, while always guaranteeing that the produced estimate lies within the specified error from the exact answer. A key ingredient to our framework is the notion of the residual mode of operation that is used to eliminate messages from sibling nodes when their cumulative change to the computed aggregate is small. We introduce two new algorithms, based on potential gains, which adaptively redistribute the error thresholds to those nodes that benefit the most and try to minimize the total number of transmitted messages in the network. Our techniques significantly reduce the number of messages, often by a factor of 10 for a modest 2\% relative error bound, and consistently outperform previous techniques for computing approximate aggregates, which we have adapted for sensor networks.},
	keywords = {Aggregate queries, approximation, sensor networks},
	isbn = {0306-4379},
	doi = {16/j.is.2005.02.001},
	url = {http://www.sciencedirect.com/science/article/pii/S0306437905000177},
	author = {Deligiannakis,Antonios and Kotidis,Yannis and Roussopoulos, Nick}
}
@conference {11979,
	title = {A sensory grammar for inferring behaviors in sensor networks},
	booktitle = {Proceedings of the 5th international conference on Information processing in sensor networks},
	series = {IPSN {\textquoteright}06},
	year = {2006},
	month = {2006///},
	pages = {251 - 259},
	publisher = {ACM},
	organization = {ACM},
	address = {Nashville, Tennessee, USA},
	abstract = {The ability of a sensor network to parse out observable activities into a set of distinguishable actions is a powerful feature that can potentially enable many applications of sensor networks to everyday life situations. In this paper we introduce a framework that uses a hierarchy of Probabilistic Context Free Grammars (PCFGs) to perform such parsing. The power of the framework comes from the hierarchical organization of grammars that allows the use of simple local sensor measurements for reasoning about more macroscopic behaviors. Our presentation describes how to use a set of phonemes to construct grammars and how to achieve distributed operation using a messaging model. The proposed framework is flexible. It can be mapped to a network hierarchy or can be applied sequentially and across the network to infer behaviors as they unfold in space and time. We demonstrate this functionality by inferring simple motion patterns using a sequence of simple direction vectors obtained from our camera sensor network testbed.},
	keywords = {algorithms, behavior identification, human activity, human factors, pcfg, real-time and embedded systems, sensor grammars, sensor networks},
	isbn = {1-59593-334-4},
	doi = {10.1145/1127777.1127817},
	author = {Lymberopoulos, Dimitrios and Ogale, Abhijit S. and Savvides, Andreas and Aloimonos, J.}
}
@conference {19046,
	title = {The sybil attack in sensor networks: analysis \& defenses},
	series = {IPSN {\textquoteright}04},
	year = {2004},
	month = {2004},
	pages = {259 - 268},
	publisher = {ACM},
	organization = {ACM},
	abstract = {Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack [6], where a node illegitimately claims multiple identities. This paper systematically analyzes the threat posed by the Sybil attack to wireless sensor networks. We demonstrate that the attack can be exceedingly detrimental to many important functions of the sensor network such as routing, resource allocation, misbehavior detection, etc. We establish a classification of different types of the Sybil attack, which enables us to better understand the threats posed by each type, and better design countermeasures against each type. We then propose several novel techniques to defend against the Sybil attack, and analyze their effectiveness quantitatively.},
	keywords = {Security, sensor networks, sybil attack},
	isbn = {1-58113-846-6},
	url = {http://doi.acm.org/10.1145/984622.984660},
	author = {Newsome, James and Elaine Shi and Song, Dawn and Perrig, Adrian}
}
