Abstract. In-network aggregation has been proposed as one method for reducing energy consumption in sensor networks. In this paper, we explore two ideas related to further reducing energy consumption in the context of in-network aggregation. The first is by influencing the construction of the routing trees for sensor networks with the goal of reducing the size of transmitted data. To this end, we propose a group-aware network configuration method that "clusters" along the same path sensor nodes that belong to the same group. The second idea involves imposing a hierarchy of output filters on the sensor network with the goal of both reducing the size of transmitted data and minimizing the number of transmitted messages. More specifically, we propose a framework to use temporal coherency tolerances in conjunction with in-network aggregation to save energy at the sensor nodes while maintaining specified quality of data. These tolerances are based on user preferences or can be dictated by the network in cases where the network cannot support the current tolerance level. Our framework, called TiNA, works on top of existing in-network aggregation schemes. We evaluate experimentally our proposed schemes in the context of existing in-network aggregation schemes. We present experimental results measuring energy consumption, response time, and quality of data for Group-By queries. Overall, our schemes provide significant energy savings with respect to communication and a negligible drop in quality of data.

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ACTA M a comprehensive transaction framework that facilitates the formal description of properties of extended transaction models. Specifically, using ACTA, one can specify and reason about (1) the effects of transactions on objects and (2) the mteractlons between transactions. This article presents ACTA as a tool for the syntheszs of e~tended transuctzon models, one which supports the development and analysis of new extended transaction models m a systematic manner Here, this is demonstrated by derivmg new transaction definitions (1) by modifymg the specifications of exlstmg transaction models, (2) by combining the specifications of existing models, and (3) by starting from first principles To exemplify the first, new models are synthesized from atomzc tra nsactlons and JOIn transactions. To illustrate the second, we synthesize a model that combines aspects of the nested-and splzt-tra nsactzon models We demonstrate the latter by deriving the specification of an open-nested-transaction model from hwgh-level requirements.

Distributed systems are expected t o support mobile computations ezecuted over a computer network of fixed and mobile hosts. This paper examines the requirements for structuring such mobile computations that access shared data i n a database, argues that opennesting can better facilitate these requirements, and proposes an Open-Nested Transaction model i n a mobile environment using the notion of Reporting Transactions and CO-Transactions.

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Recently, a number of extensions to the tradItIonal transaction model have been proposed to support new mformatlon-mtenslve apphcatlons such as CAD/CAM and software development However, these extended models capture only a subset of mteractlons that can be found m such apphcatlons, and represent only some of the pomts within the spectrum of mteractlons possible m competltlve and cooperative environments ACTd IS a formahzable framework developed for characterlzmg the whole spectrum of mteractionsThe ACTA framework 1s not yet another transactlon model, but 1s Intended to unify the exlstmg models ACTA allows for specifying the structureand the behauzorof transactions as well as for reasonmg about the concurrency and recovery properties of the transactions In ACTA, the semantics of mteractlons are expressed m terms of transactions' effects on the commit and abort of other transactions and on obJects' state and concurrency status (1 e , synchromeatlon state) Its abhty to capture the semantics of previously proposed transaction models 1s mdlcative of its generality The reasoning capabtitles of this framework have also been tested by usmg the framework to study the properties of a new model that 1s derived by comhnmg two exlstmg transaction models

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The emergence of monitoring applications has precipitated the need for Data Stream Management Systems (DSMSs), which constantly monitor incoming data feeds (through registered continuous queries), in order to detect events of interest. In this article, we examine the problem of how to schedule multiple Continuous Queries (CQs) in a DSMS to optimize different Quality of Service (QoS) metrics. We show that, unlike traditional online systems, scheduling policies in DSMSs that optimize for average response time will be different from policies that optimize for average slowdown, which is a more appropriate metric to use in the presence of a heterogeneous workload. Towards this, we propose policies to optimize for the average-case performance for both metrics. Additionally, we propose a hybrid scheduling policy that strikes a fine balance between performance and fairness, by looking at both the average-and worst-case performance, for both metrics. We also show how our policies can be adaptive enough to handle the inherent dynamic nature of monitoring applications. Furthermore, we discuss how our policies can be efficiently implemented and extended to exploit sharing in optimized multi-query plans and multi-stream CQs. Finally, we experimentally show using real data that our policies consistently outperform currently used ones.