Vasanth Rajamani

Semantic self-assessment of query results in dynamic environments

Queries are convenient abstractions for the discovery of information and services, as they offer content-based information access. In distributed settings, query semantics are well-defined, for example, queries are often designed to satisfy ACID transactional properties. When query processing is introduced in a dynamic network setting, achieving transactional semantics becomes complex due to the open and unpredictable environment. In this article, we propose a query processing model for mobile ad hoc and sensor networks that is suitable for expressing a wide range of query semantics; the semantics differ in the degree of consistency with which query results reflect the state of the environment during query execution. We introduce several distinct notions of consistency and formally express them in our model. A practical and significant contribution of this article is a protocol for query processing that automatically assesses and adaptively provides an achievable degree of consistency given the operational environment throughout its execution. The protocol attaches an assessment of the achieved guarantee to returned query results, allowing precise reasoning about a query with a range of possible semantics. We evaluate the performance of this protocol and demonstrate the benefits accrued to applications through examples drawn from an industrial application.

Inquiry and Introspection for Non-deterministic Queries in Mobile Networks

This paper focuses on the information gathering support needs for enterprises that operate over wireless mobile ad hoc networks. While queries are a convenient way to obtain information, the highly dynamic nature of such networks makes it difficult to ensure a precise match between the results returned by a query and the actual state of the enterprise. However, decisions can be made based on the perceived quality of the information retrieved; specialized query support is needed to control and assess the accuracy of the query results. In this paper, we introduce the notion of inquiry mode to allow the user to exercise control over the query processing policy so as to match the level of accuracy to the requirements of the task. In addition, we describe the use of query introspection, a process for assessing the fitness of a particular inquiry mode. Both concepts are formalized, illustrated, and evaluated.

Supporting multi-fidelity-aware concurrent applications in dynamic sensor networks

Most existing research in wireless sensor networks focuses on optimally running a single application on top of a tailor-made and deployed network. However, as sensors become an integral part of our environments, we posit that sensor networks will be increasingly viewed as platforms that will be used to run several user applications simultaneously. Concurrently executing applications requires the networks resources to be shared across applications so as to make the best long-term utilization of the constrained devices and communications network. This resource sharing entails tradeoffs in the fidelity offered to individual applications. Fidelity is an application-dependent concept that can denote a variety of operational measures including communication latency, data quality, and redundancy. In this paper, we present a principled way to define the fidelity associated with an application given a particular allocation of the available resources. Given a desired set of applications to deploy, we also explore the impact of sharing resources among the applications in terms of fidelity degradation to individual applications. To this end, we provide an algorithm that determines the optimal subset of applications to deploy given the available resources and the potential impact on fidelity and evaluate it.

Blurring snapshots: Temporal inference of missing and uncertain data

Many pervasive computing applications continuously monitor state changes in the environment by acquiring, interpreting and responding to information from sensors embedded in the environment. However, it is extremely difficult and expensive to obtain a continuous, complete, and consistent picture of a continuously evolving operating environment. One standard technique to mitigate this problem is to employ mathematical models that compute missing data from sampled observations thereby approximating a continuous and complete stream of information. However, existing models have traditionally not incorporated a notion of temporal validity, or the quantification of imprecision associated with inferring data values from past or future observations. In this paper, we support continuous monitoring of dynamic pervasive computing phenomena through the use of a series of snapshot queries. We define a decay function and a set of inference approaches to filling in missing and uncertain data in this continuous query.We evaluate the usefulness of this abstraction in its application to complex spatio-temporal pattern queries in pervasive computing networks.

An interrelational grouping abstraction for heterogeneous sensors

In wireless sensor network applications, the potential to use cooperation to resolve user queries remains largely untapped. Efficiently answering a users questions requires identifying the correct set of nodes that can answer the question and enabling coordination between them. In this article, we propose a query domain abstraction that allows an application to dynamically specify the nodes best suited to answering a particular query. Selecting the ideal set of heterogeneous sensors entails answering two fundamental questions—how are the selected sensors related to one another, and where should the resulting sensor coalition be located. We introduce two abstractions, the proximity function and the reference function, to precisely specify each of these concerns within a query. All nodes in the query domain must satisfy any provided proximity function, a user-defined function that constrains the relative relationship among the group of nodes (e.g., based on a property of the network or physical environment or on logical properties of the nodes). The selected set of nodes must also satisfy any provided reference function, a mechanism to scope the location of the query domain to a specified area of interest (e.g., within a certain distance from a specified reference point). In this article, we model these abstractions and present a set of protocols that accomplish this task with varying degrees of correctness. We evaluate their performance through simulation and highlight the tradeoffs between protocol overhead and correctness.

Fast track article: Using snapshot query fidelity to adapt continuous query execution

This paper explores the fidelity of queries issued in pervasive computing networks. A querys fidelity, or how well its results reflect the state of the environment, can be significantly impacted by dynamics that occur during its distributed execution. We focus on continuous queries that can be built out of sequences of consecutive snapshot queries and show how the fidelity of snapshots can be used to determine the fidelity of continuous queries. This simple notion of continuous query fidelity can be used to adapt query processing to impact quality and cost tradeoffs given the current state of the environment.

Fidelity-based continuous query introspection and adaptation

In this paper, we address the fidelity of information collected from distributed, interactive, pervasive computing environments. Queries in these dynamic networks come in two forms: snapshot queries and continuous queries. The former executes through the network and returns values that satisfy the query criteria at a particular instant in time. The latter expects a result that is updated over time to reflect changes in the system. The fidelity, or quality, of the results of these queries can be significantly impacted by the unpredictability of the dynamic network; as the query is distributed and executed, changes that occur due to network and environmental dynamics can cause the query to miss potential results or to report inconsistent information. Our previous work has shown how we can provide semantically meaningful statements about the fidelity, or quality, of the result of a snapshot query in a dynamic networked environment. In this paper, we demonstrate how this fidelity can also be used to adapt a continuous querys processing to make its execution best match the conditions in the underlying dynamic environment.

Automated Assessment of Aggregate Query Imprecision in Dynamic Environments

Queries are widely used for acquiring data distributed in opportunistically formed mobile networks. However, when queries are executed in such dynamic settings, the returned result may not be consistent, i.e., it may not accurately reflect the state of the environment. It can thus be difficult to reason about the meaning of a querys result. Reasoning about imperfections in the result becomes even more complex when in-network aggregation is employed, since only a single aggregate value is returned. We define the semantics of aggregate queries in terms of a qualitative description of consistency and a quantitative measure of imprecision. We provide a protocol that performs in-network aggregation while simultaneously generating quality assessments for the query result. The protocol enables intuitive interpretations of the semantics associated with an aggregate querys execution in a dynamic environment.