We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.

This paper proposes the use of repetitive broadcast as a way of augmenting the memory hierarchy of clients in an asymmetric communication environment. We describe a new technique called \Broadcast Disks" for structuring the broadcast in a way that provides improved performance for non-uniformly accessed data. The Broadcast Disk superimposes multiple disks spinning at di erent speeds on a single broadcast channel | in e ect creating an arbitrarily ne-grained memory hierarchy. In addition to proposing and de ning the mechanism, a main result of this work is that exploiting the potential of the broadcast structure requires a re-evaluation of basic cache management policies. We examine several \pure" cache management policies and develop and measure implementable approximations to these policies. These results and others are presented in a set of simulation studies that substantiates the basic idea and develops some of the intuitions required to design a particular broadcast program.

We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.

XML filtering systems aim to provide fast, on-the-fly matching of XML-encoded data to large numbers of query specifications containing constraints on both structure and content. It is now well accepted that approaches using event-based parsing and Finite State Machines (FSMs) can provide the basis for highly scalable structure-oriented XML filtering systems. The XFilter system [Altinel and Franklin 2000] was the first published FSM-based XML filtering approach. XFilter used a separate FSM per path query and a novel indexing mechanism to allow all of the FSMs to be executed simultaneously during the processing of a document. Building on the insights of the XFilter work, we describe a new method, called "YFilter" that combines all of the path queries into a single Nondeterministic Finite Automaton (NFA). YFilter exploits commonality among queries by merging common prefixes of the query paths such that they are processed at most once. The resulting shared processing provides tremendous improvements in structure matching performance but complicates the handling of value-based predicates.In this paper we first describe the XFilter and YFilter approaches and present results of a detailed performance comparison of structure matching for these algorithms as well as a hybrid approach. The results show that the path sharing employed by YFilter can provide order-of-magnitude performance benefits. We then propose two alternative techniques for extending YFilter's shared structure matching with support for valuebased predicates, and compare the performance of these two techniques. The results of this latter study demonstrate some key differences between shared XML filtering and traditional database query processing. Finally, we describe how the YFilter approach is extended to handle more complicated queries containing nested path expressions.

OBJECTIVE:To evaluate primary care and specialist physicians' satisfaction with interphysician communication and to identify the major problems in the current referral process. DESIGN:Surveys were mailed to providers to determine satisfaction with the referral process; then patient-specific surveys were e-mailed to this group to obtain real-time referral information. SETTING: Academic tertiary care medical center.PARTICIPANTS: Attending-level primary care physicians (PCPs) and specialists. MEASUREMENTS AND MAIN RESULTS:The response rate for mail surveys for PCPs was 57% and for specialists was 51%. In the mail survey, 63% of PCPs and 35% of specialists were dissatisfied with the current referral process. Respondents felt that major problems with the current referral system were lack of timeliness of information and inadequate referral letter content. Information considered important by recipient groups was often not included in letters that were sent. The response rate for the referral specific e-mail surveys was 56% for PCPs and 53% for specialists. In this e-mail survey, 68% of specialists reported that they received no information from the PCP prior to specific referral visits, and 38% of these said that this information would have been helpful. In addition, four weeks after specific referral visits, 25% of PCPs had still not received any information from specialists. CONCLUSIONS:Substantial problems were present in the referral process. The major issues were physician dissatisfaction, lack of timeliness, and inadequate content of interphysician communication. Information obtained from the general survey and referral-specific survey was congruent. Efforts to improve the referral system could improve both physician satisfaction and quality of patient care. The referral process is a critical component of quality clinical care, and it has become increasingly scrutinized in the managed care era. Physician-to-physician communication is vital to the success of an outpatient referral. Optimal communication involves transfer of relevant clinical information in both directions (from the referring physician to the specialist and vice versa). Breakdowns in communication can lead to poor continuity of care, delayed diagnoses, polypharmacy, increased litigation risk, and unnecessary testing, 1 and can therefore decrease the quality of care.Difficulties with referrals are commonplace because of physician time constraints, lack of clarity about reasons for referrals, patient self-referrals, limitations imposed by managed care, and unclear follow-up plans. Several studies have shown that communication between primary care providers (PCPs) and specialists is suboptimal in many ways. In a 1983 study of inpatient consultation, 2 the requesting physician and the consultant completely disagreed on both the reason for consultation and the principal clinical issue in 14% of consultations. In one outpatient study done in 1980, PCPs only received followup information for 62% of consultations. 3 However, despite advances in medicine ...

This open source computing framework unifies streaming, batch, and interactive big data workloads to unlock new applications.

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