Detecting complex patterns in event streams, i.e., complex event processing (CEP), has become increasingly important for modern enterprises to react quickly to critical situations. In many practical cases business events are generated based on pre-defined business logics. Hence constraints, such as occurrence and order constraints, often hold among events. Reasoning using these known constraints enables us to predict the non-occurrences of certain future events, thereby helping us to identify and then terminate the long running query processes that are guaranteed to not lead to successful matches.In this work, we focus on exploiting event constraints to optimize CEP over large volumes of business transaction streams. Since the optimization opportunities arise at runtime, we develop a runtime query unsatisfiability (RunSAT) checking technique that detects optimal points for terminating query evaluation. To assure efficiency of RunSAT checking, we propose mechanisms to precompute the query failure conditions to be checked at runtime. This guarantees a constant-time RunSAT reasoning cost, making our technique highly scalable. We realize our optimal query termination strategies by augmenting the query with Event-Condition-Action rules encoding the pre-computed failure conditions. This results in an event processing solution compatible with state-of-the-art CEP architectures. Extensive experimental results demonstrate that significant performance gains are achieved, while the optimization overhead is small.

With the rapid and widespread adoption of mobile devices, mobile phones offer an opportunity to deliver cardiovascular disease (CVD) interventions. This study evaluated the efficacy of a mobile phone-based lifestyle intervention aimed at reducing the overall CVD risk at a health management center in Guangzhou, China. We recruited 589 workers from eight work units. Based on a group-randomized design, work units were randomly assigned either to receive the mobile phone-based lifestyle interventions or usual care. The reduction in 10-year CVD risk at 1-year follow-up for the intervention group was not statistically significant (–1.05%, p = 0.096). However, the mean risk increased significantly by 1.77% (p = 0.047) for the control group. The difference of the changes between treatment arms in CVD risk was –2.83% (p = 0.001). In addition, there were statistically significant changes for the intervention group relative to the controls, from baseline to year 1, in systolic blood pressure (–5.55 vs. 6.89 mmHg; p < 0.001), diastolic blood pressure (–6.61 vs. 5.62 mmHg; p < 0.001), total cholesterol (–0.36 vs. –0.10 mmol/L; p = 0.005), fasting plasma glucose (–0.31 vs. 0.02 mmol/L; p < 0.001), BMI (–0.57 vs. 0.29 kg/m2; p < 0.001), and waist hip ratio (–0.02 vs. 0.01; p < 0.001). Mobile phone-based intervention may therefore be a potential solution for reducing CVD risk in China.

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Materialized views can be maintained by submitting maintenance queries to the data sources. However, the query results may be erroneous due to concurrent source updates. State-of-the-art maintenance strategies typically apply compensations to resolve such conflicts and assume all source schemata remain stable over time. In a loosely coupled dynamic environment, the sources may autonomously change not only their data but also their schema or semantics. Consequently, either the maintenance or the compensation queries may be broken. Unlike compensation-based approaches found in the literature, we instead model the complete materialized view maintenance process as a view maintenance transaction (VM_Transaction). This way, the anomaly problem can be rephrased as the serializability of VM_Transactions. To achieve VM_Transaction serializability, we propose a multiversion concurrency control algorithm, called TxnWrap , which is shown to be the appropriate design for loosely coupled environments with autonomous data sources. TxnWrap is complementary to the maintenance algorithms proposed in the literature, since it removes concurrency issues from consideration allowing the designer to focus on the maintenance logic. We show several optimizations of TxnWrap, in particular, (1) space optimizations on versioned data materialization and (2) parallel maintenance scheduling. With these optimizations, TxnWrap even outperforms state-of-the-art view maintenance solutions in terms of refresh time. Further, several design choices of TxnWrap are studied each having its respective advantages for certain environmental settings. A correctness proof based on transaction theory for TxnWrap is also provided. Last, we have implemented TxnWrap. The experimental results confirm that TxnWrap achieves predictable performance under a varying rate of concurrency.