Conference Paper

Detection of Behavioral Contextual Properties in Asynchronous Pervasive Computing Environments.

DOI: 10.1109/ICPADS.2010.24 Conference: IEEE 16th International Conference on Parallel and Distributed Systems, ICPADS 2010, 8-10 Dec. 2010, Shanghai, China
Source: DBLP

ABSTRACT Detection of contextual properties is one of the primary approaches to enabling context-awareness. In order to adapt to temporal evolution of the pervasive computing environment, context-aware applications often need to detect behavioral properties specified over the contexts. This problem is challenging mainly due to the intrinsic asynchrony of pervasive computing environments. However, existing schemes implicitly assume the availability of a global clock or synchronous coordination, thus not working in asynchronous environments. We argue that in pervasive computing environments, the concept of time needs to be reexamined. Toward this objective, we propose the Ordering Global Activity (OGA) algorithm, which detects behavioral contextual properties in asynchronous environments. The essence of our approach is to utilize the message causality and its on-the-fly coding as logical vector clocks. The OGA algorithm is implemented and evaluated based on the open-source context-aware middleware MIPA. The evaluation results show the impact of asynchrony on the detection of contextual properties, which justifies the primary motivation of our work. They also show that OGA can achieve accurate detection of contextual properties in dynamic pervasive computing environments.

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    ABSTRACT: Formal specification and runtime detection of contextual properties is one of the primary approaches to enabling context awareness in pervasive computing environments. Due to the intrinsic dynamism of the pervasive computing environment, dynamic properties, which delineate concerns of context-aware applications on the temporal evolution of the environment state, are of great importance. However, detection of dynamic properties is challenging, mainly due to the intrinsic asynchrony among computing entities in the pervasive computing environment. Moreover, the detection must be conducted at runtime in pervasive computing scenarios, which makes existing schemes do not work. To address these challenges, we propose the property detection for asynchronous context (PDAC) framework, which consists of three essential parts: 1) Logical time is employed to model the temporal evolution of environment state as a lattice. The active surface of the lattice is introduced as the key notion to model the runtime evolution of the environment state; 2) Specification of dynamic properties is viewed as a formal language defined over the trace of environment state evolution; and 3) The SurfMaint algorithm is proposed to achieve runtime maintenance of the active surface of the lattice, which further enables runtime detection of dynamic properties. A case study is conducted to demonstrate how the PDAC framework enables context awareness in asynchronous pervasive computing scenarios. The SurfMaint algorithm is implemented and evaluated over MIPA - the open-source context-aware middleware we developed. Performance measurements show the accuracy and cost-effectiveness of SurfMaint, even when faced with dynamic changes in the asynchronous pervasive computing environment.
    IEEE Transactions on Parallel and Distributed Systems 01/2013; 24(8):1546-1555. · 1.80 Impact Factor
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    ABSTRACT: Runtime detection of contextual properties is one of the primary approaches to enabling context-awareness in pervasive computing scenarios. Among various properties the applications may specify, the concurrency property, i.e., property delineating concurrency among contextual activities, is of great importance. It is because the concurrency property is one of the most frequently specified properties by context-aware applications. Moreover, the concurrency property serves as the basis for specification of many other properties. Existing schemes implicitly assume that context collecting devices share the same notion of time. Thus, the concurrency property can be easily detected. However, this assumption does not necessarily hold in pervasive computing environments, which are characterized by the asynchronous coordination among heterogeneous computing entities. To cope with this challenge, we identify and address three essential issues. First, we introduce logical time to model behavior of the asynchronous pervasive computing environment. Second, we propose the logic for specification of the concurrency property. Third, we propose the Concurrent contextual Activity Detection in Asynchronous environments (CADA) algorithm, which achieves runtime detection of the concurrency property. Performance analysis and experimental evaluation show that CADA effectively detects the concurrency property in asynchronous pervasive computing scenarios.
    IEEE Transactions on Parallel and Distributed Systems 01/2012; 23(4):744-750. · 1.80 Impact Factor

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