Context-Aware Framework for Performance Tuning via Multi-action Evaluation

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Nimalasena, Asanga ; Getov, Vladimir

Context-aware systems perform adaptive changes in several ways. One way is for the system developers to encompass all possible context changes in a context-aware application and embed them into the system. However, this may not suit situations where the system encounters unknown contexts. In such cases, system inferences and adaptive learning are used whereby the system executes one action and evaluates the outcome to self-adapts/self-learns based on that. Unfortunately, this iterative approach is time-consuming if high number of actions needs to be evaluated. By contrast, our framework for context-aware systems finds the best action for unknown context through concurrent multi-action evaluation and self-adaptation which reduces significantly the evolution time in comparison to the iterative approach. In our implementation we show how the context-aware multi-action system can be used for a context-aware evaluation for database performance tuning.
  • References (24)
    24 references, page 1 of 3

    [1] B.N. Schilit and M.M Theimer, Disseminating active map information to mobile hosts, IEEE Network, 8 (5), 22-32, 1994.

    [2] P.J. Brown, J.D. Bovey and X. Chen, Context-aware applications: from the laboratory to the marketplace, IEEE Personal Communications, 4 (5), 58-64, 1997.

    [3] A.K. Dey, Understanding and using context, Personal and Ubiquitous Computing, vol. 5, no. 1, pp. 4-7, 2001.

    [4] K. Kwang-Eun and S. Kwee-Bo, Development of context aware system based on Bayesian network driven context reasoning method and ontology context modeling, Proc. Int. Conf. Control, Automation and Systems (ICCAS), pp. 2309-2313, 2008.

    [5] J. Madhusudanan, A. Selvakumar and R. Sudha, Frame work for context aware applications, Computing Communication and Networking Technologies (ICCCNT), pp. 1-4, 2010.

    [6] N. O'Connor, R. Cunningham and V. Cahill, Self-Adapting Context Definition, Proc. 1st Int. Conf. Self-Adaptive and Self-Organizing Systems (SASO '07), pp. 336-339, 2007.

    M. Ziauddin, D. Das, H. Su, Y. Zhu, K. Yagoub, Optimizer plan change management: improved stability and performance in Oracle 11g, in VLDB '08, 2008.

    [8] H. Herodotou and S. Babu, Automated SQL tuning through trial and (sometimes) error. Workshop on Testing Database Systems, 2009.

    [9] S. Babu, N. Borisov, S. Duan, H. Herodotou, and V. Thummala, Automated experiment-driven management of (database) systems. In conference on Hot topics in operating systems (HotOS'09), 2009.

    [10] J. He, Y. Zhang, G. Huang and J. Cao, A smart web service based on the context of things. ACM Trans. Internet Technology. 11 (3), 13:1- 13:23, 2012.

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