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Encapsulation and Entity-Based Approach of Interconnection Between Sensor Platform and Middleware of Pervasive Computing

  • Shinyoung Lim
  • Abdelsalam (Sumi) Helal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4239)

Abstract

In this paper, we present a unique mechanism that enables seamless interconnection and scalability of the interface between the sensor platform layer and the middleware layer in pervasive computing. The disadvantages of using one-to-one hard coding for various device drivers and firmware for interfacing sensor platform and middleware layers are primarily a lack of flexibility and scalability when the system changes environments. The encapsulation of access point of the sensor platform layer provides developers and designers with an effective way of interconnecting and scaling up with diverse and various kinds of sensors and actuators. In this paper, we define encapsulation of the access point of the sensor platform layer. The module for encapsulating the detected sensor data is called ‘context representer’. The context representer converts detected sensor data to raw context. For interconnecting with the sensor platform layer and the middleware layer, ‘entity manager’ module in the middleware layer for each entity of context representer is defined. The entity manager is for transforming the raw context to a general context. Then, the middleware is able to interact with context-aware applications according to the reasoning with context in the middleware layer, upper layer requests and lower layer status, without being influenced by a change of sensor node and sensor platform environments. We present the encapsulation mechanism and entity manager for efficient interfacing and scalability of contextaware applications and compare them with other approaches.

Keywords

Resource Description Framework Delivery Time Smart Home Pervasive Computing Context Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shinyoung Lim
    • 1
  • Abdelsalam (Sumi) Helal
    • 1
  1. 1.Mobile and Pervasive Computing Laboratory, Computer & Information Science and Engineering Department, College of EngineeringUniversity of FloridaGainesvilleUSA

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