An Efficient Feedback-based Trust Model for Pervasive Computing

In pervasive computing environments, pervasive devices should collaborate effectively such that the vision of pervasive computing will come true. However, without trust, pervasive devices cannot collaborate effectively. Distributed trust systems (DTS) may support trust and thus foster collaboration in hostile pervasive computing environments. The challenge for DTS is how to aggregate the local trust values without a centralized storage and management facility. Another challenge is that such systems should have minimal overhead in terms of computation, infrastructure, storage, and message complexity, especially in real-time embedded systems and wireless networks. We focus on the computation and storage of DTS in this paper. The computation time in many existing DTS will increase with the amount of data to be processed. The efficiency of the existing DTS ranges from O (t2) to O (log t). We propose an efficient trust model based on the incremental Proportional-Integral-Derivative (PID) controller and the efficiency of our model is O(1) that uses only four data and needs four multiplications, four additions and two subtractions. Besides, this paper reviews some trust models and discusses the robust effects for some important issues such as consistent node behavior, sudden fluctuations in node behavior and unintentional errors. The modified version of our trust model for slow increasing for new entity and quick dropping for misbehaving is also investigated