Abstract: We propose a novel graphical technique (SVision) for
intrusion detection, which pictures the network as a community of
hosts independently roaming in a 3D space defined by the set of
services that they use. The aim of SVision is to graphically cluster
the hosts into normal and abnormal ones, highlighting only the ones
that are considered as a threat to the network. Our experimental
results using DARPA 1999 and 2000 intrusion detection and
evaluation datasets show the proposed technique as a good candidate
for the detection of various threats of the network such as vertical
and horizontal scanning, Denial of Service (DoS), and Distributed
DoS (DDoS) attacks.
Abstract: In wireless sensor networks,the mobile agent technology is used in data fusion. According to the node residual energy and the results of partial integration,we design the node clustering algorithm. Optimization of mobile agent in the routing within the cluster strategy for wireless sensor networks to further reduce the amount of data transfer. Through the experiments, using mobile agents in the integration process within the cluster can be reduced the path loss in some extent.
Abstract: Advances in computing applications in recent years
have prompted the demand for more flexible scheduling models for
QoS demand. Moreover, in practical applications, partly violated
temporal constraints can be tolerated if the violation meets certain
distribution. So we need extend the traditional Liu and Lanland model
to adapt to these circumstances. There are two extensions, which are
the (m, k)-firm model and Window-Constrained model. This paper
researches on weakly hard real-time constraints and their combination
to support QoS. The fact that a practical application can tolerate some
violations of temporal constraint under certain distribution is
employed to support adaptive QoS on the open real-time system. The
experiment results show these approaches are effective compared to
traditional scheduling algorithms.
Abstract: EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.