Results 1 -
2 of
2
Mutihop-enabled Trusted Handoff Algorithm in Heterogeneous Wireless Networks
"... Abstract—Ubiquitous and heterogeneous wireless network is an important form of network, and vertical handoff is one of the key issues of the mobility management in this type of network. In Ad hoc network, multihop-enabled forwarding is able to expand network coverage and reduce single-hop propagatio ..."
Abstract
- Add to MetaCart
(Show Context)
Abstract—Ubiquitous and heterogeneous wireless network is an important form of network, and vertical handoff is one of the key issues of the mobility management in this type of network. In Ad hoc network, multihop-enabled forwarding is able to expand network coverage and reduce single-hop propagation distance. Based on the above, TMVHA (trusted and multihop-enabled Vertical Handoff Algorithms) is designed and multihop trust management mechanism is established, thus enhancing the handoff performance of the mobile nodes and the network performance after handoff. The experimental result shows that: the algorithm proposed in this paper outperforms those without considering multihop and node trust in handoff times and throughput, and at the same time being able to reduce the influence of the attack on network by malicious nodes. Index Terms—Heterogeneous wireless network, vertical handoff, multihop forwarding, trust I.
Consistency of Probability Decision Rules and Its Inference in Probability Decision Table
, 19
"... In most synthesis evaluation systems and decision-making systems, data are represented by objects and attributes of objects with a degree of belief. Formally, these data can be abstracted by the form objects; attributes; P , where P represents a kind degree of belief between objects and attributes, ..."
Abstract
- Add to MetaCart
In most synthesis evaluation systems and decision-making systems, data are represented by objects and attributes of objects with a degree of belief. Formally, these data can be abstracted by the form objects; attributes; P , where P represents a kind degree of belief between objects and attributes, such that, P is a basic probability assignment. In the paper, we provide a kind of probability information system to describe these data and then employ rough sets theory to extract probability decision rules. By extension of Dempster-Shafer evidence theory, we can get probabilities of antecedents and conclusion of probability decision rules. Furthermore, we analyze the consistency of probability decision rules. Based on consistency of probability decision rules, we provide an inference method to finish inference of probability decision rules, which can be used to decide the class of a new object x . The conclusion points out that the inference method of the paper not only deals with precise information, but also imprecise or uncertain information as well.