In recent years, WiMAX has become a popular wireless communication technology. The IEEE 802.16 standard defines both point-to-multipoint ( PMP ) mode and mesh mode operations for WiMAX networks. In mesh mode, because of the long distance from SSs to BS, some SSs transmit packets by multi-hop manner. Moreover, mesh networks are always more complex and have worse network performance than PMP. In a limited bandwidth situation, the major goal is to increase network throughput. As a result of above reasons, routing tree construction, interference-aware scheme, and centralized scheduling are proposed. In this paper, we focus on centralized scheduling part and propose the Broadcast Tree-Based mechanism to improve existing method. Simulation results show that our mechanism significantly increase the network throughput in mesh mode opeartion.

This paper proposes a simple and low cost implementation framework for a policy-based network management (PBNM) system. The framework consists of reusing traditional network management system resources, specifying network management policies through the database language SQL, and designing a management database. It supports automatic network management policy processing. Finally, we used a simple example to test and verify our framework.

The authors investigate the inference problems due to functional dependencies (FD) and multivalued dependencies (MVD) in a multilevel relational database (MDB) with attribute and record classification schemes, respectively. The set of functional dependencies to be taken into account in order to prevent FD-compromises is determined. It is proven that incurring minimum information loss to prevent compromises is an NP-complete problem. An exact algorithm to adjust the attribute levels so that no compromise due to functional dependencies occurs is given. Some necessary and sufficient conditions for MVD-compromises are presented. The set of MVDs to be taken into account for controlling inferences is determined. An algorithm to prevent MVD-compromises in a relation with conflict-free MVDs is given.>

The authors investigate the suitability of the cell suppression by merging (CSM) technique as an SDB (statistical database) protection mechanism, and give various heuristic algorithms for the minimum information loss. They first revise the definition for the information loss when query probabilities are taken into account. This definition reflects the actual utilization of cells in the lattice. The authors then propose a heuristic approach to be used with the CSM technique. This approach tries to minimize the information loss by properly choosing the merging pairs. Experimental results show that, in most cases, the information loss is lower than that of the case in which the query probabilities are not considered. This indicates that the actual information loss under query probabilities is low when the CSM technique is combined with the heuristic approach. It is concluded that the CSM technique is therefore an effective protection mechanism for summary tables. It is also shown that the CSM technique is also applicable in the generalized lattice model as an effective security enforcement mechanism. The authors propose several heuristic approaches to minimize the information loss when this technique is applied.>

We investigate the inference problems due to functional dependencies (FD) and multi-valued dependencies (hND) in a multilevel relational database (MDB) with attribute and record classification schemes, respectively. For FDs, we show that, to prevent compromise, the security levels of attributes must be assigned by using the knowledge of functional dependencies. Under the assumption that all the attributes in the database have been assigned classification levels according to real world requirements, we first determine the set of functional dependencies to be taken into account. Then, we prove that changing the minimum number of attribute levels to prevent compromise is an NP-complete problem. However, assuming that the number of functional dependencies involved in inference is low, we give an exact algorithm to adjust the minimum number of attribute levels so that no compromise due to functional dependencies occurs. For NfVDs, we give a necessary and sufficient condition for compromise due to a single MVD, and then propose an algorithm to prevent single MVD inferences.

A statistical database (SDB) is a database that is used to provide simple summary statistics (e.g., SUM, COUNT, MAX, MEDIAN, etc.) about populations stored in the database and that supports statistical data analysis. When SDB users infer protected information in the SDB from responses to queries, we say that the SDB is compromised. The security problem of SDB is to allow simple summary statistics about protected information in the SDB while preventing compromise. In this paper, we investigate the effectiveness of rounding in statistical databases as a protection technique for SUM and COUNT queries. We consider the generalization hiermchy of the Data Abstraction model and assume there are four different types of inference mechanisms (called R1-R4 range reductions) available for SDB users. For a two-level generalization hierarchy, we find (a) necessary conditions for compromise, and (b) a necessary and sufficient condition for eliminating R1-R4 range reductions. We then describe a procedure for choosing a round-ing base for a tree-organized generalization hierarchy that allows range reductions, but guarantees a minimum range size for protected values in the hierarchy.