Guanling Lee

Architecture for mobility and QoS support in all-IP wireless networks

Mobility management and quality-of-service (QoS) provisioning are the important tasks on the future development of wireless networks. The high host mobility makes these tasks more challenging. In this paper, we propose an architecture which supports both mobility and QoS management in Internet protocol (IP)-based wireless networks. In mobility management, the fast handoff, which the packets are forwarded in advance to the neighboring locations where a mobile node (MN) may move to, is provided to reduce the service disruption. Also, the fast location lookup, which the routing information about a MN is replicated to some routers, is provided to avoid the triangular routing problem incurred by the protocol of mobile IP. In QoS provisioning, we enable the end-to-end QoS guarantee by using the resource reservation protocol (RSVP) signaling. In particular, the RSVP aggregation technique is used to avoid the scalability problem. Also, the technique of passive resource reservation is used to reduce the influence of host mobility on the resource reservation delay. We emphasize the integration of mobility and QoS management in the architecture design. A performance analysis is given to justify the benefits of our proposed architecture.

An efficient multipolling mechanism for IEEE 802.11 wireless LANs

To expand support for applications with QoS requirements in wireless local area networks (WLANs), the 802.11 E Task Group was formed to enhance the current IEEE 802.11 Medium Access Control (MAC) protocol. The multipolling mechanism was discussed in the task group, but some problems remain unsolved. In this paper, we show a design of the multipolling mechanism with the advantages of high channel utilization and low implementation overhead. In our proposed mechanism, wireless stations use a priority-based contention scheme to coordinate in themselves the transmission order on the channel. Moreover, we propose a polling schedule mechanism for our proposed multipoll to serve real-time traffic with constant and variable bit rates. The bounded delay requirement of the real-time traffic can be satisfied in our scheduling model. We establish an admission test to estimate the system capacity and to determine whether a new connection can be accepted. We study the performance of our proposed mechanism analytically, as well as through simulated experiments. The results show that the proposed mechanism is more efficient than the one discussed in the IEEE 802.11 E task group.

Broadcast data allocation for efficient access of multiple data items in mobile environments

The issue of data broadcast has received much attention in mobile computing. A periodic broadcast of frequently requested data can reduce the workload of the up-link channel and facilitate data access for the mobile user. Many approaches have been proposed to schedule data items for broadcasting. However, the issues of accessing multiple data items on the broadcast channel are less discussed. Two problems are discussed in this paper, that is, deciding the content of the broadcast channel based on the queries from the clients, and scheduling the data items to be broadcast. We will show that these two problems are NP-complete. Different heuristics to these problems are presented and compared through performance evaluations.

A strategy for efficient access of multiple data items in mobile environments

Many approaches have been proposed to schedule data items for broadcasting in a mobile environment. However, the issues of accessing multiple data items on the broadcast channel are less discussed. In this paper, an efficient strategy for accessing multiple data items in mobile environments is proposed. Two issues are investigated in this paper, that is, deciding the content of the broadcast channel based on the queries from the clients, and scheduling the data items to be broadcast. Experiments are performed to compare our proposed methods for deciding the content and to show that our data scheduling methods can reduce the average access time without considerable increase on processing time.

Data allocation on wireless broadcast channels for efficient query processing

Data broadcast is an excellent method for efficient data dissemination in the mobile computing environment. The application domain of data broadcast will be widely expanded in the near future, where the client is expected to perform complex queries or transactions on the broadcast data. To reduce the access latency for processing the complex query, it is beneficial to place the data accessed in a query close to each other on the broadcast channel. In this paper, we propose an efficient algorithm to determine the allocation of the data on the broadcast channel such that frequently co-accessed data are not only allocated close to each other, but also in a particular order which optimizes the performance of query processing. Our mechanism is based on the well-known problem named optimal linear ordering. Experiments are performed to justify the benefit of our approach.

Hiding sensitive patterns in association rules mining

Data mining techniques have been developed in many applications. However it also causes a threat to privacy. We investigate to find an appropriate balance between a need for privacy and information discovery on association patterns. We propose an innovative technique for hiding sensitive patterns. In our approach, a sanitization matrix is defined. By multiplying the original transaction database and the sanitization matrix, a new database, which is sanitized for privacy concern, is described. Moreover a set of experiments is performed to show the effectiveness of our approach.

Index and data allocation on multiple broadcast channels considering data access frequencies

In a wireless environment, the bandwidth of the channels and the energy of the portable devices are limited. Data broadcast has become an excellent method for efficient data dissemination. In this paper the problem for generating a broadcast program of a set of data items with the associated access frequencies on multiple channels is explored. In our approach, we consider allocating index information and data items on multiple broadcast channels by extending the distributed indexing approach. Moreover global data replication and local data allocation are performed to improve the average access time of all data items. Simulation is performed to compare the performance of our approach with an existing approach. The result of the experiments shows that our approach outperforms the existing approach.

A novel method for protecting sensitive knowledge in association rules mining

Discovering frequent patterns from huge amounts of data is one of the most studied problems in data mining. However, some sensitive patterns with security policies may cause a threat to privacy. We investigate to find an appropriate balance between a need for privacy and information discovery on frequent patterns. By multiplying the original database and a sanitization matrix together, a sanitized database with privacy concerns is obtained. Additionally, a probability policy is proposed to against the recovery of sensitive patterns and reduces the modifications of the sanitized database. A set of experiments is also performed to show the benefit of our work.

A near optimal algorithm for generating broadcast programs on multiple channels

In a wireless environment, the bandwidth of the channels and the energy of the portable devices are limited. Data broadcast has become an excellent method for efficient data dissemination. In this paper, the problem for generating a broadcast program of a set of data items with the associated access frequencies on multiple channels is explored. In our approach, an expected average access time of the broadcast data items is first derived. The broadcast program is then generated, which minimizes the expected average access time. Simulation is performed to compare the performance of our approach with two existing approaches. The result of the experiments shows that our approach outperforms others and is in fact close to the optimal.

Efficient Graph-Based Algorithms for Discovering and Maintaining Association Rules in Large Databases

Abstract. In this paper, we study the issues of mining and maintaining association rules in a large database of customer transactions. The problem of mining association rules can be mapped into the problems of finding large itemsets which are sets of items brought together in a sufficient number of transactions. We revise a graph-based algorithm to further speed up the process of itemset generation. In addition, we extend our revised algorithm to maintain discovered association rules when incremental or decremental updates are made to the databases. Experimental results show the efficiency of our algorithms. The revised algorithm is a significant improvement over the original one on mining association rules. The algorithms for maintaining association rules are more efficient than re-running the mining algorithms for the whole updated database and outperform previously proposed algorithms that need multiple passes over the database.