Location database clustering to achieve location management time cost reduction in a mobile computing system

Chen, Jixiong; Li, Guohui; Xu, Hui; X, Cai; Bing, Yang

doi:10.1109/wcnm.2005.1544300

Cited by 2 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…dis(cur_RA(x), cur_RA(y)): The distance between mobile users x and y. Therefore, dis(x,y)= dis(cur_RA(x), cur_RA(y)) When calculating the location management cost, as in [1,3], we consider the following related costs in location update and the lookup procedure: L: The cost of following a link in the tree of the location databases, i.e., sending a message to the parent or the child node of a location database. U: The cost of a database update.…”

Section: Terminologymentioning

confidence: 99%

“…Hence, the topology of the location databases can affects the location management cost greatly. According to the more detailed example given by [3], by switching the position of LDB responsible for RA 5 and LDB responsible for RA 7 with each other, the location update cost saving can achieve 300L+300U.…”

Section: Problemmentioning

confidence: 99%

“…Another LDB clustering algorithm proposed by Chen in [3] has several drawbacks, i.e. the number of RAs in a cluster is fixed which may enlarge the amount of clusters thus increasing the cost of update as well as communication, and caching strategy is not employed in his algorithm.…”

Section: The Hybrid Strategymentioning

confidence: 99%

“…TCr: Total cost of randomly cluster method under which the location databases are connected with their randomly chosen neighboring location databases. TCcsc: Total cost of clustering based on set-covering algorithm proposed in [3]. TCh: Total cost of the hybrid strategy.…”

Section: Simulation and Performance Analysismentioning

confidence: 99%

“…Ma [7] proposes a hierarchical clustering algorithm to cluster the moving log, and then uses the clustering results to dynamically reorganize LDBs. Chen [3] gives an algorithm to cluster LDBs based on mobility patterns of mobile clients in different cells with the objective to reduce the location management cost. However, the algorithms mentioned above do not reuse the users' location information, which is essentially a form of.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Hybrid Strategy of Location Database Clustering and Dynamic Hierarchical Caching in PCS Networks

Liang

Wei

et al. 2006

2006 International Conference on Wireless Communications, Networking and Mobile Computing

View full text Add to dashboard Cite

The location database (LDB) organization has much impact on the performance of Personal Communication Services (PCS) network. In order to optimize the LDB organization, users' moving and calling patterns should be considered together. In this paper, we propose a hybrid strategy of location database clustering and dynamic hierarchical caching for a hierarchical database structure in PCS network. The main goal of our strategy is to reduce the cost of location management and network signaling traffic of data access and communication. The strategy consists of two steps: (1) clustering location databases based on users' moving patterns in the system; (2) arranging the clusters and then caching the users' location information of the adjacent cluster at each cluster's representative node based on users' calling patterns. A threshold required for beneficial caching is used to determine whether to cache. Through experimental simulation, the comparison results demonstrate that our strategy can result in total cost reduction.

show abstract

Section: Terminologymentioning

confidence: 99%

Section: Problemmentioning

confidence: 99%

Section: The Hybrid Strategymentioning

confidence: 99%

Section: Simulation and Performance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations