An Intelligent Location Management approaches in GSM Mobile Network

Abstract

Location management refers to the problem of updating and searching the current location of mobile nodes in a wireless network. To make it efficient, the sum of update costs of location database must be minimized. Previous work relying on fixed location databases is unable to fully exploit the knowledge of user mobility patterns in the system so as to achieve this minimization. The study presents an intelligent location management approach which has interacts between intelligent information system and knowledge-base technologies, so we can dynamically change the user patterns and reduce the transition between the VLR and HLR. The study provides algorithms are ability to handle location registration and call delivery.

Authors and Affiliations

N. Mallikharjuna Rao , Prof M. M Naidu , P. Seetharam

Keywords

Related Articles

 A Design of a Multi-Agent Smart E-Examiner

 this paper proposes a design of an application of multi agent technology on a semantic net knowledge base, to build a smart e-examiner system. This e-examiner could be used in building and grading a personalized sp...

 Method for Vigor Diagnosis of Tea Trees based on Nitrogen Content in Tealeaves Relating to NDVI

 Method for vigor diagnosis of tea trees based on nitrogen content in tealeaves relating to NDVI is proposed. In the proposed method, NIR camera images of tealeaves are used for estimation of nitrogen content in tea...

 A Registration Method for Multimodal Medical Images Using Contours Mutual Information

 In recent years, mutual information has developed as a popular image registration measure especially in multimodality image registration. For different modality medical images, the contour of tissues or organs is s...

 FISHER DISTANCE BASED GA CLUSTERING TAKING INTO ACCOUNT OVERLAPPED SPACE AMONG PROBABILITY DENSITY FUNCTIONS OF CLUSTERS IN FEATURE SPACE

Fisher distance based Genetic Algorithm: GA clustering method which takes into account overlapped space among probability density functions of clusters in feature space is proposed. Through experiments with simulation da...

 The Mobile Version of the Predicted Energy Efficient Bee-Inspired Routing (PEEBR)

 In this paper, the previously proposed Predictive Energy Efficient Bee-inspired Routing (PEEBR) family of routing optimization algorithms based on the Artificial Bees Colony (ABC) Optimization model is extended fro...

Download PDF file
  • EP ID EP108640
  • DOI -
  • Views 103
  • Downloads 0

How To Cite

N. Mallikharjuna Rao, Prof M. M Naidu, P. Seetharam (2012). An Intelligent Location Management approaches in GSM Mobile Network. International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(1), 30-37. https://europub.co.uk/articles/-A-108640