Location management cost reduction using fuzzy logic in cellular radio network

Munadi, Rizal; Ismail, Mahamod; Abdullah, Mardina; Misran, Norbahiah

doi:10.1109/iconspace.2011.6015875

Cited by 5 publications

(2 citation statements)

References 22 publications

(17 reference statements)

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“…PP relies on Bayes theorem, GP uses ant colony optimization (ACO), while SP tries to detect the topological architecture of the current registration area to enhance the prediction process. Munadi and Ismail [27] proposes, validates, and evaluates the performance of a new LU strategy using fuzzy logic for cellular radio system. In this research, three metrics are proposed and used for fuzzy evaluation, which are; movement speed, MT density, and residence time.…”

Section: Related Workmentioning

confidence: 99%

Historical based location management strategies for PCS networks

2016

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Due to the current popularity of wireless communication, personal communication service networks have attracted a lot of attention. As mobile terminals (MTs) in such networks have the ability to communicate on the move, location management (LM) is a critical issue that should be handled carefully. Managing MTs locations is to simultaneously perform two main operations, which are; location update and paging. A good LM strategy maintains both operations with the minimum time and signaling penalties. Although several LM strategies have been introduced, they still suffer from several drawbacks. This paper introduces three novel LM strategies, which are; historical based location management (HBLM), direction based location management (DBLM) and trajectory based location management (TBLM). TBLM strategy is based on geographical position of MTs, while HBLM and DBLM are based on geographical position of MTs as well as time aspects. Visited locations are saved in MT's internal cache in the form of cell identifier as well as the corresponding time interval. Location tracking is fully supervised by the MT's current visitor location register (VLR). On the other hand, the collected location information in MT's cache is sent to VLR when MT passed through a previously defined number of cells or when a previously defined number of time periods has elapsed. In HBLM, paging is done according to the historical movements saved in VLR, while DBLM takes also MT's movement direction into consideration while in TBLM, paging is done according to the historical trajectories that MTs are used to follow. Experimental results have shown that the proposed LM strategies significantly improve MTs' tracking process as they introduce the minimum signaling penalty (for paging and registration) with an acceptable paging time delay compared with recent LM strategies.

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Section: Related Workmentioning

confidence: 99%

Historical based location management strategies for PCS networks

2016

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“…Another latest research done objective of this research is to propose, validate and evaluate the performance of location update scheme using fuzzy logic technique [21] for cellular radio system. Three metrics: speed, user density and residence time are proposed and used for fuzzy evaluation.…”

Section: Previous Workmentioning

confidence: 99%

Timer based Location Management in Cellular Network using Cache Memory

Ahirwal¹,

Sahelay²

2012

IJCA

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Location management is essential task in current cellular system. Mobility prediction is widely used to assist handoff management, resource reservation and service preconfiguration. Location management methods are to find out mobile unit current location. Location update and paging have to maintain efficiently to minimize location management cost in cellular network. This paper introduce new timer based algorithm using cache memory for reducing paging cost. This algorithm is based on user's daily predefined moving geographical activities pattern, according to time. Paging decision for user is based on this predicted location for any instance of time interval. This predicated value again sort by higher probability of user finding in any cell for that time duration. This prediction information is saved by mobile unit in its personal cache memory for every fixed time interval. If more prediction value searched for paging, so it increases average paging cost. Therefore here is threshold value used for maintain page hit ratio. But if threshold value is to less hit ratio comes down rapidly for smaller threshold values. Thus threshold value helps to maintain hit page, hit to page miss ratio. The results confirm the effectiveness of this method compare to existing method for real time in mobile services and proposed method is 6% more efficient in average hit ratio.

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