In this paper, a novel prediction technique is proposed, which uses road topology information for prediction. The proposed scheme uses real time positioning information and road topology information, which matches with the real environment. The scheme uses flexible channel assignment to maintain a better tradeoff between forced termination and call blocking probabilities. For reservation of resources in advance, the information about future handoffs is obtained from the road topology prediction technique. To show the effectiveness of the prediction scheme and flexible channel assignment scheme, this work aims at simulation of other channel assignment strategies viz., fixed and dynamic channel assignment strategy with and without incorporating the prediction based on road topology information. It gives accurate prediction results which helps to maintain a better QoS and resource management.
TopIntroduction
Today’s navigation systems are mostly based on a quite complex positioning system involving multi-sensor systems (differential odometers, gyros, and magnetic field sensors) in the mobile vehicle coupled with a global positioning system (GPS). Mobility prediction for mobile terminal (MT) traveling in a road is possible through GPS but that is not accurate and indeed not available in all areas. However, research shows that 85% of mobility activities in road traffic occur in urban areas where the availability of GPS signals is around 15 to 40%. Rare availability of satellite means due to masking and multi-path effects in urban areas, magnetic disturbances, wheel slips, and unfavorable error propagation lead to loss of position and in principle to total system failures. To make positioning systems available for every mobile vehicle (cars, motorbike, bicycle, pedestrian), development of navigation systems based on a personal digital assistant (PDA), digital maps, mobile phones, and GPS module are initiated (Zhao, 1997; Kyamakya, et al., 2002; Syrjärinne, 2001; Kaplan, 1996; Schwarz, & El-Sheimy, 1999).
Mobility prediction is an exciting research area in which mobile positioning is extremely valuable. The use of real-time positioning information for mobility prediction could potentially give rise to better accuracy and greater adaptability to time-varying conditions than previous methods (Adusei, et. al., 2002; Hellebrandt, Mathar, & Scheibenbogen, 1997; Hellebrandt & Mathar, 1999). The availability for a practical and accurate mobility prediction technique could open the door to many applications such as resource reservation, location tracking and management, location-based services, and others that have yet to be identified. If the system has prior knowledge of the exact trajectory of every MT, it could take appropriate steps to reserve resources so that quality of service (QoS) may be guaranteed during the MT’s connection lifetime (Pathirana, Svkin, & Jha, 2004). However, such an ideal scenario is very unlikely to occur in real life. Instead, much of the work on resource reservation has adopted a predictive approach (Aljadhai & Znati, 2001; Soh & Kim, 2001; Choi & Shin, 1998). A generalized framework for both describing the mobility and updating location information is considered based on a state-based mobility model (Song, Kang, & Park, 2005), and by caching and batch processing (Lee, Zhu, & Hu, 2005). Semantics prefetching strategy is developed, which, utilizes users’ information to manage location dependent data’s (Sang, Song., Park, & Hwang, 2005). Indexing schemes for location dependent queries (Waluyo, Srinivasan, & Taniar, 2005a) and data broadcasting are introduced in (Waluyo, Srinivasan, & Taniar, 2005b; Waluyo, Srinivasan, Taniar, & Rahayu, 2005). Management of data items in mobile databases and broadcasting system is proposed (Waluyo, Srinivasan, & Taniar, 2004). A mobile query processing approach is proposed when the user’s location moves from one base station to another (Jayaputera & Taniar, 2005).