Location Prediction for Improvement of Communication Protocols in Wireless Communications: Considerations and Future Directions

times.Location prediction is the estimation of a mobile hosts location at a time in future. When the future location of a mobile host isknown, this information can be used in a number of ways to improve the performance of the wireless communication network protocols and in turn the overall performance of the network.The hosts are free to move anywhere. This mobilityaffectsdifferent protocolsin the wireless communication network.The mobile hosts can move with different mobility patterns .Mobility Models are used to represent the different mobility patterns. Mobility metrics are used to differentiate the mobility models from each other. Different mobility models impact the protocols in different ways.In this paper,the importance of location prediction for improvement of different communication protocols for wireless communications is discussed. Different constituents of location prediction techniques are described.Apart from the conventional mobility prediction techniques, it is concluded thatthere is a need to look for non conventional solutions like bio inspired systems for making efficient location prediction techniques. KeywordsLocation Prediction , Mobile hosts, wireless communication, MANET

[1]  Thad Starner,et al.  Learning Significant Locations and Predicting User Movement with GPS , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[2]  H. Mehdi.  Mobility prediction with LLT algorithm in wireless networks , 2010, 2010 International Conference on Information, Networking and Automation (ICINA).

[3]  LiuGeorge,et al.  A class of mobile motion prediction algorithms for wireless mobile computing and communication , 1996 .

[4]  Natarajan Meghanathan,et al.  Location Prediction Based Routing Protocol for Mobile Ad Hoc Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[5]  Yin Zhang,et al.  Exploiting temporal stability and low-rank structure for localization in mobile networks , 2010, MobiCom.

[6]  Chris Schmandt,et al.  A User-Centered Location Model , 2002, Personal and Ubiquitous Computing.

[7]  Mingyan Liu,et al.  Random waypoint considered harmful , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[8]  Mirjana D. Stojanovic,et al.  MANET routing protocols vs. mobility models: performance analysis and comparison , 2009 .

[9]  Seok K. Hwang,et al.  Swarm Group Mobility Model for Ad Hoc Wireless Networks , 2007 .

[10]  Krishnendu Chakrabarty,et al.  Distributed Mobility Management for Target Tracking in Mobile Sensor Networks , 2007, IEEE Transactions on Mobile Computing.

[11]  Hyong S. Kim,et al.  QoS provisioning in cellular networks based on mobility prediction techniques , 2003, IEEE Commun. Mag..

[12]  Sami Tabbane,et al.  An Alternative Strategy for Location Tracking , 1995, IEEE J. Sel. Areas Commun..

[13]  Ahmed Karmouch,et al.  A mobility prediction architecture based on contextual knowledge and spatial conceptual maps , 2005, IEEE Transactions on Mobile Computing.

[14]  Radhika Ranjan Roy,et al.  Handbook of Mobile Ad Hoc Networks for Mobility Models , 2010 .

[15]  Marwan Al-Akaidi,et al.  Link stability and mobility in ad hoc wireless networks , 2007, IET Commun..

[16]  Hee Yong Youn,et al.  Vertical handover based on the prediction of mobility of mobile node , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[17]  Jian Tang,et al.  Reliable routing in mobile ad hoc networks based on mobility prediction , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[18]  Panlong Yang,et al.  Mobility Prediction Algorithm with Differential Accuracy Requirements in Target Tracking Sensor Network , 2009, 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing.

[19]  Ahmed Helmy,et al.  The effect of mobility-induced location errors on geographic routing in ad hoc networks: analysis and improvement using mobility prediction , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[20]  A. Karmouch,et al.  Mobility prediction based service location and delivery , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[21]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[22]  Mahmood Fathy,et al.  Optimized Routing Based on Mobility Prediction in Wireless Mobile Adhoc Networks for Urban Area , 2008, Fifth International Conference on Information Technology: New Generations (itng 2008).

[23]  Taieb Znati,et al.  Predictive mobility support for QoS provisioning in mobile wireless environments , 2001, IEEE J. Sel. Areas Commun..

[24]  Hamid R. Rabiee,et al.  Mobility Aware Distributed Topology Control in Mobile Ad-Hoc Networks with Model Based Adaptive Mobility Prediction , 2007, Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2007).

[25]  Madhusudan Singh,et al.  Impact and Performance of Mobility Models in Wireless Ad-hoc Networks , 2009, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology.

[26]  Pontus Svenson,et al.  A Flock-Based Model for Ad Hoc Communication Networks , 2003 .

[27]  Xiaoyan Hong,et al.  A group mobility model for ad hoc wireless networks , 1999, MSWiM '99.