An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Graph-Based Mobility Model for Mobile Ad Hoc Network Simulation
SS '02 Proceedings of the 35th Annual Simulation Symposium
Towards realistic mobility models for mobile ad hoc networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Recent advances in mobility modeling for mobile ad hoc network research
ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
Ad Hoc Routing Protocol Performance in a Realistic Environment
ICNICONSMCL '06 Proceedings of the International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies
Obstacle mobility model based on activity area in ad hoc networks
ICCSA'07 Proceedings of the 2007 international conference on Computational science and Its applications - Volume Part II
Real-world environment models for mobile network evaluation
IEEE Journal on Selected Areas in Communications
Performance Analysis and Improvement Content Discovery Protocols Over Vehicular Networks
Wireless Personal Communications: An International Journal
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The study of mobile Ad-hoc networks depends on understanding protocols from simulations, before being applied in a real world setting. To produce a real-world environment within which an ad hoc network can be formed among a set of nodes, there is a need for the development of a realistic, generic and comprehensive mobility model instead of random-based models. Previously, realistic mobility models such as Obstacle Mobility and Pathway Mobility Models have been proposed. In these models, there are pathways and obstacles that constrain the node movements and their signals, but they have not paid attention to movement pattern of the nodes in the pathways. In this paper, a new mobility model is proposed. It includes not only a realistic environment with obstacles and pathways but also intelligent nodes like the human beings who learn how to move in these pathways. Proposed mobility model consider variant type of the mobile node with different specification. This paper shows that various MANET environments and mobile nodes can be modeled based on this work.