A Random Group Mobility Model for Mobile Networks

Author(s):  
Lai Tu ◽  
Fan Zhang ◽  
Furong Wang ◽  
Xinmei Wang
2021 ◽  
Author(s):  
Sureshkumar A ◽  
Surendran D

Abstract Nowadays, a massive amount of data leads to cause network traffic and inflexible mobility in future mobile networks. A new Group Mobility Model (GMM) named MoMo is introduced that addresses the issue of the aforementioned problems. Even though, software defined network (SDN) is functional with network-rooted mobility protocols that enhance the network efficiency. Some existing network-rooted mobility administration methods still undergo handover delay, packet loss, and high signaling cost through handover processing. In this research work, SDN-based fast handover for GMM is proposed. Here, the neighbor number of evolving node transition probabilities of the mobile node (MN) and their obtainable resource probabilities are estimated. This makes a mathematical framework to decide the preeminent number of the evolving nodes and then allot these to mobile nodes virtually with all associations finished by the exploit of Open-Flow tables. The performance examination demonstrates that the proposed SDN rooted GMM technique has the enhanced performance than the conventional handover process and further technique by handover latency, signaling cost, network throughput, and packet loss.


2021 ◽  
Author(s):  
Yusi Chen ◽  
Ying Lu ◽  
Jin Liu ◽  
Qi Guo ◽  
Nierui Fan ◽  
...  

Author(s):  
Tobias Hoßfeld ◽  
Michael Duelli ◽  
Dirk Staehle ◽  
Phuoc Tran-Gia

The performance of P2P content distribution in cellular networks depends highly on the cooperation and coordination of heterogeneous and often selfish mobile users. The major challenges are the identification of problems arising specifically in cellular mobile networks and the development of new cooperation strategies to overcome these problems. In the coherent previous chapter, the authors focused on the selfishness of users in such heterogeneous environments. This discussion is now extended by emphasizing the impact of mobility and vertical handover between different wireless access technologies. An abstract mobility model is required to allow the performance evaluation in feasible computational time. As a result, the performance in today’s and future cellular networks is predicted and new approaches to master heterogeneity in cellular networks are derived.


Author(s):  
Alexander P Pelov ◽  
Thomas Noel

This paper presents the generic layered architecture for mobility models (LEMMA), which can be used to construct a wide variety of mobility models, including the majority of models used in wireless network simulations. The fundamental components of the architecture are described and analyzed, in addition to its benefits. One of the core principles stipulates that each mobility model is divided in five distinct layers that communicate via interfaces. This allows their easy replacement and recombination, which we support by reviewing 19 layers that can form 480 different mobility models. Some of the advanced features provided by the architecture are also discussed, such as layer aggregation, and creation of hybrid and group mobility models. Finally, some of the numerous existing studies of the different layers are presented.


2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Jiaxu Chen ◽  
Yazhe Tang ◽  
Chengchen Hu ◽  
Guijuan Wang

Human mobility modeling has increasingly drawn the attention of researchers working on wireless mobile networks such as delay tolerant networks (DTNs) in the last few years. So far, a number of human mobility models have been proposed to reproduce people’s social relationships, which strongly affect people’s daily life movement behaviors. However, most of them are based on the granularity of community. This paper presents interest-oriented human contacts (IHC) mobility model, which can reproduce social relationships on a pairwise granularity. As well, IHC provides two methods to generate input parameters (interest vectors) based on the social interaction matrix of target scenarios. By comparing synthetic data generated by IHC with three different real traces, we validate our model as a good approximation for human mobility. Exhaustive experiments are also conducted to show that IHC can predict well the performance of routing protocols.


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