PROJECT TITLE :

Exploiting Heterogeneity for Improving Forwarding Performance in Mobile Opportunistic Networks: An Analytic Approach

ABSTRACT:

Heterogeneity arises in a very big selection of situations in mobile opportunistic networks and is one amongst the key factors that govern the performance of forwarding algorithms. While the heterogeneity has been empirically investigated and exploited in the planning of new forwarding algorithms, it has been sometimes ignored or marginalized when it involves rigorous performance analysis of such algorithms. During this paper, we tend to develop an analytical framework to quantify the performance gain achievable by exploiting the heterogeneity in mobile nodes’ contact dynamics. In explicit, we have a tendency to derive a delay upper bound of a heterogeneity-aware static forwarding policy per each given range of message copies and obtain its closed-kind expression, that allows our quantitative study on the good thing about leveraging underlying heterogeneity structure in the planning of forwarding algorithms. In addition, we tend to develop a dynamic forwarding policy that performs as an extension of the static forwarding policy while proven to boost the delay performance. We tend to then demonstrate that solely a tiny fraction of total (unlimited) message copies, via each static and dynamic forwarding policies, are enough under numerous heterogeneous network settings to attain the same delay as that obtained using the unlimited message copies when the networks become homogeneous. We have a tendency to additionally show that, given the identical variety of message copies, our dynamic forwarding policy significantly outperforms the 'homogeneous-optimal’ forwarding policy (up to about fifty % improvement in the delay performance), particularly when the number of message copies allowed within the networks is tiny.