22,316 research outputs found
Routing for Security in Networks with Adversarial Nodes
We consider the problem of secure unicast transmission between two nodes in a
directed graph, where an adversary eavesdrops/jams a subset of nodes. This
adversarial setting is in contrast to traditional ones where the adversary
controls a subset of links. In particular, we study, in the main, the class of
routing-only schemes (as opposed to those allowing coding inside the network).
Routing-only schemes usually have low implementation complexity, yet a
characterization of the rates achievable by such schemes was open prior to this
work. We first propose an LP based solution for secure communication against
eavesdropping, and show that it is information-theoretically rate-optimal among
all routing-only schemes. The idea behind our design is to balance information
flow in the network so that no subset of nodes observe "too much" information.
Interestingly, we show that the rates achieved by our routing-only scheme are
always at least as good as, and sometimes better, than those achieved by
"na\"ive" network coding schemes (i.e. the rate-optimal scheme designed for the
traditional scenario where the adversary controls links in a network rather
than nodes.) We also demonstrate non-trivial network coding schemes that
achieve rates at least as high as (and again sometimes better than) those
achieved by our routing schemes, but leave open the question of characterizing
the optimal rate-region of the problem under all possible coding schemes. We
then extend these routing-only schemes to the adversarial node-jamming
scenarios and show similar results. During the journey of our investigation, we
also develop a new technique that has the potential to derive non-trivial
bounds for general secure-communication schemes
MoMo: a group mobility model for future generation mobile wireless networks
Existing group mobility models were not designed to meet the requirements for
accurate simulation of current and future short distance wireless networks
scenarios, that need, in particular, accurate, up-to-date informa- tion on the
position of each node in the network, combined with a simple and flexible
approach to group mobility modeling. A new model for group mobility in wireless
networks, named MoMo, is proposed in this paper, based on the combination of a
memory-based individual mobility model with a flexible group behavior model.
MoMo is capable of accurately describing all mobility scenarios, from
individual mobility, in which nodes move inde- pendently one from the other, to
tight group mobility, where mobility patterns of different nodes are strictly
correlated. A new set of intrinsic properties for a mobility model is proposed
and adopted in the analysis and comparison of MoMo with existing models. Next,
MoMo is compared with existing group mobility models in a typical 5G network
scenario, in which a set of mobile nodes cooperate in the realization of a
distributed MIMO link. Results show that MoMo leads to accurate, robust and
flexible modeling of mobility of groups of nodes in discrete event simulators,
making it suitable for the performance evaluation of networking protocols and
resource allocation algorithms in the wide range of network scenarios expected
to characterize 5G networks.Comment: 25 pages, 17 figure
A Self-Organization Framework for Wireless Ad Hoc Networks as Small Worlds
Motivated by the benefits of small world networks, we propose a
self-organization framework for wireless ad hoc networks. We investigate the
use of directional beamforming for creating long-range short cuts between
nodes. Using simulation results for randomized beamforming as a guideline, we
identify crucial design issues for algorithm design. Our results show that,
while significant path length reduction is achievable, this is accompanied by
the problem of asymmetric paths between nodes. Subsequently, we propose a
distributed algorithm for small world creation that achieves path length
reduction while maintaining connectivity. We define a new centrality measure
that estimates the structural importance of nodes based on traffic flow in the
network, which is used to identify the optimum nodes for beamforming. We show,
using simulations, that this leads to significant reduction in path length
while maintaining connectivity.Comment: Submitted to IEEE Transactions on Vehicular Technolog
- …