3,231 research outputs found
On the Catalyzing Effect of Randomness on the Per-Flow Throughput in Wireless Networks
This paper investigates the throughput capacity of a flow crossing a
multi-hop wireless network, whose geometry is characterized by general
randomness laws including Uniform, Poisson, Heavy-Tailed distributions for both
the nodes' densities and the number of hops. The key contribution is to
demonstrate \textit{how} the \textit{per-flow throughput} depends on the
distribution of 1) the number of nodes inside hops' interference sets, 2)
the number of hops , and 3) the degree of spatial correlations. The
randomness in both 's and is advantageous, i.e., it can yield larger
scalings (as large as ) than in non-random settings. An interesting
consequence is that the per-flow capacity can exhibit the opposite behavior to
the network capacity, which was shown to suffer from a logarithmic decrease in
the presence of randomness. In turn, spatial correlations along the end-to-end
path are detrimental by a logarithmic term
Restricted Mobility Improves Delay-Throughput Trade-offs in Mobile Ad-Hoc Networks
In this paper we revisit two classes of mobility models which are widely used to repre-sent users ’ mobility in wireless networks: Random Waypoint (RWP) and Random Direction (RD). For both models we obtain systems of partial differential equations which describe the evolution of the users ’ distribution. For the RD model, we show how the equations can be solved analytically both in the stationary and transient regime adopting standard mathematical techniques. Our main contributions are i) simple expressions which relate the transient dura-tion to the model parameters; ii) the definition of a generalized random direction model whose stationary distribution of mobiles in the physical space corresponds to an assigned distribution
Towards a Simple Relationship to Estimate the Capacity of Static and Mobile Wireless Networks
Extensive research has been done on studying the capacity of wireless
multi-hop networks. These efforts have led to many sophisticated and customized
analytical studies on the capacity of particular networks. While most of the
analyses are intellectually challenging, they lack universal properties that
can be extended to study the capacity of a different network. In this paper, we
sift through various capacity-impacting parameters and present a simple
relationship that can be used to estimate the capacity of both static and
mobile networks. Specifically, we show that the network capacity is determined
by the average number of simultaneous transmissions, the link capacity and the
average number of transmissions required to deliver a packet to its
destination. Our result is valid for both finite networks and asymptotically
infinite networks. We then use this result to explain and better understand the
insights of some existing results on the capacity of static networks, mobile
networks and hybrid networks and the multicast capacity. The capacity analysis
using the aforementioned relationship often becomes simpler. The relationship
can be used as a powerful tool to estimate the capacity of different networks.
Our work makes important contributions towards developing a generic methodology
for network capacity analysis that is applicable to a variety of different
scenarios.Comment: accepted to appear in IEEE Transactions on Wireless Communication
Towards a System Theoretic Approach to Wireless Network Capacity in Finite Time and Space
In asymptotic regimes, both in time and space (network size), the derivation
of network capacity results is grossly simplified by brushing aside queueing
behavior in non-Jackson networks. This simplifying double-limit model, however,
lends itself to conservative numerical results in finite regimes. To properly
account for queueing behavior beyond a simple calculus based on average rates,
we advocate a system theoretic methodology for the capacity problem in finite
time and space regimes. This methodology also accounts for spatial correlations
arising in networks with CSMA/CA scheduling and it delivers rigorous
closed-form capacity results in terms of probability distributions. Unlike
numerous existing asymptotic results, subject to anecdotal practical concerns,
our transient one can be used in practical settings: for example, to compute
the time scales at which multi-hop routing is more advantageous than single-hop
routing
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