2,797 research outputs found
Parallel Opportunistic Routing in Wireless Networks
We study benefits of opportunistic routing in a large wireless ad hoc network
by examining how the power, delay, and total throughput scale as the number of
source- destination pairs increases up to the operating maximum. Our
opportunistic routing is novel in a sense that it is massively parallel, i.e.,
it is performed by many nodes simultaneously to maximize the opportunistic gain
while controlling the inter-user interference. The scaling behavior of
conventional multi-hop transmission that does not employ opportunistic routing
is also examined for comparison. Our results indicate that our opportunistic
routing can exhibit a net improvement in overall power--delay trade-off over
the conventional routing by providing up to a logarithmic boost in the scaling
law. Such a gain is possible since the receivers can tolerate more interference
due to the increased received signal power provided by the multi-user diversity
gain, which means that having more simultaneous transmissions is possible.Comment: 18 pages, 7 figures, Under Review for Possible Publication in IEEE
Transactions on Information Theor
Achievable Rate and Optimal Physical Layer Rate Allocation in Interference-Free Wireless Networks
We analyze the achievable rate in interference-free wireless networks with
physical layer fading channels and orthogonal multiple access. As a starting
point, the point-to-point channel is considered. We find the optimal physical
and network layer rate trade-off which maximizes the achievable overall rate
for both a fixed rate transmission scheme and an improved scheme based on
multiple virtual users and superposition coding. These initial results are
extended to the network setting, where, based on a cut-set formulation, the
achievable rate at each node and its upper bound are derived. We propose a
distributed optimization algorithm which allows to jointly determine the
maximum achievable rate, the optimal physical layer rates on each network link,
and an opportunistic back-pressure-type routing strategy on the network layer.
This inherently justifies the layered architecture in existing wireless
networks. Finally, we show that the proposed layered optimization approach can
achieve almost all of the ergodic network capacity in high SNR.Comment: 5 pages, to appear in Proc. IEEE ISIT, July 200
Flow Allocation for Maximum Throughput and Bounded Delay on Multiple Disjoint Paths for Random Access Wireless Multihop Networks
In this paper, we consider random access, wireless, multi-hop networks, with
multi-packet reception capabilities, where multiple flows are forwarded to the
gateways through node disjoint paths. We explore the issue of allocating flow
on multiple paths, exhibiting both intra- and inter-path interference, in order
to maximize average aggregate flow throughput (AAT) and also provide bounded
packet delay. A distributed flow allocation scheme is proposed where allocation
of flow on paths is formulated as an optimization problem. Through an
illustrative topology it is shown that the corresponding problem is non-convex.
Furthermore, a simple, but accurate model is employed for the average aggregate
throughput achieved by all flows, that captures both intra- and inter-path
interference through the SINR model. The proposed scheme is evaluated through
Ns2 simulations of several random wireless scenarios. Simulation results reveal
that, the model employed, accurately captures the AAT observed in the simulated
scenarios, even when the assumption of saturated queues is removed. Simulation
results also show that the proposed scheme achieves significantly higher AAT,
for the vast majority of the wireless scenarios explored, than the following
flow allocation schemes: one that assigns flows on paths on a round-robin
fashion, one that optimally utilizes the best path only, and another one that
assigns the maximum possible flow on each path. Finally, a variant of the
proposed scheme is explored, where interference for each link is approximated
by considering its dominant interfering nodes only.Comment: IEEE Transactions on Vehicular Technolog
Proactive Highly Ambulatory Sensor Routing (PHASeR) protocol for mobile wireless sensor networks
This paper presents a novel multihop routing protocol for mobile wireless sensor networks called PHASeR (Proactive Highly Ambulatory Sensor Routing). The proposed protocol
uses a simple hop-count metric to enable the dynamic and robust routing of data towards the sink in mobile environments. It is motivated by the application of radiation mapping by unmanned vehicles, which requires the reliable and timely delivery of regular measurements to the sink. PHASeR maintains a gradient metric in mobile environments by using a global TDMA MAC layer. It also uses the technique of blind forwarding to pass messages through the network in a multipath manner. PHASeR is analysed mathematically based on packet delivery ratio, average packet delay, throughput and overhead. It is then simulated with varying mobility, scalability and traffic loads. The protocol gives good results over all measures, which suggests that it may also be suitable for a wider array of emerging applications
On the feasibility of monitoring DTN: Impacts of fine tuning on routing protocols and the user experience
The “machine to machine” communication paradigm will become a central element for mobile networks. This paradigm can be easily constructed by a contact-based network, notably a disruption/delay tolerant networks (DTN). To characterize a DTN, we can use the Inter-contact time among the nodes. The better understanding of inter-contact time (ICT) has practical applications on the tuning of forwarding strategies, and hence in the quality of the User Experience. Nevertheless, the fine tuning of those parameters is tight to a set of assumptions about the regularity of movement or periodicity of patterns in an usually non complete and cumbersome statistical analysis. That is why in a dynamic environment where we cannot assume any previous information the tuning of parameters is usually overestimated. In this work we study how monitoring can help to adapt those parameters to give a better understanding of both natural evolution of the network and non periodical events
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