1,900 research outputs found
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
Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks
In this paper, we consider the joint opportunistic routing and channel
assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks
(CRNs) for improving aggregate throughput of the secondary users. We first
present the nonlinear programming optimization model for this joint problem,
taking into account the feature of CRNs-channel uncertainty. Then considering
the queue state of a node, we propose a new scheme to select proper forwarding
candidates for opportunistic routing. Furthermore, a new algorithm for
calculating the forwarding probability of any packet at a node is proposed,
which is used to calculate how many packets a forwarder should send, so that
the duplicate transmission can be reduced compared with MAC-independent
opportunistic routing & encoding (MORE) [11]. Our numerical results show that
the proposed scheme performs significantly better that traditional routing and
opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201
An Extended Network Coding Opportunity Discovery Scheme in Wireless Networks
Network coding is known as a promising approach to improve wireless network
performance. How to discover the coding opportunity in relay nodes is really
important for it. There are more coding chances, there are more times it can
improve network throughput by network coding operation. In this paper, an
extended network coding opportunity discovery scheme (ExCODE) is proposed,
which is realized by appending the current node ID and all its 1-hop neighbors'
IDs to the packet. ExCODE enables the next hop relay node to know which nodes
else have already overheard the packet, so it can discover the potential coding
opportunities as much as possible. ExCODE expands the region of discovering
coding chance to n-hops, and have more opportunities to execute network coding
operation in each relay node. At last, we implement ExCODE over the AODV
protocol, and efficiency of the proposed mechanism is demonstrated with NS2
simulations, compared to the existing coding opportunity discovery scheme.Comment: 15 pages and 7 figure
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