1,254 research outputs found
Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting
In a multihop wireless network, it is crucial but challenging to schedule
transmissions in an efficient and fair manner. In this paper, a novel
distributed node scheduling algorithm, called Local Voting, is proposed. This
algorithm tries to semi-equalize the load (defined as the ratio of the queue
length over the number of allocated slots) through slot reallocation based on
local information exchange. The algorithm stems from the finding that the
shortest delivery time or delay is obtained when the load is semi-equalized
throughout the network. In addition, we prove that, with Local Voting, the
network system converges asymptotically towards the optimal scheduling.
Moreover, through extensive simulations, the performance of Local Voting is
further investigated in comparison with several representative scheduling
algorithms from the literature. Simulation results show that the proposed
algorithm achieves better performance than the other distributed algorithms in
terms of average delay, maximum delay, and fairness. Despite being distributed,
the performance of Local Voting is also found to be very close to a centralized
algorithm that is deemed to have the optimal performance
A Distributed Scheduling Algorithm to Provide Quality-of-Service in Multihop Wireless Networks
Control of multihop Wireless networks in a distributed manner while providing
end-to-end delay requirements for different flows, is a challenging problem.
Using the notions of Draining Time and Discrete Review from the theory of fluid
limits of queues, an algorithm that meets delay requirements to various flows
in a network is constructed. The algorithm involves an optimization which is
implemented in a cyclic distributed manner across nodes by using the technique
of iterative gradient ascent, with minimal information exchange between nodes.
The algorithm uses time varying weights to give priority to flows. The
performance of the algorithm is studied in a network with interference modelled
by independent sets
Enabling limited traffic scheduling in asynchronous ad hoc networks
We present work-in-progress developing a communication framework that addresses the communication challenges of the decentralized multihop wireless environment. The main contribution is the combination of a fully distributed, asynchronous power save mechanism with adaptation of the timing patterns defined by the power save mechanism to improve the energy and bandwidth efficiency of communication in multihop wireless networks. The possibility of leveraging this strategy to provide more complex forms of traffic management is explored
Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems
In this paper, we consider a cognitive multi-hop relay secondary user (SU)
system sharing the spectrum with some primary users (PU). The transmit power as
well as the hop selection of the cognitive relays can be dynamically adapted
according to the local (and causal) knowledge of the instantaneous channel
state information (CSI) in the multi-hop SU system. We shall determine a low
complexity, decentralized algorithm to maximize the average end-to-end
throughput of the SU system with dynamic spatial reuse. The problem is
challenging due to the decentralized requirement as well as the causality
constraint on the knowledge of CSI. Furthermore, the problem belongs to the
class of stochastic Network Utility Maximization (NUM) problems which is quite
challenging. We exploit the time-scale difference between the PU activity and
the CSI fluctuations and decompose the problem into a master problem and
subproblems. We derive an asymptotically optimal low complexity solution using
divide-and-conquer and illustrate that significant performance gain can be
obtained through dynamic hop selection and power control. The worst case
complexity and memory requirement of the proposed algorithm is O(M^2) and
O(M^3) respectively, where is the number of SUs
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