5,999 research outputs found
Optimal scheduling of real-time traffic in wireless networks with delayed feedback
In this paper we consider a wireless network composed of a base station and a number of clients, with the goal of scheduling real-time traffic. Even though this problem has been extensively studied in the literature, the impact of delayed acknowledgment has not been assessed. Delayed feedback is of increasing importance in systems where the round trip delay is much greater than the packet transmission time, and it has a significant effect on the scheduling decisions and network performance. Previous work considered the problem of scheduling real-time traffic with instantaneous feedback and without feedback. In this work, we address the general case of delayed feedback and use Dynamic Programming to characterize the optimal scheduling policy. An optimal algorithm that fulfills any feasible minimum delivery ratio requirements is proposed. Moreover, we develop a low-complexity suboptimal heuristic algorithm which is suitable for platforms with low computational power. Both algorithms are evaluated through simulations.National Science Foundation (U.S.) (CNS-1217048)United States. Office of Naval Research (Grant N00014-12-1-00640Coordenação de Aperfeiçoamento de Pessoal de Nível Superio
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Closing feedback loops fast and over long distances is key to emerging
applications; for example, robot motion control and swarm coordination require
update intervals of tens of milliseconds. Low-power wireless technology is
preferred for its low cost, small form factor, and flexibility, especially if
the devices support multi-hop communication. So far, however, feedback control
over wireless multi-hop networks has only been shown for update intervals on
the order of seconds. This paper presents a wireless embedded system that tames
imperfections impairing control performance (e.g., jitter and message loss),
and a control design that exploits the essential properties of this system to
provably guarantee closed-loop stability for physical processes with linear
time-invariant dynamics. Using experiments on a cyber-physical testbed with 20
wireless nodes and multiple cart-pole systems, we are the first to demonstrate
and evaluate feedback control and coordination over wireless multi-hop networks
for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International
Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19),
April 16--18, 2019, Montreal, QC, Canad
Adaptive Network Coding for Scheduling Real-time Traffic with Hard Deadlines
We study adaptive network coding (NC) for scheduling real-time traffic over a
single-hop wireless network. To meet the hard deadlines of real-time traffic,
it is critical to strike a balance between maximizing the throughput and
minimizing the risk that the entire block of coded packets may not be decodable
by the deadline. Thus motivated, we explore adaptive NC, where the block size
is adapted based on the remaining time to the deadline, by casting this
sequential block size adaptation problem as a finite-horizon Markov decision
process. One interesting finding is that the optimal block size and its
corresponding action space monotonically decrease as the deadline approaches,
and the optimal block size is bounded by the "greedy" block size. These unique
structures make it possible to narrow down the search space of dynamic
programming, building on which we develop a monotonicity-based backward
induction algorithm (MBIA) that can solve for the optimal block size in
polynomial time. Since channel erasure probabilities would be time-varying in a
mobile network, we further develop a joint real-time scheduling and channel
learning scheme with adaptive NC that can adapt to channel dynamics. We also
generalize the analysis to multiple flows with hard deadlines and long-term
delivery ratio constraints, devise a low-complexity online scheduling algorithm
integrated with the MBIA, and then establish its asymptotical
throughput-optimality. In addition to analysis and simulation results, we
perform high fidelity wireless emulation tests with real radio transmissions to
demonstrate the feasibility of the MBIA in finding the optimal block size in
real time.Comment: 11 pages, 13 figure
Providing End-to-End Delay Guarantees for Multi-hop Wireless Sensor Networks over Unreliable Channels
Wireless sensor networks have been increasingly used for real-time
surveillance over large areas. In such applications, it is important to support
end-to-end delay constraints for packet deliveries even when the corresponding
flows require multi-hop transmissions. In addition to delay constraints, each
flow of real-time surveillance may require some guarantees on throughput of
packets that meet the delay constraints. Further, as wireless sensor networks
are usually deployed in challenging environments, it is important to
specifically consider the effects of unreliable wireless transmissions.
In this paper, we study the problem of providing end-to-end delay guarantees
for multi-hop wireless networks. We propose a model that jointly considers the
end-to-end delay constraints and throughput requirements of flows, the need for
multi-hop transmissions, and the unreliable nature of wireless transmissions.
We develop a framework for designing feasibility-optimal policies. We then
demonstrate the utility of this framework by considering two types of systems:
one where sensors are equipped with full-duplex radios, and the other where
sensors are equipped with half-duplex radios. When sensors are equipped with
full-duplex radios, we propose an online distributed scheduling policy and
proves the policy is feasibility-optimal. We also provide a heuristic for
systems where sensors are equipped with half-duplex radios. We show that this
heuristic is still feasibility-optimal for some topologies
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