12,560 research outputs found
Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
We consider a wireless network with a base station serving multiple traffic
streams to different destinations. Packets from each stream arrive to the base
station according to a stochastic process and are enqueued in a separate (per
stream) queue. The queueing discipline controls which packet within each queue
is available for transmission. The base station decides, at every time t, which
stream to serve to the corresponding destination. The goal of scheduling
decisions is to keep the information at the destinations fresh. Information
freshness is captured by the Age of Information (AoI) metric.
In this paper, we derive a lower bound on the AoI performance achievable by
any given network operating under any queueing discipline. Then, we consider
three common queueing disciplines and develop both an Optimal Stationary
Randomized policy and a Max-Weight policy under each discipline. Our approach
allows us to evaluate the combined impact of the stochastic arrivals, queueing
discipline and scheduling policy on AoI. We evaluate the AoI performance both
analytically and using simulations. Numerical results show that the performance
of the Max-Weight policy is close to the analytical lower bound
Minimizing Age-of-Information with Throughput Requirements in Multi-Path Network Communication
We consider the scenario where a sender periodically sends a batch of data to
a receiver over a multi-hop network, possibly using multiple paths. Our
objective is to minimize peak/average Age-of-Information (AoI) subject to
throughput requirements. The consideration of batch generation and multi-path
communication differentiates our AoI study from existing ones. We first show
that our AoI minimization problems are NP-hard, but only in the weak sense, as
we develop an optimal algorithm with a pseudo-polynomial time complexity. We
then prove that minimizing AoI and minimizing maximum delay are "roughly"
equivalent, in the sense that any optimal solution of the latter is an
approximate solution of the former with bounded optimality loss. We leverage
this understanding to design a general approximation framework for our
problems. It can build upon any -approximation algorithm of the maximum
delay minimization problem, to construct an -approximate solution
for minimizing AoI. Here is a constant depending on the throughput
requirements. Simulations over various network topologies validate the
effectiveness of our approach.Comment: Accepted by the ACM Twentieth International Symposium on Mobile Ad
Hoc Networking and Computing (ACM MobiHoc 2019
An Upper Bound on Multi-hop Transmission Capacity with Dynamic Routing Selection
This paper develops upper bounds on the end-to-end transmission capacity of
multi-hop wireless networks. Potential source-destination paths are dynamically
selected from a pool of randomly located relays, from which a closed-form lower
bound on the outage probability is derived in terms of the expected number of
potential paths. This is in turn used to provide an upper bound on the number
of successful transmissions that can occur per unit area, which is known as the
transmission capacity. The upper bound results from assuming independence among
the potential paths, and can be viewed as the maximum diversity case. A useful
aspect of the upper bound is its simple form for an arbitrary-sized network,
which allows insights into how the number of hops and other network parameters
affect spatial throughput in the non-asymptotic regime. The outage probability
analysis is then extended to account for retransmissions with a maximum number
of allowed attempts. In contrast to prevailing wisdom, we show that
predetermined routing (such as nearest-neighbor) is suboptimal, since more hops
are not useful once the network is interference-limited. Our results also make
clear that randomness in the location of relay sets and dynamically varying
channel states is helpful in obtaining higher aggregate throughput, and that
dynamic route selection should be used to exploit path diversity.Comment: 14 pages, 5 figures, accepted to IEEE Transactions on Information
Theory, 201
QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts
Large inter-datacenter transfers are crucial for cloud service efficiency and
are increasingly used by organizations that have dedicated wide area networks
between datacenters. A recent work uses multicast forwarding trees to reduce
the bandwidth needs and improve completion times of point-to-multipoint
transfers. Using a single forwarding tree per transfer, however, leads to poor
performance because the slowest receiver dictates the completion time for all
receivers. Using multiple forwarding trees per transfer alleviates this
concern--the average receiver could finish early; however, if done naively,
bandwidth usage would also increase and it is apriori unclear how best to
partition receivers, how to construct the multiple trees and how to determine
the rate and schedule of flows on these trees. This paper presents QuickCast, a
first solution to these problems. Using simulations on real-world network
topologies, we see that QuickCast can speed up the average receiver's
completion time by as much as while only using more
bandwidth; further, the completion time for all receivers also improves by as
much as faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018,
Honolulu, H
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