13,765 research outputs found
On the Role of Mobility for Multi-message Gossip
We consider information dissemination in a large -user wireless network in
which users wish to share a unique message with all other users. Each of
the users only has knowledge of its own contents and state information;
this corresponds to a one-sided push-only scenario. The goal is to disseminate
all messages efficiently, hopefully achieving an order-optimal spreading rate
over unicast wireless random networks. First, we show that a random-push
strategy -- where a user sends its own or a received packet at random -- is
order-wise suboptimal in a random geometric graph: specifically,
times slower than optimal spreading. It is known that this
gap can be closed if each user has "full" mobility, since this effectively
creates a complete graph. We instead consider velocity-constrained mobility
where at each time slot the user moves locally using a discrete random walk
with velocity that is much lower than full mobility. We propose a simple
two-stage dissemination strategy that alternates between individual message
flooding ("self promotion") and random gossiping. We prove that this scheme
achieves a close to optimal spreading rate (within only a logarithmic gap) as
long as the velocity is at least . The key
insight is that the mixing property introduced by the partial mobility helps
users to spread in space within a relatively short period compared to the
optimal spreading time, which macroscopically mimics message dissemination over
a complete graph.Comment: accepted to IEEE Transactions on Information Theory, 201
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Optimal Relay Selection with Non-negligible Probing Time
In this paper an optimal relay selection algorithm with non-negligible
probing time is proposed and analyzed for cooperative wireless networks. Relay
selection has been introduced to solve the degraded bandwidth efficiency
problem in cooperative communication. Yet complete information of relay
channels often remain unavailable for complex networks which renders the
optimal selection strategies impossible for transmission source without probing
the relay channels. Particularly when the number of relay candidate is large,
even though probing all relay channels guarantees the finding of the best
relays at any time instant, the degradation of bandwidth efficiency due to
non-negligible probing times, which was often neglected in past literature, is
also significant. In this work, a stopping rule based relay selection strategy
is determined for the source node to decide when to stop the probing process
and choose one of the probed relays to cooperate with under wireless channels'
stochastic uncertainties. This relay selection strategy is further shown to
have a simple threshold structure. At the meantime, full diversity order and
high bandwidth efficiency can be achieved simultaneously. Both analytical and
simulation results are provided to verify the claims.Comment: 8 pages. ICC 201
Multi-Round Contention in Wireless LANs with Multipacket Reception
Multi-packet reception (MPR) has been recognized as a powerful
capacity-enhancement technique for random-access wireless local area networks
(WLANs). As is common with all random access protocols, the wireless channel is
often under-utilized in MPR WLANs. In this paper, we propose a novel
multi-round contention random-access protocol to address this problem. This
work complements the existing random-access methods that are based on
single-round contention. In the proposed scheme, stations are given multiple
chances to contend for the channel until there are a sufficient number of
``winning" stations that can share the MPR channel for data packet
transmission. The key issue here is the identification of the optimal time to
stop the contention process and start data transmission. The solution
corresponds to finding a desired tradeoff between channel utilization and
contention overhead. In this paper, we conduct a rigorous analysis to
characterize the optimal strategy using the theory of optimal stopping. An
interesting result is that the optimal stopping strategy is a simple
threshold-based rule, which stops the contention process as soon as the total
number of winning stations exceeds a certain threshold. Compared with the
conventional single-round contention protocol, the multi-round contention
scheme significantly enhances channel utilization when the MPR capability of
the channel is small to medium. Meanwhile, the scheme automatically falls back
to single-round contention when the MPR capability is very large, in which case
the throughput penalty due to random access is already small even with
single-round contention
Analysis of Power-aware Buffering Schemes in Wireless Sensor Networks
We study the power-aware buffering problem in battery-powered sensor
networks, focusing on the fixed-size and fixed-interval buffering schemes. The
main motivation is to address the yet poorly understood size variation-induced
effect on power-aware buffering schemes. Our theoretical analysis elucidates
the fundamental differences between the fixed-size and fixed-interval buffering
schemes in the presence of data size variation. It shows that data size
variation has detrimental effects on the power expenditure of the fixed-size
buffering in general, and reveals that the size variation induced effects can
be either mitigated by a positive skewness or promoted by a negative skewness
in size distribution. By contrast, the fixed-interval buffering scheme has an
obvious advantage of being eminently immune to the data-size variation. Hence
the fixed-interval buffering scheme is a risk-averse strategy for its
robustness in a variety of operational environments. In addition, based on the
fixed-interval buffering scheme, we establish the power consumption
relationship between child nodes and parent node in a static data collection
tree, and give an in-depth analysis of the impact of child bandwidth
distribution on parent's power consumption.
This study is of practical significance: it sheds new light on the
relationship among power consumption of buffering schemes, power parameters of
radio module and memory bank, data arrival rate and data size variation,
thereby providing well-informed guidance in determining an optimal buffer size
(interval) to maximize the operational lifespan of sensor networks
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