1,064 research outputs found
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
Mass-Market Receiver for Static Positioning: Tests and Statistical Analyses
Nowadays, there are several low cost GPS receivers able to provide both pseudorange and carrier phase measurements in the L1band, that allow to have good realtime performances in outdoor condition. The present paper describes a set of dedicated tests in order to evaluate the positioning accuracy in static conditions. The quality of the pseudorange and the carrier phase measurements let hope for interesting results. The use of such kind of receiver could be extended to a large number of professional applications, like engineering fields: survey, georeferencing, monitoring, cadastral mapping and cadastral road. In this work, the receivers performance is verified considering a single frequency solution trying to fix the phase ambiguity, when possible. Different solutions are defined: code, float and fix solutions. In order to solve the phase ambiguities different methods are considered. Each test performed is statistically analyzed, highlighting the effects of different factors on precision and accurac
Robust and Listening-Efficient Contention Resolution
This paper shows how to achieve contention resolution on a shared
communication channel using only a small number of channel accesses -- both for
listening and sending -- and the resulting algorithm is resistant to
adversarial noise.
The shared channel operates over a sequence of synchronized time slots, and
in any slot agents may attempt to broadcast a packet. An agent's broadcast
succeeds if no other agent broadcasts during that slot. If two or more agents
broadcast in the same slot, then the broadcasts collide and both broadcasts
fail. An agent listening on the channel during a slot receives ternary
feedback, learning whether that slot had silence, a successful broadcast, or a
collision. Agents are (adversarially) injected into the system over time. The
goal is to coordinate the agents so that each is able to successfully broadcast
its packet.
A contention-resolution protocol is measured both in terms of its throughput
and the number of slots during which an agent broadcasts or listens. Most prior
work assumes that listening is free and only tries to minimize the number of
broadcasts.
This paper answers two foundational questions. First, is constant throughput
achievable when using polylogarithmic channel accesses per agent, both for
listening and broadcasting? Second, is constant throughput still achievable
when an adversary jams some slots by broadcasting noise in them? Specifically,
for packets arriving over time and jammed slots, we give an algorithm
that with high probability in guarantees throughput and
achieves on average channel accesses against an
adaptive adversary. We also have per-agent high-probability guarantees on the
number of channel accesses -- either or , depending on how quickly the adversary can react to what
is being broadcast
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