11,294 research outputs found
Location-Quality-aware Policy Optimisation for Relay Selection in Mobile Networks
Relaying can improve the coverage and performance of wireless access
networks. In presence of a localisation system at the mobile nodes, the use of
such location estimates for relay node selection can be advantageous as such
information can be collected by access points in linear effort with respect to
number of mobile nodes (while the number of links grows quadratically).
However, the localisation error and the chosen update rate of location
information in conjunction with the mobility model affect the performance of
such location-based relay schemes; these parameters also need to be taken into
account in the design of optimal policies. This paper develops a Markov model
that can capture the joint impact of localisation errors and inaccuracies of
location information due to forwarding delays and mobility; the Markov model is
used to develop algorithms to determine optimal location-based relay policies
that take the aforementioned factors into account. The model is subsequently
used to analyse the impact of deployment parameter choices on the performance
of location-based relaying in WLAN scenarios with free-space propagation
conditions and in an measurement-based indoor office scenario.Comment: Accepted for publication in ACM/Springer Wireless Network
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
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