3,382 research outputs found
Dynamic time and power allocation for opportunistic energy efficient cooperative relay.
Exponential growth in power consumption of wireless communication devices and lack of progress in battery capacity are increasing pressure for more energy efficient (EE) wireless networks. This paper presents an algorithm for optimum EE time allocation for two cooperative relay selection schemes: opportunistic decode-and- forward (ODF) and opportunistic energy efficiency (OEE) with and without rate constraint. By dynamically optimising transmission time between source and relay it is possible to simultaneously improve EE and minimise capacity loss. Simulation in a multi-user scenario with randomly distributed number and location of cooperative nodes demonstrates the algorithm's effectiveness for improving network performance and applicability to both dynamic and static networks. Results imply a unique globally optimum time and power allocation dependent on relay position
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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