PAMAS—power aware multi-access protocol with signalling for ad hoc networks
ACM SIGCOMM Computer Communication Review
Dynamic Power Management in Wireless Sensor Networks
IEEE Design & Test
A Performance Comparison of Energy Consumption for Mobile Ad Hoc Network Routing Protocols
MASCOTS '00 Proceedings of the 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Design and Implementation of a Calibrated Store and Forward Imaging System for Teledermatology
Journal of Medical Systems
Wireless sensor networks: Enabling technology for ambient intelligence
Microelectronics Journal
Multi-modal emotive computing in a smart house environment
Pervasive and Mobile Computing
A survey on power control issues in wireless sensor networks
IEEE Communications Surveys & Tutorials
Prolonging the lifetime of wireless sensor networks by cross-layer interaction
IEEE Wireless Communications
Joint scheduling and power control for wireless ad hoc networks
IEEE Transactions on Wireless Communications
The capacity of wireless networks
IEEE Transactions on Information Theory
IEEE Communications Magazine
Balancing energy consumption with mobile agents in wireless sensor networks
Future Generation Computer Systems
Energy equilibrium based on corona structure for wireless sensor networks
Wireless Communications & Mobile Computing
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Power control is an important research topic for ad-hoc Wireless Sensor Networks (WSNs). In today's sophisticated and competitive wireless environment, the control of the energy consumption in a WSN for homecare e-health makes it possible to guarantee basic levels of system performance, such as connectivity, throughput, delay, QoS and survivability in the presence of both mobility-immobility and a large number of sensor nodes. Recent advances in sensor fabrication technology, low-power digital and analogue electronics, and low-power wireless communication systems have made it possible to develop low-cost, robust and survivable WSNs to support activities such as assisted living and ambient intelligence (Aml). A large variety of approaches for intelligent energy-efficient schemes have been simulated over different performance metrics. In this paper, various decision support schemes are proposed evaluating the selection of different network infrastructures in terms of routing optimization and signal strength selection.