Power Adaptation Based Optimization for Energy Efficient Reliable Wireless Paths

Abstract

Abstract. We define a transmission power adaptation-based routing technique that finds optimal paths for minimum energy reliable data transfer in multi-hop wireless networks. This optimal choice of the transmission power depends on the link distance between the two nodes and the channel characteristics. Typical energy efficient routing techniques use a transmission power such that the received signal power at the destination minimally exceeds a desired threshold signal strength level. In this paper we argue that such a choice of the transmission power does not always lead to optimal energy routes, since it does not consider differences in the receiver noise levels. We first analyze the optimal transmission power choices for both the ideal case from an information-theoretic perspective, and for realistic modulation schemes. Subsequently we define our technique for transmission power adaptation that can be used in existing routing protocols for multi-hop wireless networks. Our simulations show that current best-known schemes incur upto 10% more energy costs in low noise environments, and upto 6.67 times the energy costs in high noise environments compared to our proposed scheme.

Trade-off between Reliability and Energy Cost for Content-Rich Data Transmission in Wireless Sensor Networks

“…For energy-efficient and reliable communication in multi-hop networks, Banerjee and Misra proposed a link cost that is a function of both the energy required for transmission and the link error rate [3]. Based on this link cost, they proposed a scheme for power control that estimates the optimal transmission power using the link distance and the channel characteristics [4]. A major drawback of all power control mechanisms is that they require a multipower-level radio, which is a luxury that can not be afforded by regular sensor nodes.…”

System level energy management in networked real-time embedded systems

“…Current state-of-the art embedded devices support a variety of power management techniques which can be exploited by the higher layer protocols for effective energy management. These techniques include: sleep-wakeup [60,61], power adaptation [62,63] and performance scaling [64]. In this chapter we focus on performance scaling.…”

The Implementation of an Energy Balanced Routing Protocol with Dynamic Power Scaling in TinyOS

“…The problem of this approach is that the selected shortest path might not be a minimum energy cost route. Some other works concentrate on decreasing the energy consumption by replacing the hop-count routing with minimum energy routing [3]. They compute a minimum-energy path for packet delivery in a multi-hop wireless network.…”