Adaptive link layer strategies for energy efficient wireless networking

Abstract

Low power consumption is a key design metric for portable wireless network devices where battery energy is a limited resource. The resultant energy efficient design problem can be addressed at various levels of system design, and indeed much research has been done for hardware power optimization and power management within a wireless device. However, with the increasing trend towards thin client type wireless devices that rely more and more on network based services, a high fraction of power consumption is being accounted for by the transport of packet data over wireless links [28]. This offers an opportunity to optimize for low power in higher layer network protocols responsible for data communication among multiple wireless devices. Consider the data link protocols that transport bits across the wireless link. While traditionally designed around the conventional metrics of throughput and latency, a proper design offers many opportunities for optimizing the metric most relevant to battery operated devices: the amount of battery energy consumed per useful user level bit transmitted across the wireless link. This includes energy spent in the physical radio transmission process, as well as in computation such as signal processing and error coding. This paper describes how energy efficiency in the wireless data link can be enhanced via adaptive frame length control in concert with adaptive error control based on hybrid FEC (forward error correction) and ARQ (automatic repeat request). Key to this approach is a high degree of adaptivity. The length and error coding of the atomic data unit (frame) going over the air, and the retransmission protocol are (a) selected for each application stream (ATM virtual circuit or IP/RSVP flow) based on quality of service (QoS) requirements, and (b) continually adapted as a function of varying radio channel conditions due to fading and other impairments. We present analysis and simulation results on the battery energy efficiency achieved for user traffic of different QoS requirements, and describe hardware and software implementations.