Curt Schurgers

Energy-aware wireless microsensor networks

This article describes architectural and algorithmic approaches that designers can use to enhance the energy awareness of wireless sensor networks. The article starts off with an analysis of the power consumption characteristics of typical sensor node architectures and identifies the various factors that affect system lifetime. We then present a suite of techniques that perform aggressive energy optimization while targeting all stages of sensor network design, from individual nodes to the entire network. Maximizing network lifetime requires the use of a well-structured design methodology, which enables energy-aware design and operation of all aspects of the sensor network, from the underlying hardware platform to the application software and network protocols. Adopting such a holistic approach ensures that energy awareness is incorporated not only into individual sensor nodes but also into groups of communicating nodes and the entire sensor network. By following an energy-aware design methodology based on techniques such as in this article, designers can enhance network lifetime by orders of magnitude.

Energy efficient routing in wireless sensor networks

Wireless sensor nodes can be deployed on a battlefield and organize themselves in a large-scale ad-hoc network. Traditional routing protocols do not take into account that a node contains only a limited energy supply. Optimal routing tries to maximize the duration over which the sensing task can be performed, but requires future knowledge. As this is unrealistic, we derive a practical guideline based on the energy histogram and develop a spectrum of new techniques to enhance the routing in sensor networks. Our first approach aggregates packet streams in a robust way, resulting in energy reductions of a factor 2 to 3. Second, we argue that a more uniform resource utilization can be obtained by shaping the traffic flow. Several techniques, which rely only on localized metrics are proposed and evaluated. We show that they can increase the network lifetime up to an extra 90% beyond the gains of our first approach.

Optimizing sensor networks in the energy-latency-density design space

In wireless sensor networks, energy efficiency is crucial to achieving satisfactory network lifetime. To reduce the energy consumption significantly, a node should turn off its radio most of the time, except when it has to participate in data forwarding. We propose a new technique, called sparse topology and energy management (STEM), which efficiently wakes up nodes from a deep sleep state without the need for an ultra low-power radio. The designer can trade the energy efficiency of this sleep state for the latency associated with waking up the node. In addition, we integrate STEM with approaches that also leverage excess network density. We show that our hybrid wakeup scheme results in energy savings of over two orders of magnitude compared to sensor networks without topology management. Furthermore, the network designer is offered full flexibility in exploiting the energy-latency-density design space by selecting the appropriate parameter settings of our protocol.

Modulation scaling for Energy Aware Communication Systems

In systems that require low energy consumption, voltage scaling is an invaluable circuit technique. It also offers energy awareness, trading off energy and performance. In wireless handheld devices, the communication portion of the system is a major power hog. We introduce a new technique, called modulation scaling, which exhibits benefits similar to those of voltage scaling. It allows us to trade off energy against transmission delay and as such introduces the notion of energy awareness in communications. Throughout our discussion, we emphasize the analogy with voltage scaling. As an example application, we present an energy aware wireless packet scheduling system.

STEM: Topology management for energy efficient sensor networks

In wireless sensor networks, where energy efficiency is the key design challenge, the energy consumption is typically dominated by the nodes communication subsystem. It can only be reduced significantly by transitioning the embedded radio to a sleep state, at which point the node essentially retracts from the network topology. Existing topology management schemes have focused on cleverly selecting which nodes can turn off their radio, without sacrificing the capacity of the network. We propose a new technique, called sparse topology and energy management (STEM), that dramatically improves the network lifetime by exploiting the fact that most of the time, the network is only sensing its environment waiting for an event to happen. By alleviating the restriction of network capacity preservation, we can trade off extensive energy savings for an increased latency to set up a multi-hop path. We will also show how STEM integrates efficiently with existing topology management techniques.

Dynamic power management using on demand paging for networked embedded systems

The power consumption of the network interface plays a major role in determining the total operating lifetime of wireless networked embedded systems. In case of on-demand paging, a low power secondary radio is used to wake up the higher power radio, allowing the latter to sleep for longer periods of time. In this paper we present use of Bluetooth radios to serve as a paging channel for the 802.11b wireless LAN. We have implemented an on-demand paging scheme on an infrastructure based WLAN consisting of iPAQ PDAs equipped with Bluetooth radios and Cisco Aironet wireless networking cards. Our results show power saving ranging from 23% to 48% over the present 802.11b standard operating modes with negligible impact on performance.

Power management for energy-aware communication systems

System-level power management has become a key technique to render modern wireless communication devices economically viable. Despite their relatively large impact on the system energy consumption, power management for radios has been limited to shutdown-based schemes, while processors have benefited from superior techniques based on dynamic voltage scaling (DVS). However, similar scaling approaches that trade-off energy versus performance are also available for radios. To utilize these in radio power management, existing packet scheduling policies have to be thoroughly rethought to make them energy-aware, essentially opening a whole new set of challenges the same way the introduction of DVS did to CPU task scheduling. We use one specific scaling technique, dynamic modulation scaling (DMS), as a vehicle to outline these challenges, and to introduce the intricacies caused by the nonpreemptive nature of packet scheduling and the time-varying wireless channel.

Adaptive link layer strategies for energy efficient wireless networking

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.

Sensor networks of freely drifting autonomous underwater explorers

With the increasing sophistication of both manned and unmanned systems for remote ocean exploration, a wealth of knowledge about heretofore-unknown oceanic processes has become available. However, no technologies currently exist to observe organisms and processes without disturbing them, as they move with the natural motion of the oceans. We propose a new class of ocean sensing, whereby free-floating underwater devices operate autonomously and collaborate through an acoustic underwater network between them. This new class of sensing will provide a window into understanding the multifaceted interactions between the oceans currents, underwater ecosystems and our impact on them. In this paper, we will present the design of our underwater vehicle, which drifts freely with the ocean currents and is equipped with a buoyancy control piston. Results from sea tests illustrate the feasibility of our design, including its depth tracking abilities.

Modulation scaling for real-time energy aware packet scheduling

Portable wireless communication systems operate on a limited battery supply, and energy efficiency is therefore crucial. Voltage scaling techniques have been proposed to lower the energy consumption of embedded processors and real-time operating systems have incorporated these schemes in their task scheduling engine. However, the actual data transmission itself constitutes a major portion of the total energy consumption in these wireless communication systems. In this paper, we extend the scaling notion to the realm of wireless communications and propose a novel technique called modulation scaling to decrease the energy consumed during data transmission. Modulation scaling trades off energy consumption against transmission delay and as such, introduces the concept of energy awareness in communications. We investigate how modulation scaling can be exploited to design a dynamic power management engine at the level of the radio. This engine coordinates the packet transmission schedule while optimizing energy efficiency. We demonstrate such a power management module for real-time traffic and show that it reduces the energy consumption of data transmissions by up to 50 % through smart traffic scheduling.