Low-power wireless networks must leverage radio duty cycling to reduce energy consumption, but duty cycling drastically increases the risk of radio collisions, resulting in power-expensive retransmissions or data loss. We present Strawman, a contention resolution mechanism designed for low-power duty-cycled networks that experience traffic bursts. Strawman efficiently resolves network contention, mitigates the hidden terminal problem, and has zero overhead unless activated to resolve data collisions. Our testbed experiments show that Strawman instantaneously provides increased network capacity when needed, allocates the available bandwidth evenly among contenders, and increases energy efficiency in multi-hop collection networks compared to the traditionally used random backoff.

Standardization has driven interoperability at multiple layers of the stack, such as the routing and application layers, standardization of radio duty cycling mechanisms have not yet reached the same maturity. In this work, we pitch the two de facto standard flavors of sender-initiated radio duty cycling mechanisms against each other: ContikiMAC and TinyOS LPL. Our aim is to explore pragmatic interoperability mechanisms at the radio duty cycling layer. This will lead to better understanding of interoperability problems moving forward, as radio duty cycling mechanisms get standardized. Our results show that the two flavors can be configured to operate together but that parameter configuration may severely hurt performance.

Internet of Things devices will by and large be battery-operated, but existing application protocols have typically not been designed with power-efficiency in mind. In low-power wireless systems, power-efficiency is determined by the ability to maintain a low radio duty cycle: keeping the radio off as much as possible. We present an implementation of the IETF Constrained Application Protocol (CoAP) for the Contiki operating system that leverages the ContikiMAC low-power duty cycling mechanism to provide power efficiency. We experimentally evaluate our low-power CoAP, demonstrating that an existing application layer protocol can be made power-efficient through a generic radio duty cycling mechanism. To the best of our knowledge, our CoAP implementation is the first to provide power-efficient operation through radio duty cycling. Our results question the need for specialized low-power mechanisms at the application layer, instead providing low-power operation only at the radio duty cycling layer.

As sensor networks move towards general-purpose low-power wireless networks, there is a need to support both traditional low-data rate traffic and high-throughput transfer. To attain high throughput, existing protocols monopolize the network resources and keep the radio on for all nodes involved in the transfer, leading to poor energy efficiency. This becomes progressively problematic in networks with packet loss, which inevitably occur in any real-world deployment. We present burst forwarding, a generic packet forwarding technique that combines low power consumption with high throughput for multi-purpose wireless networks. Burst forwarding uses radio duty cycling to maintain a low power consumption, recovers efficiently from interference, and inherently supports both single streams and cross-traffic. We experimentally evaluate our mechanism under heavy interference and compare it to PIP, a state-of-the-art sensornet bulk transfer protocol. Burst forwarding gracefully adapts radio duty cycle both to the level of interference and to traffic load, keeping a low and nearly constant energy cost per byte when carrying TCP traffic.

Despite ease of deployment being seen as a primary advantage of sensor networks, deployment remains difficult. We present Snap, a system for rapid sensornet deployment that allows sensor networks to be deployed, positioned, and reprogrammed through a sensornet appstore. Snap uses a smartphone interface that uses QR codes for node identification, a map interface for node positioning, and dynamic loading of applications on the nodes. Snap nodes run the Contiki operating system and its low-power IPv6 network stack that provides direct access from nodes to the smartphone application. We demonstrate rapid sensor node deployment, identification, positioning, and node reprogramming within seconds, over a multi-hop sensornet routing path with a WiFi-connected smartphone.

Interoperability is essential for the commercial adoption of wireless sensor networks. However, existing sensor network architectures have been developed in isolation and thus interoperability has not been a concern. Recently, IP has been proposed as a solution to the interoperability problem of low-power and lossy networks (LLNs), considering its open and standards-based architecture at the network, transport, and application layers. We present two complete and interoperable implementations of the IPv6 protocol stack for LLNs, one for Contiki and one for TinyOS, and show that the cost of interoperability is low: their performance and overhead is on par with state-of-the-art protocol stacks custom built for the two platforms. At the same time, extensive testbed results show that the ensemble performance of a mixed network with nodes running the two interoperable stacks depends heavily on implementation decisions and parameters set at multiple protocol layers. In turn, these results argue that the current industry practice of interoperability testing does not cover the crucial topic of the performance and motivate the need for generic techniques that quantify the performance of such networks and configure their run-time behavior.

Interoperability is key to widespread adoption of sensor network technology, but interoperable systems have traditionally been difficult to develop and test. We demonstrate an interoperable system development and performance diagnosis environment in which different systems, different software, and different hardware can be simulated in a single network configuration. This allows both development, verification, and performance diagnosis of interoperable systems. Estimating the performance is important since even when systems interoperate, the performance can be sub-optimal, as shown in our companion paper that has been conditionally accepted for SenSys 2011.

We make the case for a sensor network model in which each mote stores sensor data locally, and provides a database query interface to the data. Unlike TinyDB and Cougar, in which a sink node provides a database-like front end for filtering the current sensor values from a data collection network, we propose that each sensor device should run its own database system. We present Antelope, a database management system for resource-constrained sensors. Antelope provides a dynamic database system that enables run-time creation and deletion of databases and indexes. Antelope uses energy-efficient indexing techniques that significantly improve the performance of queries. The energy cost of a query that selects 100 tuples is less than the cost of a single packet transmission. Moving forward, we believe that database techniques will be increasingly important in many emerging applications.

Emerging applications in industrial automation and medical care demand support for uninterrupted connectivity and reliable data transfer from mobile sensors. We present MobiSense, an energy-efficient system for reliable data transfer supporting IPv6 micro-mobility and fast handovers. We demonstrate that a two-way end-to-end IPv6 UPD session between two mobile nodes can achieve an end-to-end reliability of up to 96% while guarateeing a hand-over latency below 2 seconds.

RPL is the IETF candidate standard for IPv6 routing in low-power wireless sensor networks. We present the first experimental results of RPL which we have obtained with our ContikiRPL implementation. Our results show that Tmote Sky motes running IPv6 with RPL routing have a battery lifetime of years, while delivering 0.6 packets per second to a sink node.

We demonstrate low-power IP-based sensor networks by showing a system that interacts with the sensor network using a RESTful web service interface. The sensor data is displayed with overlaid 3D graphics on top of a live camera feed, so-called augmented reality. The augmented reality application is built with off-the-shelf components with no sensor network-specific code. The IP-based sensor network runs the Contiki operating system.

The goal of the GINSENG project is a performance-controlled sensor network suitable for applications with specific network performance requirements, such as plant automation and health monitoring. Any such sensor network must include a deterministic MAC protocol that can meet the application's targets in areas like delivery delays and reliability. We present a description and preliminary evaluation results of GinMAC, designed to be such a MAC protocol. Also included are details of a deployment to the GALP oil refinery in Sines, Portugal.

High-coverage testing of sensornet applications is vital for pre-deployment bug cleansing, but has previously been difficult due to the limited set of available tools. We integrate the KleeNet symbolic execution engine with the COOJA network simulator to allow for straight-forward and intuitive high-coverage testing initiated from a simulation environment. A tight coupling of simulation and testing helps detect, narrow down, and fix complex interaction bugs in an early development phase. We demonstrate the seamless transition between COOJA simulation and KleeNet symbolic execution. Our framework enables future research in how high coverage testing tools could be used in cooperation with simulation tools.

Power consumption is one of the most important factors in wireless sensor network research, but most simulators do not provide support for visualizing the power consumption of an entire sensor network. This makes it hard to develop, debug, and understand mechanisms and protocols based on power-saving mechanisms. We present Cooja TimeLine, an extension to Contiki's Cooja network simulator, that visualizes radio traffic and radio usage of sensor networks. Cooja TimeLine makes is possible to visually see the behavior of low-power protocols and mechanisms thereby increasing the understanding of the behavior of sensor networks. We see this as an important tool for the field moving forward.

Low-power networked devices, such as sensors and actuators, are becoming a vital part of our everyday infrastructure. Being networked, the continued development of these systems needs involvement from the networking community. We present a framework for simulation, experimentation, and evaluation of routing mechanisms for low-power IPv6 networking. The framework provides a detailed simulation environment for low-power routing mechanisms, and allows the system to be directly uploaded to a physical testbed for experimental measurements.

Power consumption is of utmost concern in sensor networks. Researchers have several ways of measuring the power consumption of a complete sensor network, but they are typically either impractical or inaccurate. To meet the need for practical and scalable measurement of power consumption of sensor networks, we have developed a cycle-accurate simulator, called COOJA/MSPsim, that enables live power estimation of systems running on MSP430 processors. This demonstration shows the ease of use and the power measurement accuracy of COOJA/MSPsim. The demo setup consists of a small sensor network and a laptop. Beside gathering software-based power measurements from the motes, the laptop runs COOJA/MSPsim to simulate the same network.We visualize the power consumption of both the simulated and the real sensor network, and show that the simulator produces matching results.

Summary form only given. Embedded systems driven by future applications will be tightly coupled with the increasing complexity of the real world. Consisting of myriads of wireless networked devices, of heterogeneous architectures, distributed and interacting in a number of ways and serving a multitude of purposes systems have to adapt and take advantage of conditions unpredictable at design time. In their realisation software both on a system and on an application level is playing an increasingly important role that cannot be designed independently. Dominant design factors are the severe resource constraints, the unreliability of the wireless medium and the dynamics of both the applications and the environment. Selected challenges in the area of wireless sensor networks are addressed.

Software in deployed sensor networks needs to be updated to introduce new functionality or to fix bugs. Reducing dissemination time is important because the dissemination disturbs the regular operation of the network. We present a method for reducing the dissemination time and energy consumption based on compression of native code modules. Code compression reduces the size of the software update, but the decompression on the sensor nodes requires processing time and energy. We quantify these trade-offs for seven different compression algorithms. Our results show that GZIP has the most favorable trade-offs, saving on average 67% of the dissemination time and 69% of the energy in a multi-hop wireless sensor network.

Space and Earth monitoring is the next step for sensor networks. Distributed systems of small sensor-equipped satellites improve the cost efficiency and the missions' performance. This abstract discusses the characteristics of satellite Wireless Sensor Networks (WSNs) and the challenges they introduce.

With emerging IPv6-based standards such as 6LowPAN and ISA100a, full IPv6 sensor networks are the next major step. With millions of deployed embedded IPv6 devices, interoperability is of major importance, both within the sensor networks and between the sensors and the Internet hosts. We present uIPv6, the first IPv6 stack for memory-constrained devices that passes all Phase-1 IPv6 Ready certification tests. This is an important step for end-to-end interoperability between IPv6 sensors and any IPv6 capable device. To allow widespread community adoption, we release uIPv6 under a permissive open source license that allows both commercial and non-commercial use.

In this paper we present the design and implemen tation of a small-scale marine sensor network. The network monitors the temperature in the Baltic Sea on different heights from the water surface down to the bottom. Unlike many other wireless sensor networks, this network contains both a wired and a wireless part. One of the major challenges is that the network is hard to access after its deployment and hence both hard- and software must be robust and reliable. We also present the design of an advanced buoy system featuring a diving unit that achieves a better vertical resolution and discuss remaining challenges of sensor networking in aquatic environments.

As sensor networks move towards increasing heterogeneity, the number of link layers, MAC protocols, and underlying transportation mechanisms increases. System developers must adapt their applications and systems to accommodate a wide range of underlying protocols and mechanisms. However, existing communication architectures for sensor networks are not designed for this heterogeneity and therefore the system developer must redevelop their systems for each underlying communication protocol or mechanism. To remedy this situation, we present a communication architecture that adapts to a wide range of underlying communication mechanisms, from the MAC layer to the transport layer, without requiring any changes to applications or protocols. We show that the architecture is expressive enough to accommodate typical sensor network protocols. Measurements show that the increase in execution time over a non-adaptive architecture is small.

Being able to estimate the energy consumption of sensor nodes is essential both for evaluating existing sensor network mechanisms and for constructing new energy-aware mechanisms. We present a software-based mechanism for estimating the energy consumption of sensor node at run-time. Unlike previous energy estimation mechanisms, our mechanism does not require any additional hardware components or add-ons.

Simulators for wireless sensor networks are a valuable tool for system development. However, current simulators can only simulate a single level of a system at once. This makes system development and evolution difficult since developers cannot use the same simulator for both high-level algorithm development and low-level development such as device-driver implementations. We propose cross-level simulation, a novel type of wireless sensor network simulation that enables holistic simultaneous simulation at different levels. We present an implementation of such a simulator, COOJA, a simulator for the Contiki sensor node operating system. COOJA allows for simultaneous simulation at the network level, the operating system level, and the machine code instruction set level. With COOJA, we show the feasibility of the cross-level simulation approach

From experience with wireless sensor networks it has become apparent that dynamic reprogramming of the sensor nodes is a useful feature. The resource constraints in terms of energy, memory, and processing power make sensor network reprogramming a challenging task. Many different mechanisms for reprogramming sensor nodes have been developed ranging from full image replacement to virtual machines.We have implemented an in-situ run-time dynamic linker and loader that use the standard ELF object file format. We show that run-time dynamic linking is an effective method for reprogramming even resource constrained wireless sensor nodes. To evaluate our dynamic linking mechanism we have implemented an application-specific virtual machine and a Java virtual machine and compare the energy cost of the different linking and execution models. We measure the energy consumption and execution time overhead on real hardware to quantify the energy costs for dynamic linkin.Our results suggest that while in general the overhead of a virtual machine is high, a combination of native code and virtual machine code provide good energy efficiency. Dynamic run-time linking can be used to update the native code, even in heterogeneous networks.

Event-driven programming is a popular model for writing programs for tiny embedded systems and sensor network nodes. While event-driven programming can keep the memory overhead down, it enforces a state machine programming style which makes many programs difficult to write, maintain, and debug. We present a novel programming abstraction called protothreads that makes it possible to write event-driven programs in a thread-like style, with a memory overhead of only two bytes per protothread. We show that protothreads significantly reduce the complexity of a number of widely used programs previously written with event-driven state machines. For the examined programs the majority of the state machines could be entirely removed. In the other cases the number of states and transitions was drastically decreased. With protothreads the number of lines of code was reduced by one third. The execution time overhead of protothreads is on the order of a few processor cycles.

Energy conservation plays a crucial in wireless sensor networks since such networks are designed to be placed in hostile and nonaccessible areas. While battery-driven sensors will run out of battery sooner or later, the use of renewable energy sources such as solar power or gravitation may extend the lifetime of a sensor network. We propose to utilize solar power in wireless sensor networks and extend LEACH a well-known cluster-based protocol for sensor networks to become solar-aware. The presented simulation results show that making LEACH solar-aware significantly extends the lifetime of sensor networks.

Wireless sensor networks are composed of large numbers of tiny networked devices that communicate untethered. For large scale networks, it is important to be able to download code into the network dynamically. We present Contiki, a lightweight operating system with support for dynamic loading and replacement of individual programs and services. Contiki is built around an event-driven kernel but provides optional preemptive multithreading that can be applied to individual processes. We show that dynamic loading and unloading is feasible in a resource constrained environment, while keeping the base system lightweight and compact.

We describe two small and portable TCP/IP implementations fulfilling the subset of RFC1122 requirements needed for full host-to-host interoperability. Our TCP/IP implementations do not sacrifice any of TCP's mechanisms such as urgent data or congestion control. They support IP fragment reassembly and the number of multiple simultaneous connections is limited only by the available RAM. Despite being small and simple, our implementations do not require their peers to have complex, full-size stacks, but can communicate with peers running a similarly light-weight stack. The code size is on the order of 10 kilobytes and RAM usage can be configured to be as low as a few hundred bytes.