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. Our demonstration shows the energy estimation in practice on a small network of Tmote Sky motes running the Contiki operating system. A PC connected to one of the motes shows the real-time energy estimation of the network nodes and where the energy is spent: CPU active, CPU sleeping, radio transmitting, radio listening, and LEDs

Energy is of primary importance in wireless sensor networks. By being able to estimate the energy consumption of the sensor nodes, applications and routing protocols are able to make informed decisions that increase the lifetime of the sensor network. However, it is in general not possible to measure the energy consumption on popular sensor node platforms. In this paper, we present and evaluate a softwarebased on-line energy estimation mechanism that estimates the energy consumption of a sensor node. We evaluate the mechanism by comparing the estimated energy consumption with the lifetime of capacitor-powered sensor nodes. By implementing and evaluating the X-MAC protocol, we show how software-based on-line energy estimation can be used to empirically evaluate the energy efficiency of sensor network protocols.

Sensornet Protocol (SP) is a link abstraction layer between the network layer and the link layer for sensor networks. SP was proposed as the core of a future-oriented sensor node architecture that allows flexible and optimized combination between multiple coexisting protocols. This thesis implements the SP sensornet protocol on the Contiki operating system in order to: evaluate the effectiveness of the original SP services; explore further requirements and implementation trade-offs uncovered by the original proposal. We analyze the original SP design and the TinyOS implementation of SP to design the Contiki port. We implement the data sending and receiving part of SP using Contiki processes, and the neighbor management part as a group of global routines. The evaluation consists of a single-hop traffic throughput test and a multihop convergecast test. Both tests are conducted using both simulation and experimentation. We conclude from the evaluation results that SP's link-level abstraction effectively improves modularity in protocol construction without sacrificing performance, and our SP implementation on Contiki lays a good foundation for future protocol innovations in wireless sensor networks.

For designers of the communication stack of sensor nodes there is a constant tension between performance and modularity. To alleviate this tension, researchers have come up with a number of modular architectures. In this work we take a refreshed view of the design of an abstract link level service, an important component in the communication stack. We start with a critical review of one such service, the Sensornet Protocol (SP), and then we implement an SP-flavored link level service featuring a novel combination of ARQ and MAC. Experimental results of transmission delay and energy efficiency highlight a few subtle architectural design trade-offs we have encountered, namely semantics binding, implicit information sharing, and time scope initialization. These aspects have significant impact on software modularity in tiny sensor nodes.

A public key infrastructure (PKI) has been widely deployed and well tested on the Internet. However, this standard practice of delivering scalable security has not yet been extended to the rapidly growing Internet of Things (IoT). Thanks to vendor hardware support and standardization of resource-efficient communication protocols, asymmetric cryptography is no longer unfeasible on small devices. To migrate IoT from poorly scalable, pair-wise symmetric encryption to PKI, a major obstacle remains: how do we certify the public keys of billions of small devices without manual checks or complex logistics? The process of certifying a public key in form of a digital certificate is called enrollment. In this paper, we design an enrollment protocol, called Indraj, to automate enrollment of certificate-based digital identities on resource-constrained IoT devices. Reusing the semantics of the Enrollment over Secure Transport (EST) protocol designed for Internet hosts, Indraj optimizes resource usage by leveraging an IoT stack consisting of Constrained Application Protocol (CoAP), Datagram Transport Layer Security (DTLS) and IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN).We evaluate our implementation on a low power 32-bit MCU, showing the feasibility of our protocol in terms of latency, power consumption and memory usage. Asymmetric cryptography enabled by automatic certificate enrollment will finally turn IoT devices into well behaved, first-class citizens on the Internet.

Glossy networks make use of concurrent transmissions to achieve rapid network flooding in wireless networks with high reliability. They are robust against jamming and header injection attacks. We find that Glossy floods can be hijacked by a packet injection attacker to penetrate into the network and cause severe loss. We demonstrate the design of such an attacker by evaluating its effectiveness in a 30-node testbed.

In this paper we present a new kind of Denial-of-Service attack against the PHY layer of low power wireless sensor networks. Overcoming the very limited range of jamming-based attacks, this attack can penetrate deep into a target network with high power efficiency. We term this the Droplet attack, as it attains enormous disruption by dropping small, payload-less frame headers to its victim's radio receiver, depriving the latter of bandwidth and sleep time. We demonstrate the Droplet attack's high damage rate to full duty-cycle receivers, and further show that a high frequency version of Droplet can even force nodes running on very low duty-cycle MAC protocols to drop most of their packets.

Abstract—Intermediate-quality links often cause vulnerable connectivity in wireless sensor networks, but packet losses caused by such volatile links are not easy to trace. In order to equip link layer protocol designers with a reliable test and debugging tool, we develop a reactive interferer to generate packet loss patterns precisely. By using intentional interference to emulate parameterized lossy links with very low intrusiveness, our tool facilitates both robustness evaluation of protocols and flaw detection in protocol implementation.

In this position paper, we advocate the use of bus snooping to trace radio events. Highly precise and unintrusive, the technique leads to potentially more efficient code and enables more insightful protocol analysis than conventional code instrumentation techniques.

Low power wireless sensors are limited by current radio technologies to short communication range and low throughput. We envision that future radios with advanced software programmable encoding and modulation will bring sensor networks unprecedented flexibility and performance. We have taken a step towards realizing this vision by designing a softwarebased, narrow-band transceiver using the GNU Radio software and the Universal Software Radio Peripheral hardware. We have verified the compatibility of our implementation with existing wireless sensor platforms. We demonstrate the flexibility of our design with sensing applications running on a sensor network communicating over hybrid radios.

We address the problem of analysing performance anomalies in sensor networks. In this paper, we propose an approach that uses the local flash storage of the motes for logging system data, in combination with online statistical analysis. Our results show not only that this is a feasible method but that the overhead is significantly lower than that of communication-centric methods, and that interesting patterns can be revealed when calculating the correlation of large data sets of separate event types.

Link quality estimation of reliability-crucial wireless sensor networks (WSNs) is often limited by the observability and testability of single-chip radio transceivers. The estimation is often based on collection of packer-level statistics, including packet reception rate, or vendor-specific registers, such as CC2420's Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI). The speed or accuracy of such metrics limits the performance of reliability mechanisms built in wireless sensor networks. To improve link quality estimation in WSNs, we designed a powerful wireless communication monitor based on Software Defined Radio (SDR). We studied the relations between three implemented link quality metrics and packet reception rate under different channel conditions. Based on a comparison of the metrics' relative advantages, we proposed using a combination of them for fast and accurate estimation of a sensor network link.

Link quality estimation has been an important research topic in the wireless sensor networking community and researchers have developed a large number of different methods to estimate link quality. The commonly used CC2420 radio provides simple signal quality indicators. These are agile in that they react fast to changing link quality but they are inaccurate under complicated channel conditions. More sophisticated link quality estimators combine these simple metrics with packet reception statistics collected by the network stack. These approaches compensate the hardware-based metrics to a limited degree but they compromise agility and incur extra overhead. In this paper, we take a novel approach and develop a number of link quality metrics using a software defined radio. We evaluate our metrics under several channel conditions. The results show that they have good accuracy and can handle complicated channel conditions if combined properly.

The past couple of years have seen a heightened interest in the Internet of Things (IoT), transcending industry, academia and government. As with new ideas that hold immense potential, the optimism of IoT has also exaggerated the underlying technologies well before they can mature into a sustainable ecosystem. While 6LoWPAN has emerged as a disruptive technology that brings IP capability to networks of resource constrained devices, a suitable radio technology for this device class is still debatable. In the recent past, Bluetooth Low Energy (LE) - a subset of the Bluetooth v4.0 stack - has surfaced as an appealing alternative that provides a low-power and loosely coupled mechanism for sensor data collection with ubiquitous units (e.g., smartphones and tablets). When Bluetooth 4.0 was first released, it was not targeted for IP-connected devices but for communication between two neighboring peers. However, the latest release of Bluetooth 4.2 offers features that makes Bluetooth LE a competitive candidate among the available low-power communication technologies in the IoT space. In this paper, we discuss the novel features of Bluetooth LE and its applicability in 6LoWPAN networks. We also highlight important research questions and pointers for potential improvement for its greater impact.

The Internet of Things, or the IoT, is an emerging, disruptive technology that enables physical devices to communicate across disparate networks. IP has been the de facto standard for seamless interconnectivity in the traditional Internet; and piggybacking on the success of IP, 6LoWPAN has been the first standardized technology to realize it for networks of resource-constrained devices. In the recent past Bluetooth Low Energy (BLE) a.k.a Bluetooth Smart - a subset of the Bluetooth v4.0 and the latest v4.2 stack, has surfaced as an appealing alternative, with many competing advantages over available low-power communication technologies in the IoT space such as IEEE 802.15.4. However, BLE is a closed standard and lacks open hardware and firmware support, something that hinders innovation and development in this field. In this article, we aim to overcome some of the constraints in BLE's core building blocks by making three contributions: first, we present the design of a new open hardware platform for BLE; second, we provide a Contiki O.S. port for the new platform; and third, we identify research challenges and opportunities in 6LoWPAN-connected Bluetooth Smart. We believe that the knowledge and insights will facilitate IoT innovations based on this promising technology

Persistent storage offers multiple advantages for sensor networks, yet the available storage systems have been unwieldy because of their complexity and device-specific designs. We present the Coffee file system for flash-based sensor devices. Coffee provides a programming interface for building efficient and portable storage abstractions. Unlike previous flash file systems, Coffee uses a small and constant RAM footprint per file, making it scale elegantly with workloads consisting of large files or many files. In addition, the performance overhead of Coffee is low: the throughput is at least 92\% of the achievable direct flash driver throughput. We show that network layer components such as routing tables and packet queues can be implemented on top of Coffee, leading to increased performance and reduced memory requirements for routing and transport protocols.

Sensor networks enable remote monitoring of natural environments such as glaciers, volcanoes and bodies of water. Within the project 'Sensor Networks to Monitor Marine Environment with Particular Focus on Climate Changes', SICS and partners are designing and implementing flexible, reprogrammable sensor network solutions suitable for monitoring the marine environment with high resolution in time and space.

In this paper we present the design and implementation 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.

Sensor network development is notoriously difficult due to the low visibility of sensor platforms and systems. We propose sensornet checkpointing to increase the visibility of sensor networks. With sensornet checkpointing, we transfer network-wide application checkpoints between simulated and real networks. This approach enable advances in many research areas: visualization, repeatable experiments, fault injection, and application debugging. We demonstrate sensornet checkpointing on a network of Tmote Sky motes running Contiki.