Bluetooth is an omnipresent technology, available on billions of devices today. While it has been traditionally limited to peer-to-peer communication and star networks, the recent Bluetooth Mesh standard extends it to multi-hop networking. In addition, the Bluetooth 5 standard introduces new modes to allow for increased reliability. In this article, we evaluate the feasibility of concurrent transmissions (CT) in Bluetooth via modeling and controlled experiments and then devise an efficient network-wide data dissemination protocol, BlueFlood, based on CT for multi-hop Bluetooth networks. First, we model and analyze how CT distorts the received waveform and characterize the Bit Error Rate of a Frequency-Shift Keying receiver to show that CT is feasible over Bluetooth. Second, we verify our analytic results with a controlled experimental study of CT over Bluetooth PHY. Third, we present BlueFlood, a fast and efficient network-wide data dissemination in multi-hop Bluetooth networks. In our experimental evaluation, in two testbeds deployed in university buildings, we show that BlueFlood achieves 99.9% end-to-end delivery ratio with a duty-cycle of 0.4% for periodic dissemination of advertising packets of 38 bytes with 200 milliseconds intervals at 2 Mbps. Moreover, we show that BlueFlood can be received by off-the-shelf devices such as smartphones, paving a seamless integration with existing technologies.

Massive deployment of diverse ultra-low power wireless devices in different application areas has given rise to a plethora of heterogeneous architectures and communication protocols. It is challenging to provide convergent access to these miscellaneous collections of communicating devices. In this paper, we propose VGATE, an edge-based virtualized IoT gateway for bringing these devices together in a single framework using SDRs as technology agnostic radioheads. SDR platforms, however, suffer from large unpredictable delays. We design a GNU Radio-based IEEE 802.15.4 experimental setup using LimeSDR, where the data path is time-stamped at various points of interest to get a comprehensive understanding of the characteristics of the delays. Our analysis shows that GNU Radio processing and LimeSDR buffering delays are the major delays. We decrease the LimeSDR buffering delay by decreasing the USB transfer size but show that this comes at the cost of increased processing overhead. We modify the USB transfer packet size to investigate which USB transfer size provides the best balance between buffering delay and processing overhead across two different host computers. Our experiments show that for the best measured configuration the mean and jitter of latency decreases by 37% and 40% respectively for the host computer with higher processing resources. We also show that the throughput is not affected by these modifications.

In this paper, we address the support of Time-Slotted Channel Hopping (TSCH) on multiple frequency bands within a single TSCH network. This allows to simultaneously run applications with different requirements on link characteristics and to increase resilience against interference. To this end, we first enable sub-GHz communication in TSCH, which has been primarily defined for the 2.4 GHz band. Thereafter, we propose two designs to support multiple physical layers in TSCH on the same nodes. Our experimental evaluation shows that TSCH is applicable in a wide range of data rates between 1.2 kbps and 1000 kbps. We find that data rates of 50 kbps and below have a long communication range and a nearly perfect link symmetry, but also have a 20x higher channel utilization compared to higher data rates, increasing the risk of collisions. Using these findings, we show the advantages of the multi-band support on the example of synchronization accuracy when exchanging TSCH beacons with a low data rate and application data at a high data rate.

Networks deployed in real-world conditions have to cope with dynamic, unpredictable environmental temperature changes. These changes affect the clock rate on network nodes, and can cause faster clock de-synchronization compared to situations where devices are operating under stable temperature conditions. Wireless network protocols, such as time-slotted channel hopping (TSCH) from the IEEE 802.15.4-2015 standard, are affected by this problem, since they require tight clock synchronization among all nodes for the network to remain operational. This paper proposes a method for autonomously compensating temperature-dependent clock rate changes. After a calibration stage, nodes continuously perform temperature measurements to compensate for clock drifts at runtime. The method is implemented on low-power Internet of Things (IoT) nodes and evaluated through experiments in a temperature chamber, indoor and outdoor environments, as well as with numerical simulations. The results show that applying the method reduces the maximum synchronization error more than ten times. In this way, the method allows reduction in the total energy spent for time synchronization, which is practically relevant concern for low data rate, low energy budget TSCH networks, especially those exposed to environments with changing temperature.

Synchronized communication has recently emerged as a prime option for low-power critical applications. Solutions such as Glossy or Time Slotted Channel Hopping (TSCH) have demonstrated end-to-end reliability upwards of 99.99%. In this context, the IETF Working Group 6TiSCH is currently standardizing the mechanisms to use TSCH in low-power IPv6 scenarios. This paper identifies a number of challenges when it comes to implementing the 6TiSCH stack. It shows how these challenges can be addressed with practical solutions for locking, queuing, scheduling and other aspects. With this implementation as an enabler, we present an experimental validation and comparison with state-of-the-art MAC protocols. We conduct fine-grained energy profiling, showing the impact of link-layer security on packet transmission. We evaluate distributed time synchronization in a 340-node testbed, and demonstrate that tight synchronization (hundreds of microseconds) can be achieved at very low cost (0.3% duty cycle, 0.008% channel utilization). We finally compare TSCH against traditional MAC layers: low-power listening (LPL) and CSMA, in terms of reliability, latency and energy. We show that with proper scheduling, TSCH achieves by far the highest reliability, and outperforms LPL in both energy and latency.

In low-power wireless networking, new applications such as cooperative robots or industrial closed-loop control demand for network-wide consensus at low-latency and high reliability. Distributed consensus protocols is a mature field of research in a wired context, but has received little attention in low-power wireless settings. In this paper, we present A2: Agreement in the Air, a system that brings distributed consensus to low-power multi-hop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this reliable base layer and enables the two- and three-phase commit protocols, as well as network services such as group membership, hopping sequence distribution and re-keying.

Many protocols in low-power wireless networks require a root node or a leader to bootstrap and maintain its operation. For example, Chaos and Glossy networks need an initiator to synchronize and initiate the communications rounds. Commonly, these protocols use a fixed, compile-time defined node as the leader. In this work, we tackle the challenge of dynamically bootstrapping the network and electing a leader in low-power wireless scenarios, and we focus on Chaos-style networks.

IoT applications often utilize the cloud to store and provide ubiquitous access to collected data. This naturally facilitates data sharing with third-party services and other users, but bears privacy risks, due to data breaches or unauthorized trades with user data. To address these concerns, we present Pilatus, a data protection platform where the cloud stores only encrypted data, yet is still able to process certain queries (e.g., range, sum). More importantly, Pilatus features a novel encrypted data sharing scheme based on re-encryption, with revocation capabilities and in situ key-update. Our solution includes a suite of novel techniques that enable efficient partially homomorphic encryption, decryption, and sharing. We present performance optimizations that render these cryptographic tools practical for mobile platforms. We implement a prototype of Pilatus and evaluate it thoroughly. Our optimizations achieve a performance gain within one order of magnitude compared to state-of-the-art realizations; mobile devices can decrypt hundreds of data points in a few hundred milliseconds. Moreover, we discuss practical considerations through two example mobile applications (Fitbit and Ava) that run Pilatus on real-world data.

Low-power wireless devices suffer notoriously from Cross- Technology Interference (CTI). To enable co-existence, researchers have proposed a variety of interference mitigation strategies. Existing solutions, however, are designed to work with the limitations of currently available radio chips. In this paper, we investigate how to exploit physical layer properties of 802.15.4 signals to better address CTI. We present CrossZig, a cross-layer solution that takes advantage of physical layer information and processing to improve low-power communication under CTI. To this end, CrossZig utilizes physical layer information to detect presence of CTI in a corrupted packet and to apply an adaptive packet recovery which incorporates a novel cross-layer based packet merging and an adaptive FEC coding. We implement a prototype of CrossZig for the low-power IEEE 802.15.4 in a software-defined radio platform. We show the adaptability and the performance gain of CrossZig through experimental evaluation considering both micro-benchmarking and system performance under various interference patterns. Our results demonstrate that CrossZig can achieve a high accuracy in error localization (94.3% accuracy) and interference type identification (less than 5% error rate for SINR ranges below 3 dB). Moreover, our system shows consistent performance improvements under interference from various interfering technologies.

Experimental research in low-power wireless networking lacks a reference benchmark. While other communities such as databases or machine learning have standardized benchmarks, our community still uses ad-hoc setups for its experiments and struggles to provide a fair comparison between communication protocols. Reasons for this include the diversity of network scenarios and the stochastic nature of wireless experiments. Leveraging on the excellent testbeds and tools that have been built to support experimental validation, we make the case for a reference benchmark to promote a fair comparison and reproducibility of results. This abstract describes early design elements and a benchmarking methodology with the goal to gather feedback from the community rather than propose a definite solution.

Industrial control systems have traditionally been built around dedicated wired solutions. The requirements of flexibility, mobility, and cost have created a strong push toward wireless solutions, preferably solutions requiring low power. Simultaneously, the increased need for interoperability and integration with the wider Internet made a transition to IP-based communication unavoidable. Following these trends, we survey 6TiSCH, the emerging family of standards for IP-based industrial communication over low-power and lossy networks. We describe the state of the standardization work, the major issues being discussed, and open questions recently identified. Based on extensive first-hand experience, we discuss challenges in implementation of this new wave of standards. Lessons learned are highlighted from four popular open-source implementations of these standards: OpenWSN, Contiki, RIOT, and TinyOS. We outline major requirements, present insights from early interoperability testing and performance evaluations, and provide guidelines for chip manufacturers and implementers.

Wireless Sensor Networks performing low-power data collection often suffer from uneven load distribution among nodes. Nodes close to the network root typically face a higher load, see their battery deplete first, and become prematurely unable to operate (both sensing and relaying other nodes' data). We argue that opportunistic routing, by making forwarding decision on a per-packet basis and at the receiver rather than the sender, has the potential to better balance the load across nodes. We extend ORPL, an opportunistic version of the standard routing protocol RPL, with support for load-balancing. In our protocol, ORPL-LB, nodes continuously adapt their wake-up interval in order to adjust their availability and attain a deployment-specific target duty cycle. We implement our protocol in Contikiand present our experimental validation in Indriya, a 93-nodestestbed. Our results show that ORPL-LB reduces significantly(by approximately 40%) the worst node's duty cycle, with little or no impact on packet delivery ratio and latency.

The rise of heterogeneity in wireless technologies operating in the unlicensed bands has been shown to adversely affect the performance of low-power wireless networks. Cross-Technology Interference (CTI) is highly uncertain and raises the need for agile methods that assess the channel conditions and apply actions maximizing communication success. In this paper, we present TIIM, a lightweight Technology-Independent Interference Mitigation solution that detects, quantifies, and reacts to CTI in realtime. TIIM employs a lightweight machine learning classifier to (i) decide whether communication is viable over the interfered link, (ii) characterize the ambient conditions and apply the best coexistence mitigation strategy. We present an in-depth experimental characterization of the effect of CTI on 802.15.4 links, which motivated and influenced the design of TIIM. Our evaluation shows that TIIM, while exposed to extensive and heterogeneous interference, can achieve a total PRR improvement of 30% with an additional transmission overhead of 5.6%.

Cyber-physical systems consist of several wirelessly connected components such as sensors that monitor physical phenomena, computational entities that make decisions based on sensed information and actuators that interact with physical processes. Connecting cyber-physical systems to the Internet using IP protocols increases interoperability by avoiding the need for protocol translation gateways. Unfortunately, in this context TCP has been disregarded since it is known to perform poorly in wireless scenarios as it treats packet loss as an indicator for network congestion rather than poor link quality. In this paper, we use the Low-power Wireless Bus (LWB) as a link layer for TCP/IP, taking advantage of its reliability and its routing-free communication. We design a system that integrates LWB with a low-power IP stack and includes TCP-aware schedulers for LWB. We evaluate our system with experiments on real hardware using uIP, a popular embedded Internet protocol stack. Our results demonstrate high TCP throughput in mobile and static scenarios and, furthermore, show that mobility does not decrease TCP performance.

The Internet of Things (IoT) is envisioned to digitize the physical world, resulting in a digital representation of our proximate living space. The possibility of inferring privacy violating information from IoT data necessitates adequate security measures regarding data storage and communication. To address these privacy and security concerns, we introduce our system that stores IoT data securely in the Cloud database while still allowing query processing over the encrypted data. We enable this by encrypting IoT data with a set of cryptographic schemes such as order-preserving and partially homomorphic encryptions. To achieve this on resource-limited devices, our system relies on optimized algorithms that accelerate partial homomorphic and order-preserving encryptions by 1 to 2 orders of magnitude. Our early results show the feasibility of our system on low-power devices. We envision our system as an enabler of secure IoT applications.

Time slotted operation is a well-proven approach to achieve highly reliable low-power networking through scheduling and channel hopping. It is, however, difficult to apply time slotting to dynamic networks as envisioned in the Internet of Things. Commonly, these applications do not have pre-defined periodic traffic patterns and nodes can be added or removed dynamically.

We present a system that leverages physical layer features to combat Cross-Technology Interference (CTI) in low-power wireless networks. Our system incorporates: (i) a lightweight interference detection mechanism for low-power radios that recognizes the type of interference in the received signal, (ii) a lightweight error detection mechanism to estimate and characterize error patterns within interfered packets, and (iii) a CTI-aware protocol that dynamically adapts transmission and recovery mode to the current interference patterns. We implement a prototype of our system for the low-power IEEE 802.15.4 in software-defined radios (SDR). Our early results of the system components demonstrate that we can achieve a high accuracy in error detection and interference type identification. Moreover, we observed a significant performance improvement compared to the standard 802.15.4 systems without interference-awareness.

The Internet of Things, by digitizing the physical world, is envisioned to enable novel interaction paradigms with our surroundings. This creates new threats and leads to unprecedented security and privacy concerns. To tackle these concerns, we introduce Talos, a system that stores IoT data securely in a Cloud database while still allowing query processing over the encrypted data. We enable this by encrypting IoT data with a set of cryptographic schemes such as order-preserving and partially homomorphic encryption. In order to achieve this in constrained IoT devices, Talos relies on optimized algorithms that accelerate order-preserving and partially homomorphic encryption by 1 to 2 orders of magnitude. We assess the feasibility of Talos on low-power devices with and without cryptographic accelerators and quantify its overhead in terms of energy, computation, and latency. With a thorough evaluation of our prototype implementation, we show that Talos is a practical system that can provide a high level of security with a reasonable overhead. We envision Talos as an enabler of secure IoT applications.

Lifetime estimation in Wireless Sensor Networks (WSN) is crucial to ensure that the network will last long enough (low maintenance cost) while not being over-dimensioned (low initial cost). Existing solutions have at least one of the two following limitations: (1) they are based on theoretical models or high-level protocol implementations, overlooking low-level (e.g., hardware, driver, etc.) constraints which we find have a significant impact on lifetime, and (2) they use an ideal battery model which over-estimates lifetime due to its constant voltage and its inability to model the non-linear properties of real batteries. We introduce a method for WSN lifetime estimation that operates on compiled firmware images and models the complex behavior of batteries. We use the MSPSim/Cooja node emulator and network simulator to run the application in a cycle-accurate manner and log all component states. We then feed the log into our lifetime estimation framework, which models the nodes and their batteries based on both technical and experimental specifications. In a case study of a Contiki RPL/6LoWPAN application, we identify and resolve several low-level implementation issues, thereby increasing the predicted network lifetime from 134 to 484 days. We compare our battery model to the ideal battery model and to the lifetime estimation based on the radio duty cycle, and find that there is an average over-estimation of 36% and 76% respectively.

Low-power wireless networks deployed in indoor environments inevitably encounter high-power Cross Technology Interference (CTI) from a wide range of wireless devices operating in the shared RF spectrum bands. This severely reduces the performance of such networks and possibly causes loss of connectivity, which affects their availability and drains their resources. In this work, to address the channel uncertainty, a consequence of CTI, we propose a novel channel metric that (i) harnesses the local knowledge of a node about the wireless channel to discern the presence of persistent high-power interferers, and (ii) assists the node in inferring its proximity to the dominant interference sources in the physical space. In order to motivate and validate the necessity of such a metric, we empirically characterize the impact of the interaction between high/low-power cross technology interferers and IEEE 802.15.4.

Exploiting multiple radio channels for communication has been long known as a practical way to mitigate interference in wireless settings. In Wireless Sensor Networks, however, multi-channel solutions have not reached their full potential: the MAC layers included in TinyOS or the Contiki OS for example are mostly single-channel. The literature offers a number of interesting solutions, but experimental results were often too few to build confidence. We propose a practical extension of low-power listening, MiCMAC, that performs channel hopping, operates in a distributed way, and is independent of upper layers of the protocol stack. The above properties make it easy to deploy in a variety of scenarios, without any extra configuration/scheduling/channel selection hassle. We implement our solution in Contiki and evaluate it in a 97-node~testbed while running a complete, out-of-the-box low-power IPv6 communication stack (UDP/RPL/6LoWPAN). Our experimental results demonstrate increased resilience to emulated WiFi interference (e.g., data yield kept above 90% when Contiki MAC drops in the 40% range). In noiseless environments, MiCMAC keeps the overhead low in comparison to Contiki MAC, achieving performance as high as 99% data yield along with sub-percent duty cycle and sub-second latency for a 1-minute inter-packet interval data collection.

ABSTRACT The future Internet is an IPv6 network interconnecting traditional computers and a large number of smart objects. This Internet of Things (IoT) will be the foundation of many services and our daily life will depend on its availability and reliable operation. Therefore, among many other issues, the challenge of implementing secure communication in the IoT must be addressed. In the traditional Internet, IPsec is the established and tested way of securing networks. It is therefore reasonable to explore the option of using IPsec as a security mechanism for the IoT. Smart objects are generally added to the Internet using IPv6 over Low‐power Wireless Personal Area Networks (6LoWPAN), which defines IP communication for resource‐constrained networks. Thus, to provide security for the IoT based on the trusted and tested IPsec mechanism, it is necessary to define an IPsec extension of 6LoWPAN. In this paper, we present such a 6LoWPAN/IPsec extension and show the viability of this approach. We describe our 6LoWPAN/IPsec implementation, which we evaluate and compare with our implementation of IEEE 802.15.4 link‐layer security. We also show that it is possible to reuse crypto hardware within existing IEEE 802.15.4 transceivers for 6LoWPAN/IPsec. The evaluation results show that IPsec is a feasible option for securing the IoT in terms of packet size, energy consumption, memory usage, and processing time. Furthermore, we demonstrate that in contrast to common belief, IPsec scales better than link‐layer security as the data size and the number of hops grow, resulting in time and energy savings. Copyright © 2012 John Wiley & Sons, Ltd.

Opportunistic routing is widely known to have substantially better performance than unicast routing in wireless networks with lossy links. However, wireless sensor networks are usually duty cycled, that is, they frequently enter sleep states to ensure long network lifetime. This renders existing opportunistic routing schemes impractical, as they assume that nodes are always awake and can overhear other transmissions. In this article we introduce ORW, a practical opportunistic routing scheme for wireless sensor networks. ORW uses a novel opportunistic routing metric, EDC, that reflects the expected number of duty-cycled wakeups that are required to successfully deliver a packet from source to destination. We devise distributed algorithms that find the EDC-optimal forwarding and demonstrate using analytical performance models and simulations that EDC-based opportunistic routing results in significantly reduced delay and improved energy efficiency compared to traditional unicast routing. In addition, we evaluate the performance of ORW in both simulations and testbed-based experiments. Our results show that ORW reduces radio duty cycles on average by 50% (up to 90% on individual nodes) and delays by 30% to 90% when compared to the state-of-the-art.

Routing in battery-operated wireless networks is challenging, posing a tradeoff between energy and latency. Previous work has shown that opportunistic routing can achieve low-latency data collection in duty-cycled networks. However, applications are now considered where nodes are not only periodic data sources, but rather addressable end points generating traffic with arbitrary patterns.

Traditionally, routing in wireless sensor networks consists of two steps: First, the routing protocol selects a next hop, and, second, the MAC protocol waits for the intended destination to wake up and receive the data. This design makes it difficult to adapt to link dynamics and introduces delays while waiting for the next hop to wake up.

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.

Requests scheduling in Web servers is a hot research topic. Many works aim at providing optimal algorithms according to various metrics. Most of these works are based on classical scheduling metrics, considering jobs completion times, but ignoring intermediate states. We claim that this choice conduces to the design of algorithm that do not efficiently share the system resources. Indeed, Web servers have some properties that make them different than the system considered in usual scheduling theory. The classical round-robin policy, used in most production Web servers, has intrinsic qualities: it shares equally the system resources and avoids any job starvation. We introduce a novel parameterizable algorithm proposing a compromise between the benefits of the round-robin and the policies that provide the best performances. Then, we discuss the appropriate choice of the parameter depending in the requirements and the context of the Web server.

In this paper, we show that Web protocols and technologies are good candidates to design the Internet of Things, through a user-centric architecture (the user simply has to use a standard Web browser). We detail how this Web of Things can handle typical embedded devices interaction needs. We discuss the technical feasibility of embedded Web servers, and, thanks to an analysis of the Web protocols, we propose new cross-layer solutions for efficient tiny embedded Web servers design. The problem of event notification for Web applications is also discussed. We finally present a prototype - named Smews - as a proof of concept of the Web of Things. Smews implements our proposals and has been embedded in tiny devices (smart cards, sensors and other embedded devices), with a requirement of only 200 bytes of volatile memory and 7 kilo-bytes of code. We show that it is significantly faster than other state of the art solutions. We made Smews source code publically available under an open-source license.

Embedded systems such as smart cards or sensors are now widespread, but are often closed systems, only accessed via dedicated terminals. A new trend consists in embedding Web servers in small devices, making both access and application development easier. In this paper, we propose a TCP performance model in the context of embedded Web servers, and we introduce a taxonomy of the contents possibly served by Web applications. The main idea of this paper is to adapt the communication stack behavior to application contents properties. We propose a strategies set fitting with each type of content. The model allows to evaluate the benefits of our strategies in terms of time and memory charge. By implementing a real use case on a smart card, we measure the benefits of our proposals and validate our model. Our prototype, called Smews, makes a gap with state of the art solutions both in terms of performance and memory charge.