This paper presents the design and implementation of the software for a run-time assurance infrastructure in the E-care@home system. An experimental evaluation is conducted to verify that the run-time assurance infrastructure is functioning correctly, and to enable detecting performance degradation in experimental IoT network deployments within the context of E-care@home. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

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 ContikiMAC drops in the 40% range). In noiseless environments, MiCMAC keeps the overhead low in comparison to ContikiMAC, 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.

Medium access control for wireless sensor networks has been a very active research area for the past couple of years. The sensor networks literature presents an alphabet soup of medium access control protocols with almost all of the works focusing only on energy efficiency. There is much more innovative work to be done at the MAC layer, but current efforts are not addressing the hard unsolved problems. Majority of the works appearing in the literature are "least publishable incremental improvements" over the popular S-MAC [1] protocol. In this paper we present research directions for future medium access research. We identify some open issues and discuss possible solutions.

Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.

Energy is one of the most important resources in wireless sensor networks. We use an idealized mathematical model to study the impact of routing on energy consumption. Our results are very general and, within the assumptions listed in Section 2, apply to arbitrary topologies, routings and radio energy models. We find bounds on the minimal and maximal energy routings will consume, and use them to bound the lifetime of the network. The bounds are sharp, and can be achieved in many situations of interest. We illustrate the theory with some examples.

Energy is one of the most important resources in wireless sensor networks. We use an idealized mathematical model to study the energy consumption under all possible routings. Our results are very general and, within the assumptions listed in Section 2, apply to arbitrary topologies, routings and radio energy models. We find bounds on the minimal and maximal energy routings will consume, and use them to bound the lifetime of the network. The bounds are sharp, and we show that they are achievable in many situations of interest. We give some examples, and apply the theory to the problem of covering a given square region with the most efficient member of a family of increasingly more dense square-lattice sensor networks. Finally, we use simulations to test these results in a more realistic scenario, where packet loss can occur.

The Internet of Things (IoT) consists of resource-constrained devices (e.g., sensors and actuators) which form low power and lossy networks to connect to the Internet. With billions of devices deployed in various environments, IoT is one of the main building blocks of future Internet of Services (IoS). Limited power, processing, storage and radio dictate extremely efficient usage of these resources to achieve high reliability and availability in IoS. Denial of Service (DoS) and Distributed DoS (DDoS) attacks aim to misuse the resources and cause interruptions, delays, losses and degrade the offered services in IoT. DoS attacks are clearly threats for availability and reliability of IoT, and thus of IoS. For highly reliable and available IoS, such attacks have to be prevented, detected or mitigated autonomously. In this study, we propose a comprehensive investigation of Internet of Things security for reliable Internet of Services. We review the characteristics of IoT environments, cryptography-based security mechanisms and D/DoS attacks targeting IoT networks. In addition to these, we extensively analyze the intrusion detection and mitigation mechanisms proposed for IoT and evaluate them from various points of view. Lastly, we consider and discuss the open issues yet to be researched for more reliable and available IoT and IoS. © The Author(s) 2018.

We present the experimental evaluation of different security mechanisms applied to persistent state in intermittent computing. Whenever executions become intermittent because of energy scarcity, systems employ persistent state on non-volatile memories (NVMs) to ensure forward progress of applications. Persistent state spans operating system and network stack, as well as applications. While a device is off recharging energy buffers, persistent state on NVMs may be subject to security threats such as stealing sensitive information or tampering with configuration data, which may ultimately corrupt the device state and render the system unusable. Based on modern platforms of the Cortex M*series, we experimentally investigate the impact on typical intermittent computing workloads of different means to protect persistent state, including software and hardware implementations of staple encryption algorithms and the use of ARM TrustZone protection mechanisms. Our results indicate that i) software implementations bear a significant overhead in energy and time, sometimes harming forward progress, but also retaining the advantage of modularity and easier updates; ii) hardware implementations offer much lower overhead compared to their software counterparts, but require a deeper understanding of their internals to gauge their applicability in given application scenarios; and iii) TrustZone shows almost negligible overhead, yet it requires a different memory management and is only effective as long as attackers cannot directly access the NVMs

Many Wireless Sensor Networks (WSNs) are used to collect and process confidential information. Confidentiality must be ensured at all times and, for example, solutions for confidential communication, processing or storage are required. To date, the research community has addressed mainly the issue of confidential communication. Efficient solutions for cryptographically secured communication and associated key exchange in WSNs exist. Many WSN applications, however, rely heavily on available on-node storage space and therefore it is essential to ensure the confidentiality of stored data as well. In this paper we present Codo, a confidential data storage solution which balances platform, performance and security requirements. We implement Codo for the Contiki WSN operating system and evaluate its performance.

The future Internet of Things (IoT) may be based on the existing and established Internet Protocol (IP). Many IoT application scenarios will handle sensitive data. However, as security requirements for storage and communication are addressed separately, work such as key management or cryp-tographic processing is duplicated. In this paper we present a framework that allows us to combine secure storage and secure communication in the IP-based IoT. We show how data can be stored securely such that it can be delivered securely upon request without further cryptographic processing. Our prototype implementation shows that combined secure storage and communication can reduce the security-related processing on nodes by up to 71% and energy consumption by up to 32.1%.

Comprehensive security mechanisms are required for a successful implementation of the Internet of Things (IoT). Existing solutions focus mainly on securing the communication links between Internet hosts and IoT devices. However, as most IoT devices nowadays provide vast amounts of flash storage space it is as well required to consider storage security within a comprehensive security framework. Instead of developing independent security solutions for storage and communication we propose Fusion, a framework which provides coalesced confidential storage and communication. Fusion uses existing secure communication protocols for the IoT such as IPsec and DTLS and re-uses the defined communication security mechanisms within the storage component. Thus, trusted mechanisms developed for communication security are extended into the storage space. Notably, this mechanism allows us to transmit requested data directly from the file system without decrypting read data blocks and then re-encrypting these for transmission. Thus, Fusion provides benefits in terms of processing speed and energy efficiency which are important aspects for resource constrained IoT devices. The paper describes the Fusion architecture and its instantiation for IPsec and DTLS based systems. We describe Fusion’s implementation and evaluate its storage overheads, communication performance and energy consumption

We study the effect of interference on localization algorithms through the study of the interference effect on signal features that are used for localization. Particularly, the effect of interference on packet-based Received Signal Strength Indicator (RSSI), reported by IEEE 802.11 and IEEE 802.15.4 technologies, and on Time of Flight (ToF), reported by IEEE 802.15.4 technology, is studied using both theoretical discussions and experimental verifications. As for the RSSI values, using an information theoretic formulation, we distinguish three operational regimes and we show that the RSSI values, in dBm, remain unchanged in the noise-limited regime, increase almost linearly with interference power in dBm in the interference-limited regime and cannot be obtained due to packet loss in the collision regime. The maximum observable RSSI variation is dependent on the transmission rate and Signal to Noise Ratio (SNR). We also show that ToF is, interestingly, decreased under interference which is caused in the symbol synchronization procedure at the receiver. After providing the experimental results, we discuss how the localization algorithms are affected by interference.

Radio interference may lead to packet losses, thus negatively affecting the performance of sensornet applications. In this paper, we experimentally assess the impact of external interference on state-of-the-art sensornet MAC protocols. Our experiments illustrate that specific features of existing protocols, e.g., hand-shaking schemes preceding the actual data transmission, play a critical role in this setting. We leverage these results by identifying mechanisms to improve the robustness of existing MAC protocols under interference. These mechanisms include the use of multiple hand-shaking attempts coupled with packet trains and suitable congestion backoff schemes to better tolerate interference. We embed these mechanisms within an existing X-MAC implementation and show that they considerably improve the packet delivery rate while keeping the power consumption at a moderate level.

Temperature is known to have a significant effect on the performance of radio transceivers: the higher the temper- ature, the lower the quality of links. Analysing this effect is particularly important in sensor networks because several applications are exposed to harsh environmental conditions. Daily or hourly changes in temperature can dramatically reduce the throughput, increase the delay, or even lead to network partitions. A few studies have quantified the impact of temperature on low-power wireless links, but only for a limited temperature range and on a single radio transceiver. Building on top of these preliminary observations, we de- sign a low-cost experimental infrastructure to vary the on- board temperature of sensor nodes in a repeatable fashion, and we study systematically the impact of temperature on various sensornet platforms. We show that temperature af- fects transmitting and receiving nodes differently, and that all platforms follow a similar trend that can be captured in a simple first-order model. This work represents an ini- tial stepping stone aimed at predicting the performance of a network considering the particular temperature profile of a given environment.

Wireless low-power transceivers used in sensor networks typically operate in unlicensed frequency bands that are subject to external radio interference caused by devices transmitting at much higher power.communication protocols should therefore be designed to be robust against such interference. A critical building block of many protocols at all layers is agreement on a piece of information among a set of nodes. At the MAC layer, nodes may need to agree on a new time slot or frequency channel, at the application layer nodes may need to agree on handing over a leader role from one node to another. Message loss caused by interference may break agreement in two different ways: none of the nodes uses the new information (time slot, channel, leader) and sticks with the previous assignment, or-even worse-some nodes use the new information and some do not. This may lead to reduced performance or failures. In this paper, we investigate the problem of agreement under external radio interference and point out the limitations of traditional message-based approaches. We propose JAG, a novel protocol that uses jamming instead of message transmissions to make sure that two neighbouring nodes agree, and show that it outperforms message-based approaches in terms of agreement probability, energy consumption, and time-to-completion. We further show that JAG can be used to obtain performance guarantees and meet the requirements of applications with real-time constraints.

New Internet of Things (IoT) technologies such as Long Range (LoRa) are emerging which enable power efficient wireless communication over very long distances. Devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multihop network. Given the fact that a wide area is covered and that all devices communicate directly to a few sink nodes a large number of nodes have to share the communication medium. LoRa provides for this reason a range of communication options (centre frequency, spreading factor, bandwidth, coding rates) from which a transmitter can choose. Many combination settings are orthogonal and provide simultaneous collision free communications. Nevertheless, there is a limit regarding the number of transmitters a LoRa system can support. In this paper we investigate the capacity limits of LoRa networks. Using experiments we develop models describing LoRa communication behaviour. We use these models to parameterise a LoRa simulation to study scalability. Our experiments show that a typical smart city deployment can support 120 nodes per 3.8 ha, which is not sufficient for future IoT deployments. LoRa networks can scale quite well, however, if they use dynamic communication parameter selection and/or multiple sinks.

In this paper, we address the support of TimeSlotted Channel Hopping (TSCH) on multiple frequency bandswithin a single TSCH network. This allows to simultaneously runapplications with different requirements on link characteristicsand to increase resilience against interference. To this end, wefirst enable sub-GHz communication in TSCH, which has beenprimarily defined for the 2.4 GHz band. Thereafter, we proposetwo designs to support multiple physical layers in TSCH on thesame nodes. Our experimental evaluation shows that TSCH isapplicable in a wide range of data rates between 1.2 kbps and1000 kbps. We find that data rates of 50 kbps and below have along communication range and a nearly perfect link symmetry,but also have a 20x higher channel utilization compared to higherdata rates, increasing the risk of collisions. Using these findings,we show the advantages of the multi-band support on the exampleof synchronization accuracy when exchanging TSCH beaconswith a low data rate and application data at a high data rate.Index Terms—Sub-GHz communication, IEEE 802.15.4,TSCH, multi-band support, timeslot duration

In this paper we present BurstProbe, a new technique to accurately measure link burstiness in a wireless sensor network employed for time-critical data delivery. Measurement relies on shared probing slots that are embedded in the transmission schedule and used by nodes to assess link burstiness over time. The acquired link burstiness information can be stored in the node's ash memory and relied upon to diagnose transmission problems when missed deadlines occur. Thus, accurate diagnosis is achieved in a distributed manner and without the overhead of transmitting rich measurement data to a central collection point. For the purpose of evaluation we have implemented BurstProbe in the GinMAC WSN protocol and we are able to demonstrate it is an accurate tool to debug time-critical data delivery. In addition, we analyze the cost of implementing BurstProbe and investigate its effectiveness.

The Internet of Things is expanding and since IoT devices and IoT networks are used in many crucial areas in modern societies, ranging from security and military applications to healthcare monitoring and production efficiency, the need to secure these devices is of great importance. Intrusion detection systems (IDS) play a significant role in securing IoT networks as their goal is to detect intruders that have gained access to one or several IoT nodes. While most IDS have been designed to detect a specific or at most a few attacks, the DETONAR framework detects multiple attacks. However, it is run on a designated sniffer network which adds additional cost in terms of hardware and maintenance. In this paper, we propose DETONAR-Light, adapting DETONAR to run using data collected at a border router rather than on sniffer logs. Our experiments show that this is possible almost without any decrease of detection and attack classification rate for many attacks

Time-slotted channel hopping (TSCH) is one of the medium access control (MAC) behavior modes defined in the IEEE 802.15.4e standard. It combines time-slotted access and channel hopping, thus providing predictable latency, energy efficiency, communication reliability, and high network capacity. TSCH provides both dedicated and shared links. The latter is special slots assigned to more than one transmitter, whose concurrent access is regulated by a carrier-sense multiple access with collision avoidance (CSMA-CA) algorithm. In this paper, we develop an analytical model of the TSCH CSMA-CA algorithm to predict the performance experienced by nodes when using shared links. The model allows for deriving a number of metrics, such as delivery probability, packet latency, and energy consumption of nodes. Moreover, it considers the capture effect (CE) that typically occurs in real wireless networks. We validate the model through simulation experiments and measurements in a real testbed. Our results show that the model is very accurate. Furthermore, we found that the CE plays a fundamental role as it can significantly improve the performance experienced by nodes.

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.

The TCP/IP protocol suite, which has proven itself highly successful in wired networks, is often claimed to be unsuited for wireless micro-sensor networks. In this work, we question this conventional wisdom and present a number of mechanisms that are intended to enable the use of TCP/IP for wireless sensor networks: spatial IP address assignment, shared context header compression, application overlay routing, and distributed TCP caching (DTC). Sensor networks based on TCP/IP have the advantage of being able to directly communicate with an infrastructure consisting either of a wired IP network or of IP-based wireless technology such as GPRS. We have implemented parts of our mechanisms both in a simulator environment and on actual sensor nodes, and preliminary results are promising.

Previous research on transport layer protocols for wireless sensor networks (WSNs) has focused on designing protocols specifically targeted for sensor networks. Most sensor networks applications, however, are only useful when connected to an external network. The deployment of TCP/IP in WSNs would enable direct connection between the WSN and external TCP/IP networks. However, TCP performs badly in wireless environments both in terms of throughput and energy efficiency. To overcome these problems in WSNs we have designed Distributed TCP Caching. This mechanism greatly enhances TCP performance by caching TCP segments on the nodes in the sensor network and locally retransmitting lost segments. Our simulations demonstrate that with these enhancements TCP performs well enough to be useful in wireless sensor networks.

This paper describes a prototype sensor networking platform and its associated development environment. Key elements of the system are the ESB sensor hardware, the Contiki operating system, and the communication stack, which includes a MAC layer and a highly optimized TCP/IP. Because the work is driven by prototype applications being developed by project partners, particular attention is paid to the development environment and to practical deployment issues. Three prototype applications are also presented.

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 linking. 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.

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 dynamically download code into the network. In this paper 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.

Wireless sensor networks are composed of large numbers of tiny networked devices that communicate untethered. In this paper we present the design of Contiki, a lightweight and portable operating system for such tiny devices. In this work, we try to find the right operating system abstractions that enable dynamic and efficient operation of a system with severe limitations. Contiki is built around a lightweight event scheduler and provides suitable abstractions for dynamic loading of programs, device drivers, and run-time linking of libraries. The system is highly portable and the kernel can be ported without changing a single line of code (except device drivers). We show how higher level abstractions such as multi-threading can be implemented as libraries on top of the lightweight event kernel.

Wireless sensor networks consist of tiny devices that usually have severe resource constraints in terms of energy, processing power and memory. In order to work efficiently within the constrained memory, many operating systems for such devices are based on an event-driven model rather than on multi-threading. While event-driven systems allow for reduced memory usage, they require programs to be developed as explicit state machines. Since implementing programs as explicit state machines is hard, developing, maintaining, and debugging programs for event-driven systems is difficult. In this paper, we introduce protothreads, a programming abstraction for event-driven sensor network systems. Protothreads simplify implementation of high-level functionality on top of event-driven systems, without significantly increasing the memory requirements. The memory requirement of a protothread is that of an unsigned integer.