The Internet of Things (IoT) is largely powered by batteries. This poses significant challenges for its sustainability and longevity, as batteries are short-lived, bulky and polluting. To overcome this problem, we posit the vision of a battery-less IoT network, where devices are powered by energy harvesting and tiny long-lived capacitors. However, such devices often run out of power, resulting in intermittent on-off behavior. Traditional static sequential applications cannot handle such behavior, as they lose forward progress. This problem can be solved with task-based applications, consisting of a chain of interconnected tasks. Each task performs some atomic function, and its output is saved in non-volatile memory after it successfully completes. This allows the application to ensure forward progress in face of frequent power failures. Optimally scheduling the execution of such tasks, in face of the specific behavior of various energy harvesters, as well as the capacitor, and given extremely constrained resources of battery-less devices, is non-trivial. In this project, we propose a novel task scheduler that takes these aspects, as well as the deadline of tasks into account.

The Internet of Things (IoT) vision has enabled the wireless connection of billions of battery-powered devices to the Internet. However, batteries are expensive, bulky, cause pollution and degrade after a few years. Replacing and disposing of billions of dead batteries every year is costly and unsustainable. We posit the vision of a sustainable Internet of Battery-Less Things. We imagine battery-less devices storing small amounts of energy in capacitors, harvested from their environment. Using this energy, these intermittently-powered devices can cooperatively perform sensing, actuation and communication tasks. Existing battery-less technology has many shortcomings. Such devices, usually based on passive RFID and backscatter, only support simple sensing, unable to handle more complex application logic. The goal of this project is to bring battery-less technology to the next level. We envision battery-less devices and networks that support complex sensing and actuation applications. To achieve this, we will investigate a novel energy-aware task scheduler for intermittent devices that intelligently decides which application and network tasks to execute at which time, considering task deadlines, data freshness, expected energy consumption of interconnected tasks and available and expected harvested energy. To further improve performance, cooperative task scheduling extensions to support offloading of computing tasks to powered cloud edge devices will also be investigated.

This project is part of the IMEC Frame Agreement and is being given as structural investment for fundamental research based on yearly set KPIs from the group to IMEC. This A-budget is defined within the IMEC Way of Working and part of the frame agreement of the University of Antwerp and IMEC.

Existing wireless technologies often exhibit poor performance in very dense networks, where hundreds or even thousands of stations need to connect to the same access point. This is mostly caused by the increased probability of two devices transmitting data at the same time, which causes the data packets to collide and be lost. Recently, station grouping has been proposed as a new method for collision-free data transmission in these dense environments. The basic idea is that stations are split into groups and each group is given a specific time interval during which only its members can transmit. This limits the maximum simultaneous transmissions, and therefore potential collisions. A station grouping configuration has many degrees of freedom: the number of groups, their duration, and which stations belong to each group. Several algorithms have been proposed to determine the optimal configuration as a function of the number of stations and their traffic demand. However, they all have several shortcomings that we aim to address in this project: they assume very specific and static traffic patterns, they do not optimise the trade-off between energy consumption and performance, and they cannot avoid interference among multiple overlapping networks. In this project, we will develop novel accurate mathematical models, based on Markov chains and supervised machine learning, that accurate estimate the energy consumption and throughput performance of specific station grouping configurations. This will be used to develop real-time station grouping algorithms that can handle heterogeneous stations and traffic, and adapt to changes in the traffic patterns. Finally, the algorithm will be extended to multiple access points, and used to implement interference avoidance mechanisms. The resulting solution will be evaluated using simulation to assess scalability, and will be implemented on real hardware to assess real-time execution time constraints.

This project is part of the IMEC Frame Agreement and is being given as structural investment for fundamental research based on yearly set KPIs from the group to IMEC. This A-budget is defined within the IMEC Way of Working and part of the frame agreement of the University of Antwerp and IMEC.

Existing wireless technologies often exhibit poor performance in very dense networks, where hundreds or even thousands of stations need to connect to the same access point. This is mostly caused by the increased probability of two devices transmitting data at the same time, which causes the data packets to collide and be lost. Recently, station grouping has been proposed as a new method for collision-free data transmission in these dense environments. The basic idea is that stations are split into groups and each group is given a specific time interval during which only its members can transmit. This limits the maximum simultaneous transmissions, and therefore potential collisions. A station grouping configuration has many degrees of freedom: the number of groups, their duration, and which stations belong to each group. Several algorithms have been proposed to determine the optimal configuration as a function of the number of stations and their traffic demand. However, they all have several shortcomings that we aim to address in this project: they assume very specific types of traffic, they cannot be executed in real-time, they cannot handle changes in traffic demand, they cannot provide Quality of Service differentiation among stations, and they cannot optimise multiple overlapping networks. The resulting solution will be evaluated using simulation to assess scalability, and will be implemented on real hardware to assess execution time constraints.

The goal of MAGICIaN is to overcome the limitations of out-of-the-box NB-IoT that prevent it from being used for mission-critical applications. Specifically, the standard does not natively support QoS differentiation or seamless handover mechanisms. We will design and develop an end-to-end network management solution that brings QoS guarantees on top of out-of-the-box best-effort NB-IoT networks. The MAGICIaN solution consists of two parts. The network controller interfaces and interacts with the NB-IoT access network (i.e., eNodeBs) and the different components in the Evolved Packet Core (EPC) to bring valueadded services on top of the best effort network.

In the SPIDER ESA project of Antwerp Space, Imec gives technological advice on data link and network layer protocol design for small satellite constellations and implementation and simulation in the ns-3 event-based network simulator.

The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. This has given rise to novel 'SIM-less' radio technologies that try to fill in this existing market gap of low-power wide area IoT networks, often referred to as Low Power Wide Area Networks or LPWANs. Due to the use of sub-GHz radio frequencies (typically 433 or 868 MHz), a single LPWAN base station has a large coverage area, with typical transmission ranges in the order of 1 up to 50 kilometres. As a result, a single base station can support high numbers of connected devices (> 1000 per base station), allowing a broad range of new technology companies to easily enter the IoT market. Currently, several sub-GHz technologies are being promoted simultaneously, all of which use the same (limited) wireless spectrum. Notorious initiatives in this domain are LoRa, SigFox, IEEE802.15.4g and the upcoming IEEE 802.11ah (or "HaloW") standard. However, many of these technologies are still in their infancy, and optimizations regarding a.o. quality of service, roaming, and service management are still lacking. In addition, since the amount of available spectrum is much smaller and the propagation ranges much larger, these technologies will cause interference at much larger scale, leading to severe inter-technology and inter-operator interference. If left unchecked the unlicensed sub-1GHz bands will soon be congested and unreliable. To avoid this fate, the IDEAL-IoT project will design and develop advanced, highly configurable networking components, combined with a coordination framework to uniformly manage and optimize an ecosystem of coexisting wireless sub-GHz LPWANs. More specifically, the project will investigate and develop novel & scalable networking solutions at three levels. 1. At intra-technology level, IDEAL-IoT will improve the performance of existing LPWAN networks. This objective includes (i) increasing the scalability of existing networks through the design and optimization of advanced PHY and MAC protocols for LPWAN networks; (ii) designing intelligent solutions to support real-time LPWAN traffic with latencies below 100 msec and reliability higher than 99.99%; (iii) improving energy efficiency by a factor 2 through PHY&MAC co-design. 2. At inter-technology level, IDEAL-IoT will improve the performance of coexisting LPWAN networks from different operators as well as provide coexistence between different LPWAN technologies. This objective includes: (i) reducing packet loss due to interference by 50% through interference detection, interference mitigation strategies and inter-technology LPWAN communication, negotiation and optimization; (ii) providing inter-technology roaming and multi-hop communication. 3. At management level, IDEAL-IoT will realize technology agnostic solutions for virtualized LPWAN network management and intelligence. This objective includes: (i) technology-agnostic virtualized components and light-weight APIs for real-time creation of virtualized LPWANs, on-the-fly adjustment of SLAs and dynamic installation of virtualized functionalities to control and improve interactions over LPWAN networks; (ii) the design of a cloud repository capable of optimizing LPWAN settings 10 times faster than is currently the case; (iii) realizing fully reliable over-the-air, reconfigurations and partial software updates of large groups of devices with 50% lower latency and 80% less network overhead.

The goal of MuSCLe-IoT is to design the necessary algorithms and protocols for both IoT devices and backend systems to support such multimodal communication and localization. Key innovations are planned in terms of inter-technology load balancing and routing, as well as multimodal GPS-less accurate indoor and outdoor localization. Particular attention will be paid to restrict the resulting footprint, signaling overhead and application impact to a bare minimum. A prototype solution will demonstrate the combined use of Sigfox, LoRa, DASH7 and 802.15.4g

The Internet of Things is fostering more and more mission critical applications on top of the wireless infrastructure. An example of this is the control of drones, which requires ultra-reliable communication with ultra low latency guarantees and the ability to switch from one technology to the other. Current IoT networks are currently not suited for providing such guarantees as (i) each technology works independently of each other, (ii) applications sometimes have limited control over the devices that are part of the network and (iii) existing high performing management solutions (e.g., Software Defined Networking) only work with resource rich devices. In this project, I propose a way to reach the same level of flexibility in the management of IoT networks as these high performing management solutions offer, without losing the support for resource constrained nodes and third party devices. We do this through WHISPER, an approach that generates "small lies" (fabricated messages) about the network state with the goal of improving the overall network management and providing guarantees on the application delivery. These messages are used to fool the existing IoT MAC, network and transport protocols in such a way that WHISPER will take control over the full network. This includes routing, link and end-to-end communication. As such, WHISPER can be used to manage a multi-technology IoT environment, where mission-critical applications such as drones can be hosted.

The High Impact project of IMEC aims at stimulating fundamental research that can benefit in the long term the valorization of the group. Within this project, the following research lines have been funded: - Appdaptive: configuring IoT networks based on application requirements - Participation in the DARPA Spectrum Collaboration challenge - Densenets: SDN-based network management of wireless networks (resulting in the ORCHESTRA framework) - SubWAN: management of new low power wide area wireless networks

The CONAMO project aims at improving both the training towards and the experience at mass amateur cycling events by continously monitoring and analysing the stream of cycling sensor data generated by the rider and his friends. It does this by introducing both innovations at the network (long-range networks) and the data analysis (machine learning and medical feedback).

Wireless sensor networks (WSNs) have become a very popular concept throughout the last decade, due to their wide applicability in monitoring and control applications (e.g. traffic control, environmental monitoring). They are composed of low-cost, battery-powered, constrained and failure-prone sensors and actuators, which are densely, randomly and redundantly deployed, communicating using wireless radio technologies. Recently, the concept of virtualization was proposed for WSNs. It has been applied to facilitate the creation of virtual sensors that provide more meaningful information by combining readings of multiple physical sensors and to support multi-tenancy and sensor hardware reuse by collocating multiple virtual onto a single physical sensor. The goal of this project is to uncover other, unexplored, benefits of WSN virtualization. Concretely, we will develop fully distributed solutions that allow physical sensors and actuators to self-organize into highly resilient and energy-efficient virtual sensing platforms. Resilience will be provided by exploiting redundancy of sensing hardware and network functions within virtual sensors. Energy-efficiency will be improved by intelligently disabling redundant functionality. Optimizing this trade-off dynamically is the main driver of this project proposal. The first two phases will respectively study control aspects within and between virtual sensors. The third phase will extend the solutions to the highly challenging and mostly unexplored field of mobile sensors.

Traditionally, the Internet was designed as a global communication network, allowing computers to exchange information. In the last decade, other types of devices, such as smartphones, have started connecting to the Internet. Currently, we are at the brink of another evolution, called the Internet of Things (IoT). It envisions connecting everyday appliances and devices to the Internet, such as washing machines, heart rate sensors and traffic lights. This evolution paves the way for society-benefiting applications, such as traffic lights that minimize car waiting time and remote monitoring of heart patients. However, connecting all these devices to the public Internet also carries great risk, as users with malicious intent can hack them to retrieve private information, or even worse, take control of them. To prevent this, and allow critical applications to be safely used in the IoT, the (often wireless) network that connects these devices to the Internet must be secured against hacking attempts and be made tolerant (i.e., resilient) against failures in case something does go wrong. However, this is a very challenging problem, since wireless communications can be easily intercepted or changed. Moreover, many devices are placed in public locations, making them susceptible to tampering. Finally, many envisioned IoT devices could move around (e.g., smartphones or implanted sensors), which further complicates things. The goal of this project is to make wireless IoT networks more secure and resilient. Three types of problems will be addressed: (i) internal attacks, (ii) external attacks and (iii) network failures. Internal attacks originate from a device that is already part of the network, caused by malicious (e.g., hackers that take control of a device) or selfish (e.g., users saving their own battery at the cost of others) behaviour. External attacks originate from outside the network and include hackers trying to find security holes. Finally, network failures are caused by unintentional errors, such as software bugs or malfunctioning hardware.

The High Impact project of IMEC aims at stimulating fundamental research that can benefit in the long term the valorization of the group. Within this project, the following research lines have been funded: - Appdaptive: configuring IoT networks based on application requirements - Participation in the DARPA Spectrum Collaboration challenge - Densenets: SDN-based network management of wireless networks (resulting in the ORCHESTRA framework) - SubWAN: management of new low power wide area wireless networks