Interactive Joint Transfer of Energy and Information

In some communication networks, such as passive RFID systems, the energy used to transfer information between a sender and a recipient can be reused for successive communication tasks. In fact, from known results in physics, any system that exchanges information via the transfer of given physical resources, such as radio waves, particles and qubits, can conceivably reuse, at least part, of the received resources. This paper aims at illustrating some of the new challenges that arise in the design of communication networks in which the signals exchanged by the nodes carry both information and energy. To this end, a baseline two-way communication system is considered in which two nodes communicate in an interactive fashion. In the system, a node can either send an "on" symbol (or "1"), which costs one unit of energy, or an "off" signal (or "0"), which does not require any energy expenditure. Upon reception of a "1" signal, the recipient node "harvests", with some probability, the energy contained in the signal and stores it for future communication tasks. Inner and outer bounds on the achievable rates are derived. Numerical results demonstrate the effectiveness of the proposed strategies and illustrate some key design insights.Comment: 29 pages, 11 figures, Submitted in IEEE Transactions on Communications. arXiv admin note: substantial text overlap with arXiv:1204.192

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Numerical methods for queues with shared service

A queueing system is a mathematical abstraction of a situation where elements, called customers, arrive in a system and wait until they receive some kind of service. Queueing systems are omnipresent in real life. Prime examples include people waiting at a counter to be served, airplanes waiting to take off, traffic jams during rush hour etc. Queueing theory is the mathematical study of queueing phenomena. As often neither the arrival instants of the customers nor their service times are known in advance, queueing theory most often assumes that these processes are random variables. The queueing process itself is then a stochastic process and most often also a Markov process, provided a proper description of the state of the queueing process is introduced. This dissertation investigates numerical methods for a particular type of Markovian queueing systems, namely queueing systems with shared service. These queueing systems differ from traditional queueing systems in that there is simultaneous service of the head-of-line customers of all queues and in that there is no service if there are no customers in one of the queues. The absence of service whenever one of the queues is empty yields particular dynamics which are not found in traditional queueing systems. These queueing systems with shared service are not only beautiful mathematical objects in their own right, but are also motivated by an extensive range of applications. The original motivation for studying queueing systems with shared service came from a particular process in inventory management called kitting. A kitting process collects the necessary parts for an end product in a box prior to sending it to the assembly area. The parts and their inventories being the customers and queues, we get ``shared service'' as kitting cannot proceed if some parts are absent. Still in the area of inventory management, the decoupling inventory of a hybrid make-to-stock/make-to-order system exhibits shared service. The production process prior to the decoupling inventory is make-to-stock and driven by demand forecasts. In contrast, the production process after the decoupling inventory is make-to-order and driven by actual demand as items from the decoupling inventory are customised according to customer specifications. At the decoupling point, the decoupling inventory is complemented with a queue of outstanding orders. As customisation only starts when the decoupling inventory is nonempty and there is at least one order, there is again shared service. Moving to applications in telecommunications, shared service applies to energy harvesting sensor nodes. Such a sensor node scavenges energy from its environment to meet its energy expenditure or to prolong its lifetime. A rechargeable battery operates very much like a queue, customers being discretised as chunks of energy. As a sensor node requires both sensed data and energy for transmission, shared service can again be identified. In the Markovian framework, "solving" a queueing system corresponds to finding the steady-state solution of the Markov process that describes the queueing system at hand. Indeed, most performance measures of interest of the queueing system can be expressed in terms of the steady-state solution of the underlying Markov process. For a finite ergodic Markov process, the steady-state solution is the unique solution of $N-1$ balance equations complemented with the normalisation condition, $N$ being the size of the state space. For the queueing systems with shared service, the size of the state space of the Markov processes grows exponentially with the number of queues involved. Hence, even if only a moderate number of queues are considered, the size of the state space is huge. This is the state-space explosion problem. As direct solution methods for such Markov processes are computationally infeasible, this dissertation aims at exploiting structural properties of the Markov processes, as to speed up computation of the steady-state solution. The first property that can be exploited is sparsity of the generator matrix of the Markov process. Indeed, the number of events that can occur in any state --- or equivalently, the number of transitions to other states --- is far smaller than the size of the state space. This means that the generator matrix of the Markov process is mainly filled with zeroes. Iterative methods for sparse linear systems --- in particular the Krylov subspace solver GMRES --- were found to be computationally efficient for studying kitting processes only if the number of queues is limited. For more queues (or a larger state space), the methods cannot calculate the steady-state performance measures sufficiently fast. The applications related to the decoupling inventory and the energy harvesting sensor node involve only two queues. In this case, the generator matrix exhibits a homogene block-tridiagonal structure. Such Markov processes can be solved efficiently by means of matrix-geometric methods, both in the case that the process has finite size and --- even more efficiently --- in the case that it has an infinite size and a finite block size. Neither of the former exact solution methods allows for investigating systems with many queues. Therefore we developed an approximate numerical solution method, based on Maclaurin series expansions. Rather than focussing on structural properties of the Markov process for any parameter setting, the series expansion technique exploits structural properties of the Markov process when some parameter is sent to zero. For the queues with shared exponential service and the service rate sent to zero, the resulting process has a single absorbing state and the states can be ordered such that the generator matrix is upper-diagonal. In this case, the solution at zero is trivial and the calculation of the higher order terms in the series expansion around zero has a computational complexity proportional to the size of the state space. This is a case of regular perturbation of the parameter and contrasts to singular perturbation which is applied when the service times of the kitting process are phase-type distributed. For singular perturbation, the Markov process has no unique steady-state solution when the parameter is sent to zero. However, similar techniques still apply, albeit at a higher computational cost. Finally we note that the numerical series expansion technique is not limited to evaluating queues with shared service. Resembling shared queueing systems in that a Markov process with multidimensional state space is considered, it is shown that the regular series expansion technique can be applied on an epidemic model for opinion propagation in a social network. Interestingly, we find that the series expansion technique complements the usual fluid approach of the epidemic literature

Methods and Tools for Battery-free Wireless Networks

Embedding small wireless sensors into the environment allows for monitoring physical processes with high spatio-temporal resolutions. Today, these devices are equipped with a battery to supply them with power. Despite technological advances, the high maintenance cost and environmental impact of batteries prevent the widespread adoption of wireless sensors. Battery-free devices that store energy harvested from light, vibrations, and other ambient sources in a capacitor promise to overcome the drawbacks of (rechargeable) batteries, such as bulkiness, wear-out and toxicity. Because of low energy input and low storage capacity, battery-free devices operate intermittently; they are forced to remain inactive for most of the time charging their capacitor before being able to operate for a short time. While it is known how to deal with intermittency on a single device, the coordination and communication among groups of multiple battery-free devices remain largely unexplored. For the first time, the present thesis addresses this problem by proposing new methods and tools to investigate and overcome several fundamental challenges

The Case for Approximate Intermittent Computing

We present the concept of approximate intermittent computing and concretely demonstrate its application. Intermittent computations stem from the erratic energy patterns caused by energy harvesting: computations unpredictably terminate whenever energy is insufficient and the application state is lost. Existing solutions maintain equivalence to continuous executions by creating persistent state on non-volatile memory, enabling stateful computations to cross power failures. The performance penalty is massive: system throughput reduces while energy consumption increases. In contrast, approximate intermittent computations trade the accuracy of the results for sparing the entire overhead to maintain equivalence to a continuous execution. This is possible as we use approximation to limit the extent of stateful computations to the single power cycle, enabling the system to completely shift the energy budget for managing persistent state to useful computations towards an immediate approximate result. To this end, we effectively reverse the regular formulation of approximate computing problems. First, we apply approximate intermittent computing to human activity recognition. We design an anytime variation of support vector machines able to improve the accuracy of the classification as energy is available. We build a hw/sw prototype using kinetic energy and show a 7x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while retaining 83% accuracy in a setting where the best attainable accuracy is 88%. Next, we apply approximate intermittent computing in a sharply different scenario, that is, embedded image processing, using loop perforation. Using a different hw/sw prototype we build and diverse energy traces, we show a 5x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while providing an equivalent output in 84% of the cases

Stochastic Modeling and Analysis for Environmentally Powered Wireless Sensor Nodes

Environmental energy is becoming a feasible alternative for many low-power systems, such as wireless sensor nodes. Designing an environmentally powered device faces several challenges: choosing the exact type of the energy harvester, the energy storage elements and determining the duty cycle of the application. With harvesting, the design process becomes even more difficult because it also has to take into account the unpredictability of the energy source. The contribution of this paper is a methodology that facilitates the analysis of energy harvesting nodes. The existing modeling strategies for battery powered systems are not suitable because they do not capture the uncertainty of the power source. Also, the metrics of interest for battery powered devices are different, as opposed to the harvesting powered ones: in the former case we search to maximize the system lifetime, while in the latter case a more expressive goal is to increase the system availability

Wireless wire - ultra-low-power and high-data-rate wireless communication systems

With the rapid development of communication technologies, wireless personal-area communication systems gain momentum and become increasingly important. When the market gets gradually saturated and the technology becomes much more mature, new demands on higher throughput push the wireless communication further into the high-frequency and high-data-rate direction. For example, in the IEEE 802.15.3c standard, a 60-GHz physical layer is specified, which occupies the unlicensed 57 to 64 GHz band and supports gigabit links for applications such as wireless downloading and data streaming. Along with the progress, however, both wireless protocols and physical systems and devices start to become very complex. Due to the limited cut-off frequency of the technology and high parasitic and noise levels at high frequency bands, the power consumption of these systems, especially of the RF front-ends, increases significantly. The reason behind this is that RF performance does not scale with technology at the same rate as digital baseband circuits. Based on the challenges encountered, the wireless-wire system is proposed for the millimeter wave high-data-rate communication. In this system, beamsteering directional communication front-ends are used, which confine the RF power within a narrow beam and increase the level of the equivalent isotropic radiation power by a factor equal to the number of antenna elements. Since extra gain is obtained from the antenna beamsteering, less front-end gain is required, which will reduce the power consumption accordingly. Besides, the narrow beam also reduces the interference level to other nodes. In order to minimize the system average power consumption, an ultra-low power asynchronous duty-cycled wake-up receiver is added to listen to the channel and control the communication modes. The main receiver is switched on by the wake-up receiver only when the communication is identified while in other cases it will always be in sleep mode with virtually no power consumed. Before transmitting the payload, the event-triggered transmitter will send a wake-up beacon to the wake-up receiver. As long as the wake-up beacon is longer than one cycle of the wake-up receiver, it can be captured and identified. Furthermore, by adopting a frequency-sweeping injection locking oscillator, the wake-up receiver is able to achieve good sensitivity, low latency and wide bandwidth simultaneously. In this way, high-data-rate communication can be achieved with ultra-low average power consumption. System power optimization is achieved by optimizing the antenna number, data rate, modulation scheme, transceiver architecture, and transceiver circuitries with regards to particular application scenarios. Cross-layer power optimization is performed as well. In order to verify the most critical elements of this new approach, a W-band injection-locked oscillator and the wake-up receiver have been designed and implemented in standard TSMC 65-nm CMOS technology. It can be seen from the measurement results that the wake-up receiver is able to achieve about -60 dBm sensitivity, 10 mW peak power consumption and 8.5 µs worst-case latency simultaneously. When applying a duty-cycling scheme, the average power of the wake-up receiver becomes lower than 10 µW if the event frequency is 1000 times/day, which matches battery-based or energy harvesting-based wireless applications. A 4-path phased-array main receiver is simulated working with 1 Gbps data rate and on-off-keying modulation. The average power consumption is 10 µW with 10 Gb communication data per day

Relaying in the Internet of Things (IoT): A Survey

The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to gateways. However, incorporating relays into IoT networks faces some challenges. IoT end devices are designed primarily for uplink communication of small-sized observations toward the network; hence, opportunistically using end devices as relays needs a redesign of both the medium access control (MAC) layer protocol of such end devices and possible addition of new communication interfaces. Additionally, the wake-up time of IoT end devices needs to be synchronized with that of the relays. For cellular-based IoT, the possibility of using infrastructure relays exists, and noncellular IoT networks can leverage the presence of mobile devices for relaying, for example, in remote healthcare. However, the latter presents problems of incentivizing relay participation and managing the mobility of relays. Furthermore, although relays can increase the lifetime of IoT networks, deploying relays implies the need for additional batteries to power them. This can erode the energy efficiency gain that relays offer. Therefore, designing relay-assisted IoT networks that provide acceptable trade-offs is key, and this goes beyond adding an extra transmit RF chain to a relay-enabled IoT end device. There has been increasing research interest in IoT relaying, as demonstrated in the available literature. Works that consider these issues are surveyed in this paper to provide insight into the state of the art, provide design insights for network designers and motivate future research directions