Computing Battery Lifetime Distributions

The usage of mobile devices like cell phones, navigation systems, or laptop computers, is limited by the lifetime of the included batteries. This lifetime depends naturally on the rate at which energy is consumed, however, it also depends on the usage pattern of the battery. Continuous drawing of a high current results in an excessive drop of residual capacity. However, during \ud intervals with no or very small currents, batteries do recover to a certain extend. We model this complex behaviour with an inhomogeneous Markov reward model, following the approach of the so-called Kinetic battery Model (KiBaM). \ud The state-dependent reward rates thereby correspond to the power consumption of the attached device and to the available charge, respectively. We develop a tailored numerical algorithm for the computation of the distribution of the consumed energy and show how different workload patterns influence the overall lifetime of a battery

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Wireless distance estimation with low-power standard components in wireless sensor nodes

In the context of increasing use of moving wireless sensor nodes the interest in localizing these nodes in their application environment is strongly rising. For many applications, it is necessary to know the exact position of the nodes in two- or three-dimensional space. Commonly used nodes use state-of-the-art transceivers like the CC430 from Texas Instruments with integrated signal strength measurement for this purpose. This has the disadvantage, that the signal strength measurement is strongly dependent on the orientation of the node through the antennas inhomogeneous radiation pattern as well as it has a small accuracy on long ranges. Also, the nodes overall attenuation and output power has to be calibrated and interference and multipath effects appear in closed environments. Another possibility to trilaterate the position of a sensor node is the time of flight measurement. This has the advantage, that the position can also be estimated on long ranges, where signal strength methods give only poor accuracy. In this paper we present an investigation of the suitability of the state-of-the-art transceiver CC430 for a system based on time of flight methods and give an overview of the optimal settings under various circumstances for the in-field application. For this investigation, the systematic and statistical errors in the time of flight measurements with the CC430 have been investigated under a multitude of parameters. Our basic system does not use any additional components but only the given standard hardware, which can be found on the Texas Instruments evaluation board for a CC430. Thus, it can be implemented on already existent sensor node networks by a simple software upgrade.Comment: 8 pages, Proceedings of the 14th Mechatronics Forum International Conference, Mechatronics 201

Connectivity, Coverage and Placement in Wireless Sensor Networks

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes

On the cooperative relaying strategies for multi-core wireless Network-on-Chip

Recently, hybrid wired-wireless Network-on-Chip (WiNoC) has been proposed as a suitable communication fabric to provide scalability and satisfy high performance demands of the exascale era of modern multi/many-core System-on-Chip (SoC) design. A well accepted low-latency wireless communication fabric for WiNoCs is millimeter wave (mm-Wave). However, the wireless channel of mm-Wave is lossy due to free space signal radiation with both dielectric propagation loss (DPL) and molecular absorption attenuation (MAA). This is exacerbated for edge situated cores and in macro-chips embodying thousands of cores. To this end, this paper proposes efficient relaying techniques to improve the signal strength of the wireless channel in the WiNoCs using on-chip networking approaches under the realistic SoC channel conditions. First, we propose a realistic relay communication channel for the WiNoCs to characterise both MAA and DPL which have drastic effect on the performance. We then derive and show that the channel capacity for a single-relay WiNoC employing Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying protocols increases by up to 20% and 25%, respectively, compared to the conventional direct transmission. The AF protocol outperforms the DF mode for shorter transmissions between the relay and the destination cores, while the reverse is observed in other conditions. A hybrid protocol is then proposed to exploit the performance advantages of both relaying protocols to address the unbalanced distance between the cores, providing the maximal channel capacity close to the cutset bound. Finally, our approach is further validated in multi-relay WiNoCs where the communications of the remote cores is assisted by multiple intermediate cores along with the details of associated realistic channel model in emerging many-core SoCs

Fine-grained performance analysis of massive MTC networks with scheduling and data aggregation

Abstract. The Internet of Things (IoT) represents a substantial shift within wireless communication and constitutes a relevant topic of social, economic, and overall technical impact. It refers to resource-constrained devices communicating without or with low human intervention. However, communication among machines imposes several challenges compared to traditional human type communication (HTC). Moreover, as the number of devices increases exponentially, different network management techniques and technologies are needed. Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators not only collect data but also implement scheduling mechanisms to cope with scarce network resources. This thesis provides an overview of the most common IoT applications and the network technologies to support them. We describe the most important challenges in machine type communication (MTC). We use a stochastic geometry (SG) tool known as the meta distribution (MD) of the signal-to-interference ratio (SIR), which is the distribution of the conditional SIR distribution given the wireless nodes’ locations, to provide a fine-grained description of the per-link reliability. Specifically, we analyze the performance of two scheduling methods for data aggregation of MTC: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). The results show the fraction of users in the network that achieves a target reliability, which is an important aspect to consider when designing wireless systems with stringent service requirements. Finally, the impact on the fraction of MTDs that communicate with a target reliability when increasing the aggregators density is investigated