Bluetooth Low Energy (BLE) is a wireless protocol well suited for ultralow-power sensors running on small batteries. It is optimized for low power communication and is not compatible with the original Bluetooth, referred to as Bluetooth Basic Rate (BR)/Enhanced Data Rate (EDR). BLE is described as a new protocol in the official Bluetooth 4.0 specification. It reuses many parts of the Bluetooth BR hardware and software stack to enable dual mode devices supporting Bluetooth BR/EDR and BLE. To design energy-efficient devices, the protocol provides a number of parameters that need to be optimized within an energy, latency and throughput design space. To minimize power consumption, the protocol parameters have to be optimized for a given application. Therefore, an energy-model that can predict the energy consumption of a BLE-based wireless device for different parameter value settings, is needed. As BLE differs from Bluetooth BR significantly, models for Bluetooth BR cannot be easily applied to the BLE protocol. Since the last one year, there have been a couple of proposals on energy models for BLE. However, none of them can model all the operating modes of the protocol. This paper presents a precise energy model of the BLE protocol, that allows the computation of a device's power consumption in all possible operating modes. To the best of our knowledge, our proposed model is not only one of the most accurate ones known so far (because it accounts for all protocol parameters), but it is also the only one that models all the operating modes of BLE. Furthermore, we present a sensitivity analysis of the different parameters on the energy consumption and evaluate the accuracy of the model using both discrete event simulation and actual measurements. Based on this model, guidelines for system designers are presented, that help choosing the right parameters for optimizing the energy consumption for a given application.

Neighbor discovery is the procedure using which two wireless devices initiate a first contact. In low power ad-hoc networks, radios are duty-cycled and the latency until a packet meets a reception phase of another device is determined by a random process. Most research considers slotted protocols, in which the points in time for reception are temporally coupled to beacon transmissions. In contrast, many recent protocols, such as ANT/ANT+ and Bluetooth Low Energy (BLE) use a slotless, periodic-interval based scheme for neighbor discovery. Here, one device periodically broadcasts packets, whereas the other device periodically listens to the channel. Both periods are independent from each other and drawn over continuous time. Such protocols provide 3 degrees of freedom (viz., the intervals for advertising and scanning and the duration of each scan phase). Though billions of existing BLE devices rely on these protocols, neither their expected latencies nor beneficial configurations with good latency-duty-cycle relations are known. Parametrizations for the participating devices are usually determined based on a "good guess". In this paper, we for the first time present a mathematical theory which can compute the neighbor discovery latencies for all possible parametrizations. Further, our theory shows that upper bounds on the latency can be guaranteed for all parametrizations, except for a finite number of singularities. Therefore, slotless, periodic interval-based protocols can be used in applications with deterministic latency demands, which have been reserved for slotted protocols until now. Our proposed theory can be used for analyzing the neighbor discovery latencies, for tweaking protocol parameters and for developing new protocols. arXiv:1509.04366v4 [cs.NI] 18 Aug 2017Maximum deviation (max(|dcomp − dsim|)) for mean/maximum latencies dcomp, dsimComputed/Simulated latency

Mobile devices apply neighbor discovery (ND) protocols to wirelessly initiate a first contact within the shortest possible amount of time and with minimal energy consumption. For this purpose, over the last decade, a vast number of ND protocols have been proposed, which have progressively reduced the relation between the time within which discovery is guaranteed and the energy consumption. In spite of the simplicity of the problem statement, even after more than 10 years of research on this specific topic, new solutions are still proposed even today. Despite the large number of known ND protocols, given an energy budget, what is the best achievable latency still remains unclear. This paper addresses this question and for the first time presents safe and tight, duty-cycle-dependent bounds on the worst-case discovery latency that no ND protocol can beat. Surprisingly, several existing protocols are indeed optimal, which has not been known until now. We conclude that there is no further potential to improve the relation between latency and duty-cycle, but future ND protocols can improve their robustness against packet collisions.The ND protocols proposed in the literature could progressively reduce the guaranteed worst-case latencies for every given energy-budget. For example, the Griassdi [13]-protocol proposed in 2017 is claimed to achieve by 87 % lower worst-case latencies than Searchlight-Striped [5], which has been proposed in 2012. However, despite the significant attention the ND problem has received in the literature, the fundamental question regarding the theoretically lowest possible worst-case latency that any ND protocol could guarantee still remains unanswered.Performance of ND Protocols: In the absence of bounds, comparisons among multiple ND protocols are difficult, because there is no common base. The results of such comparisons depend on the choice of protocols,The authors are with the Chair

In this paper, we present Smart 2 , an advanced smartphone charger that mitigates battery's capacity fading, which until now has usually been ignored. Smart 2 exploits the fact that many users charge their phones over night. Since the overnight charging duration is unnecessarily long, the battery is subjected to a high average state of charge (SOC), which accelerates battery aging. Therefore, we delay the charging adaptively to be done shortly before the phone is unplugged. With this scheme, clearly when averaged over the duration of the night, the average SOC is lower and hence aging is reduced. Indicators are a set alarm clock and/or statistics of previous usage. Similarly, we lower the maximum target SOC. To enable this, the main challenges are firstly to find a solution that does not negatively influence the usability and secondly to quantify the achieved savings in terms of aging mitigation. Towards this, we propose a novel charging scheme which can be implemented in the smartphone's firmware. Furthermore, we propose a modified battery charging device that can be used with almost all existing smart phone models. Using our proposed techniques, the average battery cycle life can be nearly doubled from 3.7 to 6.6 years.

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