Article Synchronising Energy Harvesting and Data Packets in a Wireless Sensor (original) (raw)

Synchronising Energy Harvesting and Data Packets in a Wireless Sensor

We consider a wireless sensor node that gathers energy through harvesting and reaps data through sensing. The node has a wireless transmitter that sends out a data packet whenever there is at least one “energy packet” and one “data packet”, where an energy packet represents the amount of accumulated energy at the node that can allow the transmission of a data packet. We show that such a system is unstable when both the energy storage space and the data backlog buffer approach infinity, and we obtain the stable stationary solution when both buffers are finite. We then show that if a single energy packet is not sufficient to transmit a data packet, there are conditions under which the system is stable, and we provide the explicit expression for the joint probability distribution of the number of energy and data packets in the system. Since the two flows of energy and data can be viewed as flows that are instantaneously synchronised, this paper also provides a mathematical analysis of a fundamental problem in computer science related to the stability of the “join” synchronisation primitive.

A Sensor Node with Energy Harvesting

We study the backlog of energy and of data packets in a sensor node that collects data and harvests energy, and using the energy to forward data packets. Assuuming that data transmission times are negligible, we compute the properties of energy and data backlogs and discuss some interesting system stability issues.

Energy Consumption Model for Data Processing and Transmission in Energy Harvesting Wireless Sensors

This paper studies energy harvesting wireless sensor nodes in which energy is gathered through harvesting process and data is gathered through sensing from the environment at random rates. These packets can be stored in node buffers as discrete packet forms which were previously introduced in " Energy Packet Network " paradigm. We consider a standby energy loss in the energy buffer (battery or capacitor) in a random rate, due to the fact that energy storages have self discharge characteristic. The wireless sensor node consumes Ke and Kt amount of harvested energy for node electronics (data sensing and processing operations) and wireless data transmission, respectively. Therefore, whenever a sensor node has less than Ke amount of energy, data can not be sensed and stored, and whenever there is more than Ke amount of energy, data is sensed and stored and also it could be transmitted immediately if the remaining energy is greater or equal than the Kt. We assume that the values of both Ke and Kt as one energy packet, which leads us a one-dimensional random walk modeling for the transmission system. We obtain stationary probability distribution as a product form solution and study on other quantities of interests. We also study on transmission errors among a set of M identical sensor with the presence of interference and noise.

Deterministic and Energy-Optimal Wireless Synchronization

Lecture Notes in Computer Science, 2011

We consider the problem of clock synchronization in a wireless setting where processors must powerdown their radios in order to save energy. In this setting, each processor has a radio device that is either on or off. When the radio device of a processor is on, it is able to communicate with other processors in its range. However, turning the radio on results in a significant waste of energy, even when listening. Energy efficiency is a central goal in wireless networks, especially if energy resources are severely limited. This is indeed the case in sensor networks, ad-hoc networks, and many other wireless network settings. Consequently, the main goal of multiple papers in wireless and sensor networks literature aims at achieving clock synchronization in an energy-efficient manner. In other words, the goal is to synchronize all clocks while minimizing the number of times a processor must switch its radio on. The problem of clock synchronization is an important problem in the field of distributed algorithms. In the current setting, the problem is to synchronize clocks of m processors that wake up in arbitrary time points, such that the maximum difference between wake up times is bounded by a positive integer n, where time intervals are appropriately discretized to allow communication of all processors that are awake in the same discrete time unit. (We remark that in this model we do not consider the issue of Broadcast Interference, which is a different problem known as radio broadcast problem.) The current model received a wide attention in sensor network literature. Currently, the best-known results for synchronization for single-hop networks of m processors is a randomized algorithm due to Bradonjic, Kohler and Ostrovsky [2] of O n/m • poly-log(n) awake times per processor and a lower bound of

Synchronization Uncertainty Contributions in Wireless Sensor Networks

2008 IEEE Instrumentation and Measurement Technology Conference, 2008

Time synchronization is of primary importance for the operation of wireless sensor networks (WSN): time measurements, coordinated actions and event ordering require common time on WSN nodes. Due to intrinsic energy limitations of wireless networks there is a need for new energy-efficient time synchronization solutions, different from the ones that have been developed for wired networks. In this work we investigated the trade-offs between time synchronization accuracy and energy saving in WSN. On the basis of that study we developed a power-efficient adaptive time synchronization strategy, that achieves a target synchronization accuracy at the expense of a negligible overhead. Also, we studied the energy benefits of periodic time synchronization in WSN employing synchronous wakeup schemes, and developed an algorithm that finds the optimal synchronization period to save energy. The proposed research improves state-of-the-art by exploring new ways to save energy while assuring high flexibility and reliable operation of WSN.

Wireless Sensor with Data and Energy Packets

We study an energy harvesting wireless sensor node which harvests energy and senses and transmits data. Both data and energy are represented as discrete quantities using the previously introduced in " Energy Packet Network " paradigm. For each data packet, the sensor requires and consumes Ke energy packets for sensing and storage and Kt energy packets for transmission. Assuming random processes for sensing and energy harvesting, we obtain a two-dimensional random walk model and reduce its complexity using companion matrices and matrix algebra techniques. The resulting solution allows us to obtain, in steady-state, all the metrics of interest such as the backlog of energy and data in the sensor. We also consider the case when M sensors operate in proximity and create some interference for each other.

Transmission policies for energy harvesting sensors with time-correlated energy supply

This paper considers a wireless sensor powered by an energy harvesting device, which reports data of varying importance to its receiver. Modeling the ambient energy supply by a two-state Markov chain ("GOOD" and "BAD"), assuming a finite battery capacity constraint, and associating data transmission with a given energy cost, we propose low-complexity transmission policies, that achieve near-optimal performance in terms of the average long-term importance of the reported data. In particular, we derive the performance of the Balanced Policy (BP), which adapts the transmission probability to the harvesting state, such that energy harvesting and consumption are balanced. Our analysis demonstrates that the performance of the BP largely depends on the power-to-depletion, defined as the power that a fully charged battery can supply on average over a BAD period. Numerical results show that the optimal BP achieves nearoptimal performance and that a BP which avoids energy overflow further reduces the gap with respect to the globally optimal policy. A heuristic BP, based on the analysis of a system with a deterministic and periodic energy supply, is also proposed, and the parallels between the deterministic system and its stochastic counterpart are discussed.

Stability of Control Systems with Feedback from Energy Harvesting Sensors

arXiv: Optimization and Control, 2017

In this paper, we study the problem of certifying the stability of a closed loop system which receives feedback from an energy harvesting sensor. This is important, as energy harvesting sensors are recharged stochastically, and may only be able to provide feedback intermittently. Thus, stabilizing plants with feedback provided by energy harvesting sensors is challenging in that the feedback signal is only available stochastically, complicating the analysis of the closed-loop system. As the main contribution of the paper, we show that for a broad class of energy harvesting processes and transmission policies, the system can be modeled as a Markov jump linear system (MJLS), which thereby enables a rigorous stability analysis. We discuss the types of transmission policies and energy harvesting processes which can be accommodated in detail, demonstrating the generality of the results.