ReNEW A Practical Module For Reliable Routing in Networks of Energy-harvesting Wireless Sensors
Abstract : Many Internet of Things smart-* applications are being powered solely through ambient energy-harvested energy. These applications require periodic data collection with low latency and high reliability. Since the energy is harvested in small amounts from ambient sources and is stochastic in nature, it is extremely challenging to achieve low latency and high reliability for such applications. To this end, we propose a distributed, energy-management module called ReNEW, for Constructive Interference (CI) based protocols that utilizes the available energy effectively in order to achieve our target of increased reliability in EH-WSN, especially in the low harvesting regimes. We choose CI-based protocols to leverage the low latency guarantees. Specifically, we propose a Markov decision model to maximize the energy utility in the infinite horizon by allocating energy optimally. To this end, we also propose a threshold optimal policy. As we find that just a energy scheduler cannot achieve the goal, we also propose distributed techniques to conserve energy on the redundant nodes in the network, and dynamically activate them based on feedback. We also improve the performance of CI by adapting the transmit powers on nodes. We implement and evaluate ReNEW on Indriya testbed for real-world scenarios. We show that in a network of 20 source nodes out of the 30 nodes in the network can perform periodic data collection with an improvement of 2.5 times higher packet reception ratio as compared to LWB. This is one of the worst case scenarios as the harvested energy is as low as 50uJ/s and packets of size 100B is sent every 30 s. Furthermore, in this scenario, ReNEW saves around 25% higher residual energy on the average as compared to the standard LWB. In a nutshell, by integrating ReNEW with CI based protocols, we enable guaranteed latency and increased reliability for the batteryless EH-WSNs.
? Harvesting energy from the surroundings of the existing sources has become one of the promising technologies.
? Power density is the main parameter to harvest energy from any of the existing energy resources, and the sunlight has the maximum density.
? They have developed an analytical model to estimate energy consumed during route establishment and existing simulation results that claim better performance and energy efficiency.
? Therefore various attenuation models exists based upon the different operating conditions such as indoor, outdoor and free space.
? The scheme is based on to optimize the energy consumed and provide end-to end reliability for WSN.
? It is important to clearly define the performance metrics and design requirements that impact EH-WSNs, given that energy is no longer limited in the same way.
? Preventing, managing, or at least mitigating their effects is a major challenge due to the unpredictable, short-span, and high-impact nature of these disasters.
? Due to the prediction-based nature of energy-harvesting problems, some of the algorithms assume that either the full knowledge of the harvested energy in the future is known at the transmitter, or both the history and the future harvested energy are available prior to the communication.
? WSNs can be used to monitor the environment to provide information that can aid in finding solutions to these issues.
• The design proposes optimization scheme for direct transmission, joint routing scheme for single-relay cooperation and power allocation scheme for multi-relay cooperation scenarios .
• The proposed RF energy harvesting technique is implemented for many electronic devices like LED, scientific calculator and battery charging.
• The proposed converter consists of cross coupled rectifier with differential- drive and a four-bit capacitor array.
• They propose to increase the efficiency over different frequency ranges with reduced size of RF rectifier circuit.
• They proposed a frame work known as MIP (mixed integer programming) to decrease energy consumed by the sensor nodes.
? A high vibrational acceleration, wide range frequency band, and an adaptive resonant frequency tracker are the main requirements to design a high performance vibration energy-harvesting system.
? Design considerations include sensor nodes robustness (in terms of storage, charge and discharge rate), low price, MPPT performance, and data transmission mechanism to achieve a longer lifetime of the WSN.
? In Dynamic Power Management (DPM), which is another technique for power management, the main focus is on reducing the power consumption while maintaining the network performance at a reasonable level by switching the nodes to different energy states.
? These include the size of the energy buffer, the operational performance level when in energy-neutral mode, and the measurement capabilities required in the hardware for harvesting the energy.
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