Browsing by Author "Yildiz, Huseyin Ugur"

Now showing 1 - 5 of 5

Citation - Scopus: 29
A Hybrid Energy Harvesting Framework for Energy Efficiency in Wireless Sensor Networks Based Smart Grid Applications
(Institute of Electrical and Electronics Engineers Inc., 2018) Yildiz, Huseyin Ugur; Güngör, Vehbi Çağrı; Tavli, Bülent
In smart grid applications, Wireless Sensor Net-works (WSNs) which consist of battery limited sensor nodes are used on critical equipments of power distribution grids for monitoring purposes. WSN nodes have tight energy constraints hence it is important to reduce the energy consumption of sensor nodes due to harsh propagation characteristics of smart grid environment. One possible way to reduce the energy consumption is to utilize transmission power control where transmission powers are adjusted according to channel conditions. Another technique is to employ energy harvesting schemes to provide additional power for nodes by using environmental energy sources. Solar and electromagnetic energies are two possible environmental energy sources in outdoor substation environments. Solar energy can be efficiently exploited in a sunny day. On the other hand, electromagnetic energy can be used at any time. In this work, we propose a hybrid energy harvesting model that exploits both solar and electromagnetic energies and develop a Mixed Integer Programming (MIP) method to minimize the energy dissipation of sensor nodes. By using the MIP framework, we quantify the impact of the proposed hybrid energy harvesting model as well as transmission power control on the energy saving of nodes. © 2018 Elsevier B.V., All rights reserved.
Citation - WoS: 5
Node-Level Error Control Strategies for Prolonging the Lifetime of Wireless Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2021) Tekin, Nazli; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri
In Wireless Sensor Networks (WSNs), energy-efficiency and reliability are two critical requirements for attaining a long-term stable communication performance. Using error control (EC) methods is a promising technique to improve the reliability of WSNs. EC methods are typically utilized at the network-level, where all sensor nodes use the same EC method. However, improper selection of EC methods on some nodes in the network-level strategy can reduce the energy-efficiency, thus the lifetime of WSNs. In this study, a node-level EC strategy is proposed via mixed-integer programming (MIP) formulations. The MIP model determines the optimum EC method (i.e., automatic repeat request (ARQ), forward error correction (FEC), or hybrid ARQ (HARQ)) for each sensor node to maximize the network lifetime while guaranteeing a pre-determined reliability requirement. Five meta-heuristic approaches are developed to overcome the computational complexity of the MIP model. The performances of the MIP model and meta-heuristic approaches are evaluated for a wide range of parameters such as the number of nodes, network area, packet size, minimum desired reliability criterion, transmission power, and data rate. The results show that the node-level EC strategy provides at least 4.4% prolonged lifetimes and 4.0% better energy-efficiency than the network-level EC strategies. Furthermore, one of the developed meta-heuristic approaches (i.e., extended golden section search) provides lifetimes within a 3.9% neighborhood of the optimal solutions, reducing the solution time of the MIP model by 89.6%.
Citation - WoS: 23
Citation - Scopus: 28
On the Lifetime of Compressive Sensing Based Energy Harvesting in Underwater Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2019) Erdem, Huseyin Emre; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri
Recently, there has been a growing interest in academia and industry on the development of underwater acoustic sensor networks (UASNs) for scientific, commercial, and military purposes. Severe underwater channel conditions and limited battery energy of underwater nodes pose great challenges to prolong UASNs lifetime. Compressive sensing (CS), energy harvesting (EH), and transmission power control (TPC) are three promising solutions to improve UASNs lifetime. This paper aims to quantitatively investigate the joint impact of CS, EH, and TPC methods on the lifetime of UASNs. A novel Mixed Integer Programming framework is developed to maximize the network lifetime by joint consideration of CS, EH, and TPC. The performance results show that the impact of CS on the network lifetime is higher than that of EH when both methods are combined with TPC. Moreover, when all three methods are combined, the network lifetime can be extended up to three times as compared to the case when all three methods are not utilized.
Citation - WoS: 78
Citation - Scopus: 91
Packet Size Optimization for Lifetime Maximization in Underwater Acoustic Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2019) Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri; Tavli, Bulent
Recently, underwater acoustic sensor networks (UASNs) have been proposed to explore underwater environments for scientific, commercial, and military purposes. However, long propagation delays, high transmission losses, packet drops, and limited bandwidth in underwater propagation environments make realization of reliable and energy-efficient communication a challenging task for UASNs. To prolong the lifetime of battery-limited UASNs, two critical factors (i.e., packet size and transmission power) play vital roles. At one hand, larger packets are vulnerable to packet errors, while smaller packets are more resilient to such errors. In general, using smaller packets to avoid bit errors might be a good option. However, when small packets are used, more frames should be transmitted due to the packet fragmentation, and hence, network overhead and energy consumption increases. On the other hand, increasing transmission power reduces frame errors, but this would result in unnecessary energy consumption in the network. To this end, the packet size and transmission power should be jointly considered to improve the network lifetime. In this study, an optimization framework via an integer linear programming (ILP) has been proposed to maximize the network lifetime by joint optimization of the transmission power and packet size. In addition, a realistic link-layer energy consumption model is designed by employing the physical layer characteristics of UASNs. Extensive numerical analysis through the optimization model has been also performed to investigate the tradeoffs caused by the transmission power and packet size quantitatively.
Citation - WoS: 144
Citation - Scopus: 177
Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications
(IEEE-Inst Electrical Electronics Engineers Inc, 2017) Kurt, Sinan; Yildiz, Huseyin Ugur; Yigit, Melike; Tavli, Bulent; Gungor, Vehbi Cagri
Wireless sensor networks (WSNs) are envi-sioned to be an important enabling technology for smart grid (SG) due to the low cost, ease of deployment, and versatility of WSNs. Limited battery energy is the tightest resource constraint on WSNs. Transmission power control and data packet size optimization are powerful mechanisms for prolonging network lifetime and improving energy effi-ciency. Increasing transmission power will reduce the bit error rate (BER) on some links, however, utilizing the high-est power level will lead to inefficient use of battery energy because on links with low path loss achieving low BER is possible without the need to use the highest power level. Utilizing a large packet size is beneficial for increasing the payload-to-overhead ratio, yet, lower packet sizes have the advantage of lower packet error rate. Furthermore, trans-mission power level assignment and packet size selection are interrelated. Therefore, joint optimization of transmission power level and packet size is of utmost importance in WSN lifetime maximization. In this study, we construct a de-tailed link layer model by employing the characteristics of Tmote Sky WSN nodes and channel characteristics based on actual measurements of SG path loss for various envi-ronments. A novel mixed integer programming framework is created by using the aforementioned link layer model for WSN lifetime maximization by joint optimization of trans-mission power level and data packet size. We analyzed the WSN performance by systematic exploration of the parameter space for various SG environments through the numer-ical solutions of the optimization model.