Bulent Tavli | TOBB University of Economics and Technology (original) (raw)

Papers by Bulent Tavli

2020 28th Signal Processing and Communications Applications Conference (SIU), 2020

Network lifetime has been the most commonly employed metric for characterization of Wireless Sens... more Network lifetime has been the most commonly employed metric for characterization of Wireless Sensor Networks (WSNs) in the literature. Network reliability is also an important aspect of WSNs, especially, deployed for critical missions. However, there is a tradeoff between maximizing the network lifetime and reliability. In this study, we investigate the impact of increasing network reliability in terms of k-connectivity and network lifetime through a mathematical programming framework. We explored a large parameter space to quantitatively characterize this tradeoff. Our results reveal that increasing k leads to significant decrease of network lifetime due to the necessity to utilize energy inefficient routing paths.

2022 30th Signal Processing and Communications Applications Conference (SIU)

Applied Mechanics and Materials, 2013

Progress as well as integration of wireless communication technology, computer technology and sem... more Progress as well as integration of wireless communication technology, computer technology and semiconductor technology, can integrate information such as the perception,acquisition and data processing in a very limited volume [. With the rapid development of wireless technology,wireless sensor networks greatly extends the applications of sensor network and Internet of Things as well as the new challenges to wireless communication technology. We will use STC12LE4052AD microcontroller and ultra-low power radio frequency chip nRF24AP2 embedded ANT protocol stack to complete the development of wireless sensor nodes in this paper.

2017 25th Signal Processing and Communications Applications Conference (SIU), 2017

Wireless Sensor Networks (WSN) are used in various critical monitoring applications such as milit... more Wireless Sensor Networks (WSN) are used in various critical monitoring applications such as military safety, environmental surveillance, etc. In such scenarios, it is common that WSN nodes are threatened by potential adversaries. Since the network lifetime is known to be the one of the most important performance metrics in WSNs, capturing the most critical nodes and incapacitating these nodes by various attacks may significantly reduce network lifetime. WSN lifetime reduction due to the elimination of the most critical sensor node set has never been investigated in the literature. In this study, we proposed two Linear Programming (LP) based algorithms to analyze the impact of capturing multiple critical nodes on WSN lifetime through numeric evaluations. Our results reveal that capturing the multiple critical nodes in WSN degrades the network lifetime greatly.

2020 28th Telecommunications Forum (TELFOR), 2020

Research on Underwater Sensor Networks (UWSNs) have been increasing drastically due to their sign... more Research on Underwater Sensor Networks (UWSNs) have been increasing drastically due to their significant potential for solving technically challenging problems. However, the challenging operating conditions such as underwater transmission delay, severe path loss, noise, and limited operating frequency render the realization of efficient UWSNs challenging. Surface Gateway (SG) deployment becomes one of the promising solutions to mitigate such challenges. In this paper, the optimal positioning of an SG to maximize the sensor coverage is investigated. The optimal location is compared with the benchmark location computed by averaging the location of underwater sensors. The coverage performances of solutions by using both of these approaches are comparatively investigated in terms of different numbers of underwater sensor nodes and transmission power levels.

IEEE Transactions on Reliability, 2018

IEEE Sensors Journal, 2017

Enabling Real-Time Mobile Cloud Computing through Emerging Technologies

For military communication systems, it is important to achieve robust and energy efficient real-t... more For military communication systems, it is important to achieve robust and energy efficient real-time communication among a group of mobile users without the support of a pre-existing infrastructure. Furthermore, these communication systems must support multiple communication modes, such as unicast, multicast, and network-wide broadcast, to serve the varied needs in military communication systems. One use for these military communication systems is in support of real-time mobile cloud computing, where the response time is of utmost importance; therefore, satisfying real-time communication requirements is crucial. In this chapter, we present a brief overview of military tactical communications and networking (MTCAN). As an important example of MTCAN, we present the evolution of the TRACE family of protocols, describing the design of the TRACE protocols according to the tactical communications and networking requirements. We conclude the chapter by identifying how the TRACE protocols c...

the main mechanism for link level data exchange is through handshaking. To maximize the network l... more the main mechanism for link level data exchange is through handshaking. To maximize the network lifetime, transmission power levels for both data and acknowledgement (ACK) packets should be selected optimally. If the highest transmission power level is selected then handshake failure is minimized, however, minimizing handshake failure does not necessarily result in the maximized lifetime due to the fact that for some links selection of the maximum transmission power may not be necessary. In this study we investigate the impact of optimal transmission power assignment for data and ACK packets on network lifetime in WSNs. We built a novel family of mathematical programming formulations to accurately model the energy dissipation in WSNs under practical assumptions by considering a wide range of energy dissipation mechanisms. We also investigate the validity of a commonly made assumption in wireless communication and networking research: lossless feedback channel (i.e., ACK packets neve...

2017 25th Signal Processing and Communications Applications Conference (SIU), 2017

All communications networks, in general, and Wireless Sensor Networks (WSNs), in particular, need... more All communications networks, in general, and Wireless Sensor Networks (WSNs), in particular, need time synchronization for fulfilling the stringent requirements of the services they are providing. Time synchronization in WSNs is needed for multiple purposes (e.g., sleep-wakeup scheduling, event detection annotation). In literature, various time synchronization protocols for WSNs are proposed and some of these designs are evaluated in experimental testbeds. However, multi-hop time synchronization in WSNs have never been investigated experimentally. Therefore, to fill the gap in the WSN literature, in this study, we present the design and implementation of a novel time synchronization technique. Furthermore, we investigate the performance of the proposed technique through direct experimentation. Our results reveal the superior performance of our technique.

Wireless sensor networks (WSNs) consist of tiny sensor nodes distributed over a specific geograph... more Wireless sensor networks (WSNs) consist of tiny sensor nodes distributed over a specific geographical area. Eavesdropping can be considered as an attack against WSNs when an adversary node overhears the transmissions among the sensor nodes. Hence a WSN needs to minimize the risk of overhearing in order to operate safely. One of the most important performance metrics of WSNs is network lifetime. Decreasing the transmission power levels of the nodes in order to reduce the overhearing can negatively affect the network lifetime due to the suboptimal routing paths that are used. In this study, two optimization models are developed to jointly reduce eavesdropping and increase the network lifetime. The analysis of the relationship between eavesdropping and network lifetime is investigated by using the proposed optimization models. As a result of this study, it was observed that the minimum reduction of eavesdropping causes a significant decrement in network lifetime and when the overhearin...

2018 26th Telecommunications Forum (TELFOR), 2018

Reliability and network lifetime maximization are two important objectives when designing a Wirel... more Reliability and network lifetime maximization are two important objectives when designing a Wireless Sensor Network (WSN). However, these two are conflicting objectives. To increase the reliability maintaining mathbfk\mathbf{k}mathbfk-connectivity is necessary, yet, for higher mathbfk\mathbf{k}mathbfk values transmission power should be kept at the maximum which reduces the lifetime. In this study we investigate the reliability versus lifetime tradeoff.

2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015

Time synchronization is a vitally important service for all distributed systems. Wireless Sensor ... more Time synchronization is a vitally important service for all distributed systems. Wireless Sensor Networks (WSNs), which, generally, are designed to operate with stringent set of constraints, require time synchronization services especially for accomplishing the functionality expected from them. In literature there are various time synchronization protocols designed specifically for WSNs. Some of these protocols are also evaluated through direct experimentation. In this study, we propose a novel time synchronization protocol (DLWTS: Distributed Light Weight Time Synchronization for Wireless Sensor Networks), which is light-weight, reliable, accurate, and designed to operate in a distributed fashion. We conducted extensive experimental analysis to quantify the performance of the DLWTS protocol.

IEEE Sensors Journal, 2013

Proceedings of the 2nd International Conference on Robotic Communication and Coordination, 2009

To address the ever-growing connectivity demands of wireless communications, the adoption of inge... more To address the ever-growing connectivity demands of wireless communications, the adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base Stations (BSs), is imperative. In general, the location of a UAV Base Station (UAV-BS) is determined by optimization algorithms, which have high computationally complexities and place heavy demands on UAV resources. In this paper, we show that a Convolutional Neural Network (CNN) model can be trained to infer the location of a UAV-BS in real time. In so doing, we create a framework to determine the UAV locations that considers the deployment of Mobile Users (MUs) to generate labels by using the data obtained from an optimization algorithm. Performance evaluations reveal that once the CNN model is trained with the given labels and locations of MUs, the proposed approach is capable of approximating the results given by the adopted optimization algorithm with high fidelity, outperforming Reinforcement Learning (RL)-base...

2018 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), 2018

ArXiv, 2021

To address the ever-growing connectivity demands of wireless communications, the adoption of inge... more To address the ever-growing connectivity demands of wireless communications, the adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base Stations (BSs), is imperative. In general, the location of a UAV Base Station (UAV-BS) is determined by optimization algorithms, which have high computationally complexities and place heavy demands on UAV resources. In this paper, we show that a Convolutional Neural Network (CNN) model can be trained to infer the location of a UAV-BS in real time. In so doing, we create a framework to determine the UAV locations that considers the deployment of Mobile Users (MUs) to generate labels by using the data obtained from an optimization algorithm. Performance evaluations reveal that once the CNN model is trained with the given labels and locations of MUs, the proposed approach is capable of approximating the results given by the adopted optimization algorithm with high fidelity, outperforming Reinforcement Learning (RL)-base...

2020 28th Signal Processing and Communications Applications Conference (SIU), 2020

Network lifetime has been the most commonly employed metric for characterization of Wireless Sens... more Network lifetime has been the most commonly employed metric for characterization of Wireless Sensor Networks (WSNs) in the literature. Network reliability is also an important aspect of WSNs, especially, deployed for critical missions. However, there is a tradeoff between maximizing the network lifetime and reliability. In this study, we investigate the impact of increasing network reliability in terms of k-connectivity and network lifetime through a mathematical programming framework. We explored a large parameter space to quantitatively characterize this tradeoff. Our results reveal that increasing k leads to significant decrease of network lifetime due to the necessity to utilize energy inefficient routing paths.

2022 30th Signal Processing and Communications Applications Conference (SIU)

Applied Mechanics and Materials, 2013

Progress as well as integration of wireless communication technology, computer technology and sem... more Progress as well as integration of wireless communication technology, computer technology and semiconductor technology, can integrate information such as the perception,acquisition and data processing in a very limited volume [. With the rapid development of wireless technology,wireless sensor networks greatly extends the applications of sensor network and Internet of Things as well as the new challenges to wireless communication technology. We will use STC12LE4052AD microcontroller and ultra-low power radio frequency chip nRF24AP2 embedded ANT protocol stack to complete the development of wireless sensor nodes in this paper.

2017 25th Signal Processing and Communications Applications Conference (SIU), 2017

Wireless Sensor Networks (WSN) are used in various critical monitoring applications such as milit... more Wireless Sensor Networks (WSN) are used in various critical monitoring applications such as military safety, environmental surveillance, etc. In such scenarios, it is common that WSN nodes are threatened by potential adversaries. Since the network lifetime is known to be the one of the most important performance metrics in WSNs, capturing the most critical nodes and incapacitating these nodes by various attacks may significantly reduce network lifetime. WSN lifetime reduction due to the elimination of the most critical sensor node set has never been investigated in the literature. In this study, we proposed two Linear Programming (LP) based algorithms to analyze the impact of capturing multiple critical nodes on WSN lifetime through numeric evaluations. Our results reveal that capturing the multiple critical nodes in WSN degrades the network lifetime greatly.

2020 28th Telecommunications Forum (TELFOR), 2020

Research on Underwater Sensor Networks (UWSNs) have been increasing drastically due to their sign... more Research on Underwater Sensor Networks (UWSNs) have been increasing drastically due to their significant potential for solving technically challenging problems. However, the challenging operating conditions such as underwater transmission delay, severe path loss, noise, and limited operating frequency render the realization of efficient UWSNs challenging. Surface Gateway (SG) deployment becomes one of the promising solutions to mitigate such challenges. In this paper, the optimal positioning of an SG to maximize the sensor coverage is investigated. The optimal location is compared with the benchmark location computed by averaging the location of underwater sensors. The coverage performances of solutions by using both of these approaches are comparatively investigated in terms of different numbers of underwater sensor nodes and transmission power levels.

IEEE Transactions on Reliability, 2018

IEEE Sensors Journal, 2017

Enabling Real-Time Mobile Cloud Computing through Emerging Technologies

For military communication systems, it is important to achieve robust and energy efficient real-t... more For military communication systems, it is important to achieve robust and energy efficient real-time communication among a group of mobile users without the support of a pre-existing infrastructure. Furthermore, these communication systems must support multiple communication modes, such as unicast, multicast, and network-wide broadcast, to serve the varied needs in military communication systems. One use for these military communication systems is in support of real-time mobile cloud computing, where the response time is of utmost importance; therefore, satisfying real-time communication requirements is crucial. In this chapter, we present a brief overview of military tactical communications and networking (MTCAN). As an important example of MTCAN, we present the evolution of the TRACE family of protocols, describing the design of the TRACE protocols according to the tactical communications and networking requirements. We conclude the chapter by identifying how the TRACE protocols c...

the main mechanism for link level data exchange is through handshaking. To maximize the network l... more the main mechanism for link level data exchange is through handshaking. To maximize the network lifetime, transmission power levels for both data and acknowledgement (ACK) packets should be selected optimally. If the highest transmission power level is selected then handshake failure is minimized, however, minimizing handshake failure does not necessarily result in the maximized lifetime due to the fact that for some links selection of the maximum transmission power may not be necessary. In this study we investigate the impact of optimal transmission power assignment for data and ACK packets on network lifetime in WSNs. We built a novel family of mathematical programming formulations to accurately model the energy dissipation in WSNs under practical assumptions by considering a wide range of energy dissipation mechanisms. We also investigate the validity of a commonly made assumption in wireless communication and networking research: lossless feedback channel (i.e., ACK packets neve...

2017 25th Signal Processing and Communications Applications Conference (SIU), 2017

All communications networks, in general, and Wireless Sensor Networks (WSNs), in particular, need... more All communications networks, in general, and Wireless Sensor Networks (WSNs), in particular, need time synchronization for fulfilling the stringent requirements of the services they are providing. Time synchronization in WSNs is needed for multiple purposes (e.g., sleep-wakeup scheduling, event detection annotation). In literature, various time synchronization protocols for WSNs are proposed and some of these designs are evaluated in experimental testbeds. However, multi-hop time synchronization in WSNs have never been investigated experimentally. Therefore, to fill the gap in the WSN literature, in this study, we present the design and implementation of a novel time synchronization technique. Furthermore, we investigate the performance of the proposed technique through direct experimentation. Our results reveal the superior performance of our technique.

Wireless sensor networks (WSNs) consist of tiny sensor nodes distributed over a specific geograph... more Wireless sensor networks (WSNs) consist of tiny sensor nodes distributed over a specific geographical area. Eavesdropping can be considered as an attack against WSNs when an adversary node overhears the transmissions among the sensor nodes. Hence a WSN needs to minimize the risk of overhearing in order to operate safely. One of the most important performance metrics of WSNs is network lifetime. Decreasing the transmission power levels of the nodes in order to reduce the overhearing can negatively affect the network lifetime due to the suboptimal routing paths that are used. In this study, two optimization models are developed to jointly reduce eavesdropping and increase the network lifetime. The analysis of the relationship between eavesdropping and network lifetime is investigated by using the proposed optimization models. As a result of this study, it was observed that the minimum reduction of eavesdropping causes a significant decrement in network lifetime and when the overhearin...

2018 26th Telecommunications Forum (TELFOR), 2018

Reliability and network lifetime maximization are two important objectives when designing a Wirel... more Reliability and network lifetime maximization are two important objectives when designing a Wireless Sensor Network (WSN). However, these two are conflicting objectives. To increase the reliability maintaining mathbfk\mathbf{k}mathbfk-connectivity is necessary, yet, for higher mathbfk\mathbf{k}mathbfk values transmission power should be kept at the maximum which reduces the lifetime. In this study we investigate the reliability versus lifetime tradeoff.

2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015

Time synchronization is a vitally important service for all distributed systems. Wireless Sensor ... more Time synchronization is a vitally important service for all distributed systems. Wireless Sensor Networks (WSNs), which, generally, are designed to operate with stringent set of constraints, require time synchronization services especially for accomplishing the functionality expected from them. In literature there are various time synchronization protocols designed specifically for WSNs. Some of these protocols are also evaluated through direct experimentation. In this study, we propose a novel time synchronization protocol (DLWTS: Distributed Light Weight Time Synchronization for Wireless Sensor Networks), which is light-weight, reliable, accurate, and designed to operate in a distributed fashion. We conducted extensive experimental analysis to quantify the performance of the DLWTS protocol.

IEEE Sensors Journal, 2013

Proceedings of the 2nd International Conference on Robotic Communication and Coordination, 2009

To address the ever-growing connectivity demands of wireless communications, the adoption of inge... more To address the ever-growing connectivity demands of wireless communications, the adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base Stations (BSs), is imperative. In general, the location of a UAV Base Station (UAV-BS) is determined by optimization algorithms, which have high computationally complexities and place heavy demands on UAV resources. In this paper, we show that a Convolutional Neural Network (CNN) model can be trained to infer the location of a UAV-BS in real time. In so doing, we create a framework to determine the UAV locations that considers the deployment of Mobile Users (MUs) to generate labels by using the data obtained from an optimization algorithm. Performance evaluations reveal that once the CNN model is trained with the given labels and locations of MUs, the proposed approach is capable of approximating the results given by the adopted optimization algorithm with high fidelity, outperforming Reinforcement Learning (RL)-base...

2018 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), 2018

ArXiv, 2021

To address the ever-growing connectivity demands of wireless communications, the adoption of inge... more To address the ever-growing connectivity demands of wireless communications, the adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base Stations (BSs), is imperative. In general, the location of a UAV Base Station (UAV-BS) is determined by optimization algorithms, which have high computationally complexities and place heavy demands on UAV resources. In this paper, we show that a Convolutional Neural Network (CNN) model can be trained to infer the location of a UAV-BS in real time. In so doing, we create a framework to determine the UAV locations that considers the deployment of Mobile Users (MUs) to generate labels by using the data obtained from an optimization algorithm. Performance evaluations reveal that once the CNN model is trained with the given labels and locations of MUs, the proposed approach is capable of approximating the results given by the adopted optimization algorithm with high fidelity, outperforming Reinforcement Learning (RL)-base...