Huseyin Ugur Yildiz

Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications

Wireless sensor networks (WSNs) are envisioned 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 efficiency. Increasing transmission power will reduce the bit error rate (BER) on some links, however, utilizing the highest 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, transmission 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 detailed 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 environments. A novel mixed integer programming framework is created by using the aforementioned link layer model for WSN lifetime maximization by joint optimization of transmission power level and data packet size. We analyzed the WSN performance by systematic exploration of the parameter space for various SG environments through the numerical solutions of the optimization model.

Transmission Power Control for Link-Level Handshaking in Wireless Sensor Networks

In practical wireless sensor networks (WSNs), the main mechanism for link-level data exchange is through handshaking. To maximize the network lifetime, the transmission power levels for both data and acknowledgement (ACK) packets should be selected optimally. If the highest transmission power level is selected then the 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 paper, 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 never fail). Our results show that the global optimal assignment of data and ACK packets can be replaced with link scope power level assignment strategies without any significant deterioration of network lifetime. The assumption that ACK packets do not fail is shown to be misleading.

Impact of Limiting Hop Count on the Lifetime of Wireless Sensor Networks

In this study, we present a novel family of mixed integer programming (MIP) models to analyze the effects of limiting hop count on Wireless Sensor Network (WSN) lifetime. We performed analysis to uncover the trade-off between minimizing the number of hops and maximizing the network lifetime by exploring the parameter space through numerical evaluations of the optimization models. Our results reveal that minimum hop routing leads to significant decrease in network lifetime (up to 40%) when compared to the maximum network lifetime obtained without any restrictions on hop count. However, the decrease in network lifetime is negligible if the minimum hop routing criterion is modestly relaxed (e.g., 3% decrease in network lifetime is possible if the minimum hop count is increased by 15%).

Maximizing Wireless Sensor Network lifetime by communication/computation energy optimization of non-repudiation security service

In a typical Wireless Sensor Network (WSN) application, the basic communication service is the transportation of the data collected from sensors to the base station. For prolonging the network lifetime, energy efficiency should be one of the primary attributes of such a service. The amount of data transmitted by a node usually depends on how much local processing is performed. As an example, in visual sensor networks the amount of image processing on the nodes affects the amount of data transmitted to the base station (i.e., the higher the computation, the lower the communication and vice versa). Hence in order to improve energy efficiency and prolong the network lifetime this communication/computation energy trade-off must be analyzed. This analysis may be performed at the network-level (i.e., all nodes in the network use the same strategy) or at a node level (i.e., sensor nodes do not necessarily have identical strategies). The latter is more fine-grained allowing different nodes to implement different solutions. To guide designers in effectively using these trade-offs to prolong network lifetime, we develop a novel Mixed Integer Programming (MIP) framework. We show that the optimal node level strategy can extend network lifetime more than 20% as compared to a network-level optimal strategy. We also develop a computationally efficient heuristic to overcome the very high computational requirements of the proposed MIP model.

Joint Optimization of Transmission Power Level and Packet Size for WSN Lifetime Maximization

In pursuit of better energy efficiency and enhanced network lifetime in wireless sensor networks (WSNs), two crucial factors are data packet size and transmission power level. On one hand, smaller packet size reduces the overall impact of bit error rates on packet loss. However, the consequence of smaller packet size is fragmentation into more data packets and thereby dissipation of increased energy. Hence, there emerges a delicate engineering tradeoff in deciding the data packet size, where both low and high data packet size decisions lead to certain energy inefficiency issues. On the other hand, increasing transmission power level decreases packet loss probability, which is another decision variable to optimize for maximizing network lifetime. Joint consideration of these two factors exacerbates the complexity of the optimization problem for the objective of the network lifetime maximization. In this paper, we develop a realistic WSN link layer model built on top of the empirically verified energy dissipation characteristics of Mica2 motes and WSN channel models. We make use of the aforementioned link layer model to design a novel mixed integer programming (MIP) framework for the joint optimization of transmission power level and data packet size to take up the challenge introduced above. Numerical evaluations of the MIP framework with the analysis of the results over a large parameter space are performed to characterize the effects of joint optimization of packet size and power level on WSN lifetime.

The Impact of Near-Ground Path Loss Modeling on Wireless Sensor Network Lifetime

Network lifetime is the ultimate objective in evaluating the performance of Wireless Sensor Networks (WSNs). To assess the network lifetime correctly for a particular WSN deployment, utilizing realistic abstractions for modeling various aspects of system components are crucial. The overwhelming majority of the studies on the WSN lifetime maximization utilize well known theoretical path loss models like the two-ray model, however, such models do not lead to realistic path loss results. In this study, we formulate a detailed link level model of WSNs utilizing Mica2 motes and, based on the link layer model, we construct a novel Mixed Integer Program (MIP) to analyze the effects of path loss models on the WSN lifetime. By exploring the parameter space through numerical evaluations of the MIP model, we characterize the impact of path loss models on the WSN lifetime.

The Impact of Incapacitation of Multiple Critical Sensor Nodes on Wireless Sensor Network Lifetime

Wireless sensor networks (WSNs) are envisioned to be utilized in many application areas, such as critical infrastructure monitoring, and therefore, WSN nodes are potential targets for adversaries. Network lifetime is one of the most important performance indicators in WSNs. The possibility of reducing the network lifetime significantly by eliminating a certain subset of nodes through various attacks will create the opportunity for the adversaries to hamper the performance of WSNs with a low risk of detection. However, the extent of reduction in network lifetime due to elimination of a group of critical sensor nodes has never been investigated in the literature. Therefore, in this letter, we create two novel algorithms based on a linear programming framework to model and analyze the impact of critical node elimination attacks on WSNs and explore the parameter space through numerical evaluations of the algorithms. Our results show that critical node elimination attacks can significantly shorten the network lifetime.

Optimal transmission power level sets for lifetime maximization in wireless sensor networks

In Wireless Sensor Networks (WSNs) data transmission by using the highest available power level leads to energy wastage on certain links. Therefore, assigning the optimal transmission power for each link in a WSN is necessary to prolong the network lifetime. Transceivers of WSN nodes perform transmission power control by selecting one of the available discrete transmission power levels. As such, the power level set of a WSN transceiver is an important tool for achieving energy efficiency, yet, the power level sets are determined without considering their effects on WSN lifetime. In this study, we investigate the characteristics of the optimal transmission power level sets from WSN lifetime maximization perspective.

Prolonging Wireless Sensor Network Lifetime by Optimal Utilization of Compressive Sensing

In a typical Wireless Sensor Network (WSN) application, sensor nodes gather data from the environment and convey the collected data towards the base station. It is possible to perform certain signal processing operations on raw data on each sensor node before transmission so that the amount of transmitted data bits is reduced. The amount of transmitted data usually depends on how much processing is performed on each node. Less processing results in more data to be transmitted and vice versa. However, more complex computation operations dissipate more energy. Hence, utilization of signal processing operations should be evaluated carefully by considering both their computation costs and the amount of data reduction they achieve. It is also possible to employ different signal processing techniques at different nodes, hence, optimal assignment of signal processing algorithms can be assessed at the network-level (i.e., all nodes adopts a single signal processing technique during the entire lifetime) or at the node-level (i.e., allowing different nodes to implement different solutions during lifetime). In this study, we develop a novel Mixed Integer Programming (MIP) framework to quantitatively investigate the effects of utilizing traditional transform coding (TC) based and compressive sensing (CS) based signal processing techniques (network-level and node- level) on WSN lifetime. We explore the parameter space consisting of network size, node density, and signal sparsity level through the numerical evaluations of the proposed novel MIP model.

Role of Unidirectionality and Reverse Path Length on Wireless Sensor Network Lifetime

Transceiver characteristics, asymmetric interference, and various properties of electromagnetic propagation environment create unidirectional links in wireless sensor networks (WSNs), especially in extreme environments. Utilization of unidirectional links is shown to improve network connectivity and lifetime. In practical WSNs, link level data exchange is performed through handshaking. However, a special handshake mechanism, where acknowledgment (ACK) packets are conveyed through a multihop reverse path, is necessary to be able to utilize unidirectional links. In this mechanism, hop length of the reverse path is a key design parameter because by allowing longer reverse paths, more unidirectional links can be utilized. However, increasing the reverse path hop length increases the energy overhead due to the extra ACK packets. Furthermore, complexity of maintaining the data flow also increases as the allowed maximum reverse path hop length increases. In this paper, we seek the answer for the following question: what is the optimum number of hops allowed for the reverse path hop length in WSNs? We created a novel mixed integer programming (MIP) framework to characterize the impact of reverse path hop length on WSN lifetime and performed extensive numerical analysis. Our results show that reverse path hop length has a significant impact on WSN lifetime.