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.

Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications

Wireless body area sensor network is a sub-field of wireless sensor network. Wireless body area sensor network has come into existence after the development of wireless sensor network reached some ...

https://journals.sagepub.com/doi/pdf/10.1177/1550147718768994

The state-of-the-art wireless body area sensor networks: A survey:

Topology optimization against cascading failures on wireless sensor networks using a memetic algorithm

Propagation models are used to abstract the actual propagation characteristics of electromagnetic waves utilized for conveying information in a compact form (i.e., a model with a small number of parameters). The correct modeling of propagation and path loss is of paramount importance in wireless sensor network (WSN) system design and analysis [1]. Most of the important performance metrics commonly employed for WSNs, such as energy dissipation, route optimization, reliability, and connectivity, are affected by the utilized propagation model. However, in many studies on WSNs, overly simplistic and unrealistic propagation models are used. One of the reasons for the utilization of such impractical propagation models is the lack of awareness of experimentally available WSN-specific propagation and path-loss models. In this article, necessary succint background information is given on general wireless propagation modeling, and salient WSN-specific constraints on path-loss modeling are summarized. Building upon the provided background, an overview of the experimentally verified propagation models for WSNs is presented, and quantitative comparisons of propagation models employed in WSN research under various scenarios and frequency bands are provided.

Path-Loss Modeling for Wireless Sensor Networks: A review of models and comparative evaluations.

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e., coverage-aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered.

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Coverage protocols for wireless sensor networks: Review and future directions

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 Near-Ground Path Loss Modeling on Wireless Sensor Network Lifetime

A survey on packet size optimization for terrestrial, underwater, underground, and body area 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.

Sinan Kurt

Papers

Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications

Path-Loss Modeling for Wireless Sensor Networks: A review of models and comparative evaluations.

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

A survey on packet size optimization for terrestrial, underwater, underground, and body area sensor networks

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