Duty cycle adapted MAC for Wireless Sensor Networks with energy harvesting

Radio frequency energy transfer (RET) has been proposed as a promising solution to power sensor nodes in wireless sensor networks (WSNs). However, RET has a significant drawback to be directly applied to WSNs, i.e., unfairness in the achieved throughput among sensor nodes due to the difference of their energy harvesting rates that strongly depend on the distance between the energy emitting node and the energy harvesting nodes. The unfairness problem should be properly taken into account to mitigate the drawback caused from the features of RET. To resolve this issue, in this paper, we propose a medium access control (MAC) protocol for WSNs based on RET with two distinguishing features: energy adaptive (EA) duty cycle management that adaptively manages the duty cycle of sensor nodes according to their energy harvesting rates and EA contention algorithm that adaptively manages contentions among sensor nodes considering fairness. Through analysis and simulation, we show that our MAC protocol works well under the RET environment. Finally, to show the feasibility of WSNs with RET, we test our MAC protocol with a prototype system in a real environment.

Recent advances in wireless communications and sensor technologies have enabled the development of low-cost wireless sensor networks (WSNs) for a wide range of applications. Medium access control (MAC) protocols play a crucial role in WSNs by enabling the sharing of scarce wireless bandwidth efficiently and fairly. This article provides a survey of the literature on MAC protocols for WSNs. We first briefly describe the unique features of WSNs. We then review representative MAC protocols from the following four categories: contention-based protocols, contention-free (scheduled-based) protocols, hybrid protocols , and preamble sampling protocols. Our discussions focus on the background, main features, operation procedures, major design issues, and the advantages and disadvantages of these protocols. We also present an analysis of the inherent and desirable features of the protocols, and the key challenges of MAC technology for WSNs. Finally, we present our view on future research directions for WSN MAC protocols in a reader-friendly way using illustrative diagrams.

Medium Access Control (MAC) protocol is one of the key network protocols that ensure Wireless Sensor Networks (WSNs) maintain high performance during communication. MAC protocol design plays an important role in improving the performances of the whole network. First, Wireless Passive Sensor Networks (WPSNs) and MAC protocols are introduced in this paper. Second, some existing MAC protocols are introduced. Sensor MAC (S-MAC) protocol is analyzed and existing improved backoff algorithms are introduced. A new MAC protocol called Improved Sensor MAC (IS-MAC) is then proposed to solve the problem that the contention window (CW) during carrier sense is fixed in S-MAC protocol. IS-MAC protocol is able to adjust CW in terms of network load, so energy consumption can be decreased. Finally, according to the simulation results on NS2, the proposed protocol has better performance in terms of throughput and energy consumption.

Recent advancements in wireless communications and electronics have enabled the development of low cost sensor networks. Among the protocols of wireless Sensor Networks (WSN), Medium Access Control (MAC) protocols are given more priority as traditional MAC protocols are not suitable for Wireless communication. As many of the MAC protocols consider the sensor nodes to be stationary, and when these protocols are used in mobile environment the network performance decreases. In this paper, we introduce a new TDMA based MAC protocol which can be used in mobile wireless sensor network. This protocol uses TDMA based MAC scheme where the time will be divided into frames and then time slots. These slots are further divided into sections as channel request (CR), channel allocation (CA) and data section. We will also design an algorithm considering the energy efficiency of a wireless sensor network. Therefore the life time of the sensor nodes deployed in a wireless sensor network will be increased.

The properties of underwater acoustic channel are quite different from those of terrestrial wireless sensor networks, which brings many challenges to design an efficient media access control (MAC) protocol for underwater acoustic sensor networks (UWASNs). In order to overcome the long propagation delay and the funneling effect of UWASNs, a MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC) protocol, is proposed in the paper. In the proposed protocol, a round-robin method and the CDMA technology are used to make the sink receive packets from multiple neighbors at the same time. Unlike other CDMA-based protocols using the transmitter-oriented code assignment (TOCA) or the receiver-oriented code assignment (ROCA), the POCA is used in the CDMA technology. Since the number of the path is much less than the number of nodes, the length of the spreading code used in systems with POCA is greatly shorter than those of the spreading code used in systems with TOCA or ROCA. Simulation results show that compared to existing MAC protocols for UWASNs, the proposed MAC protocol achieves a higher throughput, and a lower end-to-end delay.

The industrial Internet of Things (IIoT) depends on wireless sensor networks (WSNs) to enable low‐power, low‐data‐rate communication in resource‐limited settings. While the IEEE 802.15.4 standard provides the communication foundation, its medium access control (MAC) protocols face challenges including energy consumption, latency, scalability, and adaptability. Traditional MAC protocols cannot keep up with the demands of IIoT networks as the number of connected devices continues to increase. Therefore, edge artificial intelligence (Edge AI) and tiny machine learning (TinyML) represent emerging approaches that show potential for improving the performance of traditional MAC protocols directly on IIoT devices. Edge AI and TinyML allow intelligent decision‐making at the edge, which enables efficient data processing and adaptability to the environment without the need for cloud infrastructure, which may reduce latency and energy consumption. This paper systematically examines the emerging paradigm of combining Edge AI and TinyML to improve MAC protocols for WSNs in IIoT networks. We explore advanced machine learning (ML) methods applicable to resource‐limited devices, and we investigate how these methods can improve key performance metrics for MAC protocols, including energy efficiency, throughput, and network lifetime. We also discuss the challenges and limitations of applying AI solutions in WSNs, including computational constraints, data scarcity, and model scalability. Finally, we propose potential future research directions to improve the application of AI and ML techniques to develop more efficient, adaptive, and intelligent MAC protocols for future IIoT networks.

We present a novel TDMA-based medium access control (MAC) protocol for wireless sensor networks. Unlike conventional MAC protocols, which function independently of the application, we introduce an adaptive, information-centric and lightweight MAC (AI-LMAC) protocol that adapts its operation depending on the requirements of the application. We also present a completely localised data management framework that helps capture information about traffic patterns in the network. This information is subsequently used by AI-LMAC to modify its operation. The data management-framework can additionally be used for efficient query dissemination and query optimisation. We present preliminary results showing how the MAC protocol efficiently manages the issues of fairness and latency.

Medium access control (MAC) protocols provide a means to nodes to access the wireless medium efficiently and collision free to the best of their ability. In this paper we provide a survey of MAC protocols developed for mobile ad hoc (MANETs) in the past based on certain methods and techniques such as multiple radios, multiple channels and specialized beamforming antennas. We discuss some of the MAC protocols designed for wireless sensor networks (WSNs) and their applicability in a MANET environment. There are some similarities between MANETs and WSN's in general but there is also critical differences between the two that affect the design of MAC protocols for both these networks. Traditionally, MAC protocols have been classified on the basis of two broad categories of contention free and contention based MAC protocols but a number of new algorithms proposed in the recent past merge the two schemes together in a single MAC solution and thus there is a need for a new classification approach. MANETs have their unique constraints and characteristics. In this classification, we will discuss various MAC solutions proposed in the past in the light of these constraints and characteristics. We do not intend to explain each and every protocol since the number of MAC solutions proposed in the past decade or so is very large. The purpose of this article is to give the readers a general idea on the various techniques and methods used in literature to develop MAC protocols for MANETs. The techniques range from algorithmic changes such as cross-layer design to enhancement in hardware such as directional antennas.

Wireless sensor “motes” is small or tiny embedded systems equipped with radios for wireless communication in the networks, which depend on batteries as a power source. The development of Medium Access Control (MAC) protocols which search is for to minimize the energy consumption in the wireless sensor network. Recent contention based MAC protocols reduce energy usage by placing the radio in a low power sleep state when not sending or receiving the message. In this paper the main emphasis is on the analysis of the Contention Based MAC Protocols and energy consumption in the networks. Based on the work done by various researchers conclude that S-MAC is the backbone of all the MAC protocols for wireless sensor networks. Our proposed work investigated the energy usage and compared the performance of IEEE 802.11 MAC protocol with S-MAC protocol on different modes like without periodic sleep and with periodic sleep on different performance metrics like Remaining Energy vs Time, Energy consumption vs global packet id and Average End to End Delay vs Time. The performance of S-MAC protocol improves on the basis of duty-cycle parameter, which determines the length of sleep period in a frame and this parameter is a variable. So changing the duty cycle will change the performance of S-MAC protocol. Finally, we have used the different routing protocol with S-MAC to evaluate the energy consumption. The experimented worked done on Network Simulator Ns2- 2.34.KeywordsMedium Access ProtocolWireless Sensor NetworkIdle listeningSleep StateS-MACEnergy ConsumptionDuty cycle

In this paper, we propose a detailed energy survey of the physical, data link, and network layer by analytical techniques. We also show the impact of regular sleep periods on node energy consumption and present a comparison analysis of single-hop vs. multi-hop communications in the energy realm. A detailed energy expenditure analysis of not only the physical layer but also the link and network layer provides a basis for developing new energy efficient wireless sensor networks. Regular, coordinated sleeping extends the lifetime of sensor nodes, but systems can only benefit from sleeping in terms of transmitted packets if the data arrival rate to the system is low. Energy efficiency is the driving motivation for it can be considered the most important factor for wireless sensor networks because of the power constraints set by battery operation. Radio solutions in the lower ISM bands are attractive because of their relatively easy implementation and low power consumption. However, the data rates of these commercial radios are also relatively low, limiting transmittable frame sizes to a few tens of octets along with strict duty cycle requirements. From the analysis we extract key parameters of selected MAC protocols and show that some traditional mechanisms, such as binary exponential backoff, have some inherent problems. We also argue that single-hop communications has up todo% lower energy consumption than multi-hop forwarding within the feasible transmission distances of an ISM radio. Index Terms-Energy efficiency, Wireless sensor net- works, Medium access control (MAC) protocols, multi-hop communications a duty cycIe (Z), (3), which is normally 10% for the 434MHz band and 1% for the 868MHz band. The duty cycle is defined as the ratio, expressed as a percentage, of the maximum transmitter on-time, relative to a one hour period. When a sensor network is expected to work continuously, this duty cycle has to be taken into account and it can affect the energy efficiency of a network. In this paper we perform cross-layer analysis by pre- senting topology, medium access control (MAC) and ra- dio transceiver energy consumption models that work in unison. The hear topology model represents a common network after network layer route discovery has been accomplished. We use an energy consumption model for the transmission and reception of MAC frames originally presented in (4), develop a coordinated sleep group energy consumption model, and analytically investigate the effect of sleep on sensor networks using three MAC protocols. From the analysis we show that although in an ideal scenario multi-hop communications perform better than single-hop communications, realistic energy models and especially the MAC protocol design have a significant impact. We propose a multi-group sleep model for our nanoMAC protocol, and show that reg- ular sleep periods have a significant, energy reducing impact on node energy consumption with low traf!fic rates. The radio transceiver energy model takes into account several important radio parameters and we use the RFM TRlOOO and RFM radio designers guide (5) for realistic transceiver parameters. The main metric used is absolute energy, consumption per useful transmitted bit. This means only the MAC or thc network protocol data unit (PDU) will be considered and all the other communicated bits, headers, control frames, preambles, etc. are considered as overhead. The rest of the paper is organized as follows. Some related work is discussed in Section IT and in Section 111 we look at the radio propagation energy model. Section TV presents the network topology and energy

Design of energy efficient medium access control (MAC) protocol for wireless sensor network (WSN) containing mobile nodes is a challenging task. Majority of the MAC protocols for wireless sensor networks assume static sensor nodes, which results in poor performance of such protocols in a network containing mobile nodes. In this paper we propose a MAC protocol which is energy efficient as well as suitable for a WSN containing mobile nodes. The proposed protocol is based on both TDMA and CSMA. It adjusts the frame size to adapt to the changes in mobility and traffic conditions. The performance of the proposed protocol has been compared with LEACH-C protocol. It outperforms LEACH-C in terms of average energy consumption, packet delivery ratio and network life time.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

Energy efficiency is a primary consideration in a wireless sensor network (WSN). This is also a major parameter when designing a medium access control (MAC) protocol for WSNs. Hierarchical clustering structure is regarded suitable for WSNs due to its good performance in energy conservation. In this work, an adequately flexible mechanism for clustering WSNs is designed, in which some creative or promotional metrics are utilized, such as cluster head selection algorithm, cluster optional reconstruction, interested data transmission, multiple path routing protocol. All these strategies were cooperated to maximize energy saving of whole system. An appropriate MAC protocol for this mechanism is proposed, by flexibly switching the status of diverse sensor nodes in different strategies. The simulation results show that the proposed MAC protocol is suitable for clustering WSNs and performs well in aspects of energy efficiency, flexibility and scalability.

Due to their limited software and hardware capabilities, wireless sensor nodes are vulnerable against radio jamming. This becomes even worse if energy-efficient jamming is achieved by exploiting knowledge of the data link layer. Encrypting the packets may help to prevent or restrict the jamming. However, due to the nature of the MAC (Media Access Control) protocols, the jammer may take advantage and prevent network communication for relatively long periods even when dealing with encrypted packets. This paper aims to investigate and provide new insights into the security considerations of MAC protocols for wireless sensor networks. The paper also discusses countermeasures for energy-efficient encryption resistant jamming attacks against wireless sensor network MAC protocols.

Wireless sensor networks with many inexpensive sensor nodes allow users to accurately monitor a remote environment. Usually one or several mobile nodes are used to collect and combine sensor data from each individual stationary node. These networks require robust wireless communication protocols that are energy efficient and provide low latency. Motivated by these applications, we develop a novel medium access control (MAC) protocol for this kind of applications. The sensor nodes are expected to remain inactive for most of time, but become active when a mobile node is nearby. A few techniques for energy saving are developed in our protocol, e.g., true-sleep and pseudo-sleep modes are introduced to reduce energy consumption. They are implemented by radio-triggered circuit which wakes up the stationary nodes as a mobile node moves into the stationary nodespsila reception range. The proposed protocol is simulated in OPNET Modeler 10.5. The simulation results show that the proposed protocol has better performance than S-MAC and EAR (Eavesdrop-And-Register) in terms of latency, energy efficiency, and throughput.