Energy Efficient Algorithm & Protocol For Wireless Industrial Sensor Network

Wireless sensor networks (WSNs) consists ofunattended sensors with limited storage, energy (battery power)and computation and communication capabilities. So, energy efficient mechanism for wireless communication on each sensor node is so crucial for wireless sensor networks. Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. A wireless sensor node is often powered by battery which is not easily replaced, so researching how to use itslimited energy effectively is the meaningful for wireless sensor networks(WSNs). Energy routing protocol is suitable for industrial applications due to its capability of energy efficient,real-time,reliable comm.& energy efficient algorithm is provided which based on power control

Accounting for Failures in Delay Analysis for WirelessHART Networks

WirelessHART networks are gaining ground as a real-time communication infrastructure in industrial wireless control systems. Because wireless communication is often susceptible to transmission failures in industrial environments, it is essential to account for failures in the delay analysis for realtime flows between sensors and actuators in process control. WirelessHART networks handle transmission failures through retransmissions using dedicated and shared time slots through different paths in the routing graphs. While these mechanisms for handling transmission failures are critical for process control requiring reliable communication, they introduce substantial challenges to worst-case end-to-end delay analysis for real-time flows. This paper presents the first worst-case end-to-end delay analysis for periodic real-time flows in a WirelessHART network that takes into account transmission failures. The delay bounds can be used to quickly assess the schedulability of real-time flows for industrial wireless control applications with stringent requirements on both high reliability and network latency. Simulations based on the topologies of a wireless sensor network testbed consisting of 69 TelosB motes indicate that our analysis provides safe upper bounds of the end-to-end delays of real-time flows at an acceptable level of pessimism

Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing

Wireless industrial monitoring and control networks: the journey so far and the road ahead

While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Design and Analysis of Enhanced LEACH based Energy Routing Protocol for Wireless Sensor Network

In recent times, wireless sensor networks, or WSNs, have attracted a lot of attention because of their extensive use in a variety of fields, such as industrial automation, healthcare, and environmental monitoring. Energy efficiency is a major problem for WSNs since sensor nodes frequently run on batteries and have little energy available. Effective routing techniques are essential for extending the life of the network and guaranteeing dependable data transfer. This work focuses on the performance analysis and numerical modeling of a new routing strategy that combines machine learning approaches to improve WSN energy efficiency. The suggested routing algorithm optimizes energy consumption and overall network performance by adjusting its recommendations in real-time in response to environmental and network variables. We assess this machine learning-based routing protocol's performance using large-scale numerical simulations, contrasting it with conventional routing protocols and emphasizing its possible advantages in terms of energy efficiency and dependable data delivery. We investigate a variety of situations in our simulations, taking into account different network topologies, traffic patterns, and environmental factors. We evaluate many measures, including energy consumption, network lifetime, packet delivery ratio, and end-to-end delay, in order to offer a thorough evaluation of the efficacy of the machine learning-based routing protocol. The outcomes show how energy-efficient the protocol is, guaranteeing long-lasting sensor nodes and reliable data transfer while adjusting to changing network conditions.The results of this study highlight how machine learning approaches can completely change how routing protocols are designed and optimized in wireless sensor networks with limited energy. This research helps to construct sustainable and dependable WSNs by enhancing energy efficiency and network performance, which makes it easier to deploy sensor networks in crucial applications