Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Priority Based Data Transmission for WBAN

Wireless Body Area Sensor Network (WBASN) or Wireless Body Area Network (WBAN) is a growing field in healthcare applications. It enables remote monitoring of patient’s physiological data through wireless communication. It is composed of sensor network which collects physiological data from the patient. There are several issues concerning WBAN such as security, power, routing protocol to address QoS metrics (reliability, end-to-end delay, and energy efficiency), etc. The focus of the study is the issue on different QoS metrics. There were several QoS aware routing protocol that has been proposed which implements multiple queues for different types of data. However, one issue on multiple queue system is starvation, end-to-end delay, and reliability. The study proposed an efficient priority queue based data transmission that improves the end-to-end delay, reliability, and queuing delay of QoS aware routing protocol

Radio Frequency Energy Harvesting and Management for Wireless Sensor Networks

Radio Frequency (RF) Energy Harvesting holds a promising future for generating a small amount of electrical power to drive partial circuits in wirelessly communicating electronics devices. Reducing power consumption has become a major challenge in wireless sensor networks. As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks is an emerging and active research area. This chapter presents a practical approach for RF Energy harvesting and management of the harvested and available energy for wireless sensor networks using the Improved Energy Efficient Ant Based Routing Algorithm (IEEABR) as our proposed algorithm. The chapter looks at measurement of the RF power density, calculation of the received power, storage of the harvested power, and management of the power in wireless sensor networks. The routing uses IEEABR technique for energy management. Practical and real-time implementations of the RF Energy using Powercast harvesters and simulations using the energy model of our Libelium Waspmote to verify the approach were performed. The chapter concludes with performance analysis of the harvested energy, comparison of IEEABR and other traditional energy management techniques, while also looking at open research areas of energy harvesting and management for wireless sensor networks.Comment: 40 pages, 9 figures, 5 tables, Book chapte

Low-Power Pıc-Based Sensor Node Devıce Desıgn And Theoretıcal Analysıs Of Energy Consumptıon In Wıreless Sensor Networks

Teknolojinin ilerlemesi, daha enerji verimli ve daha ucuz elektronik bileşenlerinin daha küçük üretilmesini sağlamıştır. Bu nedenle, daha önce mevcut birçok bilgisayar ve elektronik bilim-mühendislik fikirleri uygulanabilir hale gelmiştir. Bunlardan birisi de kablosuz sensör ağları teknolojisidir. Kablosuz algılayıcı ağlar, düşük enerji tüketimi ve gerekli teknik gereksinimlerin gerçekleşmesi ile uygulanabilir hale gelmiştir. Ayrıca, Kablosuz algılayıcı ağlarının tasarımında iletişim algoritmaları, enerji tasarruf protokolleri ve yenilenebilir enerji teknolojileri gibi diğer bilimsel çalışmalar zorunlu hale gelmiştir. Bu tez, mikroelektronik sistemler, kablosuz iletişim ve dijital elektronik teknolojisinin ilerlemesiyle uygulanabilir hale gelmiş sensör ağları teknolojisini kapsamaktadır. Birincisi, algılama görevleri ve potansiyel algılayıcı ağ uygulamaları araştırılmış ve algılayıcı ağlarının tasarımını etkileyen faktörlerin gözden geçirilmesi sağlanmıştır. Ardından sensör ağları için iletişim mimarisi ana hatlarıyla belirtilmiştir. Ayrıca, tek bir düğümün WLAN ile iletişim kurabilmesi için yeni donanım mimarisi tasarlanmış ve düğümlerde yenilenebilir enerji kaynakları kullanılmıştır. Bu tezde WSN, analitik bilim ve uygulamalı bilim açısından incelenmiştir. Düşük enerji tüketimi ve iletişim protokolleri arasındaki ilişki değerlendirilmiş ve bilimsel sonuçlara varılmıştır. Teorik analizler bilimsel uygulamalarla desteklenmiştir. Çalışmalar, düşük enerji ve maksimum verimlilik prensibinin gerçekleştirilmesine dayalı kablosuz sensör ağları üzerinde gerçekleştirilmiştir. Kablosuz sensör ağlari sistemi tasarlandıktan sonra; sensör düğümlerinin enerji tüketimi ve kablosuz ağdaki davranışları test ve analiz edilmiştir. Düşük enerji tüketimi ile sensör düğümleri arasındaki ilişki detaylı olarak değerlendirilmiştir. PIC Tabanlı mikro denetleyiciler sensör düğümlerinin tasarımında kullanılmış ve çok düşük maliyetli tasarım için ultra düşük güçte, nanoWatt teknolojisi ile desteklenen sensör düğümleri tasarlanmıştır. İşleme birimi, bellek birimi ve kablosuz iletişim birimi sensör viii düğümlerine entegre edilmiştir. Tasarlanan sensör düğümünün işletim sistemi PIC C dili ile yazılmıştır ve PIC işletim sistemi nem, sıcaklık, ışığa duyarlılık ve duman sensörü gibi farklı özelliklerin ölçülmesine izin vermiştir. Sensörlerden gelen verilerin merkezi bir konumdan kaydedilmesi ve izlenebilmesi için, C# programlama dili ile bilgisayar yazılımı geliştirilmiştir. Gelişmiş algılayıcı düğümler tarafından alınan kararların uygulanması için yazılım algoritması ve donanım modüllerini içeren karar verme sistemi tasarlanmıştır. Gelişmiş PIC Tabanlı sensör düğümleri, enerji üretimi ve enerji tasarrufu için, güneş enerjisi paneli, şarj edilebilir pil ve süper kapasitör gibi yenilenebilir enerji kaynakları ile benzersiz bir PIC Kontrollü voltaj birimi ile desteklenmiştir. Geliştirilmiş kablosuz sensör ağları sistemi, endüstri uygulamaları, akıllı fabrikalar ve akıllı evler gibi günlük hayat uygulamaları için de kullanılabilecektir. Kablosuz algılayıcı ağlar geniş bir aralıkta kullanılmak üzere tasarlanmıştır. Tezin sonuçları, özellikle yenilenebilir enerji kaynakları ile WSN'nin geliştirilmesine yardımcı olmayı amaçlamaktadır

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

Energy Harvesting Techniques for Internet of Things (IoT)

The rapid growth of the Internet of Things (IoT) has accelerated strong interests in the development of low-power wireless sensors. Today, wireless sensors are integrated within IoT systems to gather information in a reliable and practical manner to monitor processes and control activities in areas such as transportation, energy, civil infrastructure, smart buildings, environment monitoring, healthcare, defense, manufacturing, and production. The long-term and self-sustainable operation of these IoT devices must be considered early on when they are designed and implemented. Traditionally, wireless sensors have often been powered by batteries, which, despite allowing low overall system costs, can negatively impact the lifespan and the performance of the entire network they are used in. Energy Harvesting (EH) technology is a promising environment-friendly solution that extends the lifetime of these sensors, and, in some cases completely replaces the use of battery power. In addition, energy harvesting offers economic and practical advantages through the optimal use of energy, and the provisioning of lower network maintenance costs. We review recent advances in energy harvesting techniques for IoT. We demonstrate two energy harvesting techniques using case studies. Finally, we discuss some future research challenges that must be addressed to enable the large-scale deployment of energy harvesting solutions for IoT environments

A wearable wireless sensor network for indoor smart environment monitoring in safety applications

This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO2 concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers

Energy Management in RFID-Sensor Networks: Taxonomy and Challenges

Ubiquitous Computing is foreseen to play an important role for data production and network connectivity in the coming decades. The Internet of Things (IoT) research which has the capability to encapsulate identification potential and sensing capabilities, strives towards the objective of developing seamless, interoperable and securely integrated systems which can be achieved by connecting the Internet with computing devices. This gives way for the evolution of wireless energy harvesting and power transmission using computing devices. Radio Frequency (RF) based Energy Management (EM) has become the backbone for providing energy to wireless integrated systems. The two main techniques for EM in RFID Sensor Networks (RSN) are Energy Harvesting (EH) and Energy Transfer (ET). These techniques enable the dynamic energy level maintenance and optimisation as well as ensuring reliable communication which adheres to the goal of increased network performance and lifetime. In this paper, we present an overview of RSN, its types of integration and relative applications. We then provide the state-of-the-art EM techniques and strategies for RSN from August 2009 till date, thereby reviewing the existing EH and ET mechanisms designed for RSN. The taxonomy on various challenges for EM in RSN has also been articulated for open research directives