3,437 research outputs found
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
E2XLRADR (Energy Efficient Cross Layer Routing Algorithm with Dynamic Retransmission for Wireless Sensor Networks)
The main focus of this article is to achieve prolonged network lifetime with
overall energy efficiency in wireless sensor networks through controlled
utilization of limited energy. Major percentage of energy in wireless sensor
network is consumed during routing from source to destination, retransmission
of data on packet loss. For improvement, cross layered algorithm is proposed
for routing and retransmission scheme. Simulation and results shows that this
approach can save the overall energy consumptio
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
H-MAC: A Hybrid MAC Protocol for Wireless Sensor Networks
In this paper, we propose a hybrid medium access control protocol (H-MAC) for
wireless sensor networks. It is based on the IEEE 802.11's power saving
mechanism (PSM) and slotted aloha, and utilizes multiple slots dynamically to
improve performance. Existing MAC protocols for sensor networks reduce energy
consumptions by introducing variation in an active/sleep mechanism. But they
may not provide energy efficiency in varying traffic conditions as well as they
did not address Quality of Service (QoS) issues. H-MAC, the propose MAC
protocol maintains energy efficiency as well as QoS issues like latency,
throughput, and channel utilization. Our numerical results show that H-MAC has
significant improvements in QoS parameters than the existing MAC protocols for
sensor networks while consuming comparable amount of energy.Comment: 10 pages, IJCNC Journal 201
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