880 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
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Routing Protocols for Wireless Sensor Networks (WSNs)
Wireless sensor networks (WSNs) are achieving importance with the passage of time. Out of massive usage of wireless sensor networks, few applications demand quick data transfer including minimum possible interruption. Several applications give importance to throughput and they have not much to do with delay. It all rest on the applications desires that which parameter is more favourite. The knowledge of network structure and routing protocol is very important and it should be appropriate for the requirement of the usage. In the end a performance analysis of different routing protocols is made using a WLAN and a ZigBee based Wireless Sensor Network
Unified Role Assignment Framework For Wireless Sensor Networks
Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing.
The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue this by first developing a Role-based Hierarchical Self-Organization (RBSHO) protocol that organizes a connected dominating set (CDS) of nodes called dominators. This is done by hierarchically selecting nodes that possess cumulatively high energy, connectivity, and sensing capabilities in their local neighborhood. The RBHSO protocol then assigns specific tasks such as sensing, coordination, and routing to appropriate dominators that end up playing a certain role in the network.
Roles, though abstract and implicit, expose role-specific resource controls by way of role assignment and scheduling. Based on this concept, we have designed a Unified Role-Assignment Framework (URAF) to model application services as roles played by local in-network sensor nodes with sensor capabilities used as rules for role identification. The URAF abstracts domain specific role attributes by three models: the role energy model, the role execution time model, and the role service utility model. The framework then generalizes resource management for services by providing abstractions for controlling the composition of a service in terms of roles, its assignment, reassignment, and scheduling. To the best of our knowledge, a generic role-based framework that provides a simple and unified network management solution for wireless sensor networks has not been proposed previously
A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments
In recent years, due to the unnecessary wastage of electrical energy in
residential buildings, the requirement of energy optimization and user comfort
has gained vital importance. In the literature, various techniques have been
proposed addressing the energy optimization problem. The goal of each technique
was to maintain a balance between user comfort and energy requirements such
that the user can achieve the desired comfort level with the minimum amount of
energy consumption. Researchers have addressed the issue with the help of
different optimization algorithms and variations in the parameters to reduce
energy consumption. To the best of our knowledge, this problem is not solved
yet due to its challenging nature. The gap in the literature is due to the
advancements in the technology and drawbacks of the optimization algorithms and
the introduction of different new optimization algorithms. Further, many newly
proposed optimization algorithms which have produced better accuracy on the
benchmark instances but have not been applied yet for the optimization of
energy consumption in smart homes. In this paper, we have carried out a
detailed literature review of the techniques used for the optimization of
energy consumption and scheduling in smart homes. The detailed discussion has
been carried out on different factors contributing towards thermal comfort,
visual comfort, and air quality comfort. We have also reviewed the fog and edge
computing techniques used in smart homes
Energy-aware routing protocols in wireless sensor networks
Saving energy and increasing network lifetime are significant challenges in
the field of Wireless Sensor Networks (WSNs). Energy-aware routing protocols
have been introduced for WSNs to overcome limitations of WSN including limited
power resources and difficulties renewing or recharging sensor nodes batteries.
Furthermore, the potentially inhospitable environments of sensor locations, in some
applications, such as the bottom of the ocean, or inside tornados also have to be
considered. ZigBee is one of the latest communication standards designed for
WSNs based on the IEEE 802.15.4 standard. The ZigBee standard supports two
routing protocols, the Ad hoc On-demand Distance Vector (AODV), and the
cluster-tree routing protocols. These protocols are implemented to establish the
network, form clusters, and transfer data between the nodes. The AODV and the
cluster-tree routing protocols are two of the most efficient routing protocols in terms
of reducing the control message overhead, reducing the bandwidth usage in the
network, and reducing the power consumption of wireless sensor nodes compared to
other routing protocols. However, neither of these protocols considers the energy
level or the energy consumption rate of the wireless sensor nodes during the
establishment or routing processes. (Continues...)
Kablosuz sensör ağlarinda yönlü antenlerle enerji̇ veri̇mli̇ yönlendi̇rme
Without measurements, sustainable development effort can not progress in the right direction. Wireless sensor networks are vital for monitoring in real time and making accurate measurements for such an endeavor. However small energy storage in the sensors can become a bottleneck if the wireless sensor network is not optimized at the hardware and software level. Directional antennas are such optimization technologies at the hardware level. They have advantages over the omnidirectional antennas, such as high gain, less interference, longer transmission range, and less power consumption. In wireless sensor networks, most of the energy is consumed for communication. Considering the limited energy in small scale batteries of the sensors, energy efficient (aware) routing, is one of the most important software optimization techniques. The main goal of the technique is to improve the lifetime of the wireless sensor networks. In the light of these observations, it is desirable to do a coupled design of directional antennas with network software, for fully exploiting the advantages offered by directional antenna technology. In this thesis, the possibilities of doing such integrated design are surveyed and improvements are suggested. The design of the proposed microstrip patch antenna array is discussed and the performance characteristics are assessed through simulations. In the benchmarks, the proposed routing method showed improvements in energy usage compared to the existing approaches.Ölçümler olmadan sürdürülebilir kalkınma çabaları doğru yönde ilerleyemez. Bu tür çabalar için, kablosuz sensör ağları, gerçek zamanlı olarak izleme ve kesin ölçümler yapmak için vazgeçilemez unsurdur. Ancak, sensör ağı, donanım ve yazılım düzeylerinde optimize edilmemişse, sensörlerde enerji yetersizliği görülebilinir. Yönlü antenler, donanım düzeyinde uygulanan optimizasyon teknolojilerinden biri olmakla birlikte, çok yönlü antenlerden farklı olarak, yüksek kazanç, daha az parazit, daha uzun iletim mesafesi ve daha az güç tüketimi sağlarlar. Kablosuz sensör ağlarında enerjinin çoğu iletişim için tüketilir. Sensörlerdeki limitli enerjili küçük ölçekli piller göz önüne alındığında, yazılım düzeyindeki önemli metodlardan biri olan enerji verimli (duyarlı) yönlendirme protokolü, kablosuz sensör ağının genel enerji kullanımını optimize etmek ve ömrünü uzatmak için gereklidir. Bu gözlemlerin ışığında, yönlü anten teknolojisinin sunduğu potansiyel avantajlardan tam olarak yararlanmak için, yönlü antenlerin ağ yazılımıyla birlikte entegre tasarımını yapmak arzu edilir. Bu tezde, böyle bir entegre tasarımın yapılma olasılıkları araştırılmış ve iyileştirmeler önerilmiştir. Tezde, küçük şeritli yamalı anten dizisinin tasarımı tartışılmış ve performans karakteristikleri simulasyonlarla ölçülmüştür. Önerilen yönlendirme algoritması, diğer yönlendirme algoritmaları ile karşılaştırıldığında, enerji kullanımında iyileştirmeler göstermiştirM.S. - Master of Scienc
Average Load Distance (ALD) radio communication model for wireless sensor networks
The lifetime of network is one of the most critical issues that have to be considered in the application of wireless sensor networks. The network nodes are battery powered and remain operational as long as they can transmit the sensed data to the processing (sink) node. The main energy consumption of sensor node can be attributed to the task of data transmission to sink node or cluster head. Hence, conserving energy in transmitting data shall maximize functional life of the wireless networks. In this paper we proposed a computationally efficient Average Load Distance (ALD) communication model for forwarding data from sensor to the cluster head. Experiment results indicate that the proposed model can be up to 88% more efficient over direct mode of communication, in respect of per-round maximum energy consumption. An application study shows that ALD can save up to 89% of wireless sensor networks operational cost when compared to direct mode transmission
- …