7,495 research outputs found
An objective based classification of aggregation techniques for wireless sensor networks
Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented
A network-aware framework for energy-efficient data acquisition in wireless sensor networks
Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Distributed Optimization in Energy Harvesting Sensor Networks with Dynamic In-network Data Processing
Energy Harvesting Wireless Sensor Networks (EH- WSNs) have been attracting increasing interest in recent years. Most current EH-WSN approaches focus on sensing and net- working algorithm design, and therefore only consider the energy consumed by sensors and wireless transceivers for sensing and data transmissions respectively. In this paper, we incorporate CPU-intensive edge operations that constitute in-network data processing (e.g. data aggregation/fusion/compression) with sens- ing and networking; to jointly optimize their performance, while ensuring sustainable network operation (i.e. no sensor node runs out of energy). Based on realistic energy and network models, we formulate a stochastic optimization problem, and propose a lightweight on-line algorithm, namely Recycling Wasted Energy (RWE), to solve it. Through rigorous theoretical analysis, we prove that RWE achieves asymptotical optimality, bounded data queue size, and sustainable network operation. We implement RWE on a popular IoT operating system, Contiki OS, and eval- uate its performance using both real-world experiments based on the FIT IoT-LAB testbed, and extensive trace-driven simulations using Cooja. The evaluation results verify our theoretical analysis, and demonstrate that RWE can recycle more than 90% wasted energy caused by battery overflow, and achieve around 300% network utility gain in practical EH-WSNs
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
Distance Aware Relaying Energy-efficient: DARE to Monitor Patients in Multi-hop Body Area Sensor Networks
In recent years, interests in the applications of Wireless Body Area Sensor
Network (WBASN) is noticeably developed. WBASN is playing a significant role to
get the real time and precise data with reduced level of energy consumption. It
comprises of tiny, lightweight and energy restricted sensors, placed in/on the
human body, to monitor any ambiguity in body organs and measure various
biomedical parameters. In this study, a protocol named Distance Aware Relaying
Energy-efficient (DARE) to monitor patients in multi-hop Body Area Sensor
Networks (BASNs) is proposed. The protocol operates by investigating the ward
of a hospital comprising of eight patients, under different topologies by
positioning the sink at different locations or making it static or mobile.
Seven sensors are attached to each patient, measuring different parameters of
Electrocardiogram (ECG), pulse rate, heart rate, temperature level, glucose
level, toxins level and motion. To reduce the energy consumption, these sensors
communicate with the sink via an on-body relay, affixed on the chest of each
patient. The body relay possesses higher energy resources as compared to the
body sensors as, they perform aggregation and relaying of data to the sink
node. A comparison is also conducted conducted with another protocol of BAN
named, Mobility-supporting Adaptive Threshold-based Thermal-aware
Energy-efficient Multi-hop ProTocol (M-ATTEMPT). The simulation results show
that, the proposed protocol achieves increased network lifetime and efficiently
reduces the energy consumption, in relative to M-ATTEMPT protocol.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
The Dynamics of Vehicular Networks in Urban Environments
Vehicular Ad hoc NETworks (VANETs) have emerged as a platform to support
intelligent inter-vehicle communication and improve traffic safety and
performance. The road-constrained, high mobility of vehicles, their unbounded
power source, and the emergence of roadside wireless infrastructures make
VANETs a challenging research topic. A key to the development of protocols for
inter-vehicle communication and services lies in the knowledge of the
topological characteristics of the VANET communication graph. This paper
explores the dynamics of VANETs in urban environments and investigates the
impact of these findings in the design of VANET routing protocols. Using both
real and realistic mobility traces, we study the networking shape of VANETs
under different transmission and market penetration ranges. Given that a number
of RSUs have to be deployed for disseminating information to vehicles in an
urban area, we also study their impact on vehicular connectivity. Through
extensive simulations we investigate the performance of VANET routing protocols
by exploiting the knowledge of VANET graphs analysis.Comment: Revised our testbed with even more realistic mobility traces. Used
the location of real Wi-Fi hotspots to simulate RSUs in our study. Used a
larger, real mobility trace set, from taxis in Shanghai. Examine the
implications of our findings in the design of VANET routing protocols by
implementing in ns-3 two routing protocols (GPCR & VADD). Updated the
bibliography section with new research work
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