Issues of Data Aggregation Methods in Wireless Sensor Network: A Survey

Sirsikar, Sumedha; Anavatti, Samarth

doi:10.1016/j.procs.2015.04.244

Cited by 47 publications

(18 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are some different view to do data aggregation in theoretical and practical scenarios. Traditional views concentrated to specific network devices and resources such as Wireless Sensor Networks (WSN) to manage data aggregation approaches [17][18][19]. The other view extends the previous view to go beyond ubiquitous and distributed scenarios (instead of focusing on specific devices and network) such as big data [16], cloud and distributed computing [16,20], web technologies [21,22], or real-time systems [19].…”

Section: A Data Aggregationmentioning

confidence: 99%

“…So, it is very obvious the data aggregation techniques and approaches provide some help in such environments to perform data redundancy elimination, delay reduction, data accuracy (data quality), data security (reliability), traffic management, network scalability and minimizing overhead (bandwidth usage, processing requirements and power and energy wastage) [16,18,23]. In [24], the authors propose more sophisticated aggregation algorithms by proposing some soft computing techniques based on artificial neural networks, genetic algorithms, fuzzy logic models, and particle swarm techniques.…”

Section: A Data Aggregationmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

Sinaeepourfard

García

Masip-Bruin

et al. 2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

View full text Add to dashboard Cite

Abstract-Smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, smart city resources are managed with a cloud based solution, where sensors and devices are connected to provide a centralized and rich set of open data. The advantages of cloud based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for realtime or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. In this work, we present a new framework for data management in the context of a smart city through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment, we estimate the network traffic in this model during data collection and compare it with a traditional real system.

show abstract

Section: A Data Aggregationmentioning

confidence: 99%

Section: A Data Aggregationmentioning

confidence: 99%

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

Sinaeepourfard

García

Masip-Bruin

et al. 2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

View full text Add to dashboard Cite

show abstract

“…Data aggregation is the process in which some intermediate nodes receiving multiple packets will aggregate and produce single packet by removing duplicity. The aggregation protocol must achieve five goals: energy efficiency, reducing data propagation latency, data accuracy, aggregation freshness and avoiding collisions.The literature [8] shows that there are four data aggregation strategies as shown in figure-7: Centralized Data Aggregation-the idea is to have a more powerful central node called header node to which all sensing node will forward data and finally it will aggregate and send data to base station. Here, each sensor node will send data to this header node via possible shortest path.…”

Section: Data Aggregation In Wsnmentioning

confidence: 99%

Wireless Sensor Network- Challenges and Possibilities

Rathee¹,

Singh²,

Nandini³

2016

IJCA

View full text Add to dashboard Cite

Wireless Sensor Network (WSN) is the current research field in computer science & has growing use in day to day life. As a new technology, it has several research challenges and vast opportunities for the researchers. This paper highlights WSN, its architecture, challenges, applications and classification of various protocols concerning it. It also classifies various security protocols to make WSN a secure network.

show abstract

“…Transport layer is having multiple techniques for controlling traffic & avoiding congestion but these techniques consumes lot of power & resources [2].…”

Section: Introductionmentioning

confidence: 99%

Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach

Bhandari¹,

Rajasekhar²

2016

IJECE

View full text Add to dashboard Cite

In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer & Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.

show abstract

Issues of Data Aggregation Methods in Wireless Sensor Network: A Survey

Cited by 47 publications

References 3 publications

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

A Novel Architecture for Efficient Fog to Cloud Data Management in Smart Cities

Wireless Sensor Network- Challenges and Possibilities

Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach

Contact Info

Product

Resources

About