scholarly journals A Novel Data Collection Algorithm Based on Mobile Agent to Improve Energy Efficiency in Wireless Sensor Networks

2014 ◽  
Vol 39B (8) ◽  
pp. 528-537
Author(s):  
Myungjoon Yang ◽  
Jinhyuk Kim ◽  
Sangbang Choi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Mobile Agent ◽  
Wireless Sensor ◽  
Improve Energy Efficiency

WIRELESS SENSOR NETWORKS TO IMPROVE ENERGY EFFICIENCY IN DATA CENTERS

2021 ◽  
pp. 163-174
Author(s):  
Levente Klein ◽  
Sergio Bermudez ◽  
Fernando Marianno ◽  
Hendrik Hamann
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Centers ◽  
Wireless Sensor ◽  
Improve Energy Efficiency

Energy Efficient Multi-Hop Wireless Sensor Networks with CMIMO-SM Scheme

2014 ◽  
Vol 666 ◽  
pp. 322-326
Author(s):  
Yu Yang Peng ◽  
Jae Ho Choi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Improve Energy Efficiency ◽  
Output System

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.

scholarly journals An Event-based Local Action Paradigm to Improve Energy Efficiency in Queriable Wireless Sensor Actuator Networks

2020 ◽  
Vol 16 (1) ◽  
pp. 66-74
Author(s):  
René Bergelt ◽  
Wolfram Hardt
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Big Data ◽  
Sensor Networks ◽  
Data Processing ◽  
Wireless Sensor ◽  
Big Data Processing ◽  
Improve Energy Efficiency ◽  
Sensor Actuator ◽  
Event Based

Wireless sensor networks (WSN) are deployed in a multitude of applications both in industrial and academic fields. In recent years, due to the emerge of Internet of Things (IoT) technologies and Vehicle2X communication scenarios, novel challenges for wireless sensor network platforms - regarding hardware and software - arose. Thus, challenges known from big data processing have reached the WSN scope and consequently approaches and methods have been devised to handle these. One such approach is queriable wireless sensor networks which enable their users the specification of sensing tasks in a declarative way without the need to re-program nodes in case the application requirements change. As many current WSN applications feature active parts with which nodes can directly influence their environment, the term wireless sensor actuator networks (WSAN) has been coined, setting such networks apart from solely passively measuring networks.In this article, we will present a short introduction to big data processing in wireless sensor networks which motivates the usage of queriable networks. We will show that in order to enable a WSAN to carry out actions energy-efficiently and in a timely manner, an event-based action model is favorable. Additionally, we will demonstrate how such an event system can be used to improve sub query performance in WSNs. We conclude with an evaluation regarding the benefit of combining this approach with wake-up receiver technologies based on a qualitative energy efficiency definition for WSN.

scholarly journals MINDS: Mobile Agent Itinerary Planning Using Named Data Networking in Wireless Sensor Networks

2021 ◽  
Vol 10 (2) ◽  
pp. 28
Author(s):  
Saeid Pourroostaei Ardakani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Mobile Agent ◽  
Network Traffic ◽  
Mobile Agents ◽  
Route Planning ◽  
Wireless Sensor ◽  
Named Data Networking ◽  
Sensory Data

Mobile agents have the potential to offer benefits, as they are able to either independently or cooperatively move throughout networks and collect/aggregate sensory data samples. They are programmed to autonomously move and visit sensory data stations through optimal paths, which are established according to the application requirements. However, mobile agent routing protocols still suffer heavy computation/communication overheads, lack of route planning accuracy and long-delay mobile agent migrations. For this, mobile agent route planning protocols aim to find the best-fitted paths for completing missions (e.g., data collection) with minimised delay, maximised performance and minimised transmitted traffic. This article proposes a mobile agent route planning protocol for sensory data collection called MINDS. The key goal of this MINDS is to reduce network traffic, maximise data robustness and minimise delay at the same time. This protocol utilises the Hamming distance technique to partition a sensor network into a number of data-centric clusters. In turn, a named data networking approach is used to form the cluster-heads as a data-centric, tree-based communication infrastructure. The mobile agents utilise a modified version of the Depth-First Search algorithm to move through the tree infrastructure according to a hop-count-aware fashion. As the simulation results show, MINDS reduces path length, reduces network traffic and increases data robustness as compared with two conventional benchmarks (ZMA and TBID) in dense and large wireless sensor networks.

scholarly journals IACR: an interference-aware channel reservation for wireless sensor networks

2019 ◽  
Vol 9 (2) ◽  
pp. 1220
Author(s):  
Sangsoon Lim
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Frequency Band ◽  
Success Probability ◽  
Wireless Sensor ◽  
Signal Interference ◽  
Efficient Operation ◽  
Improve Energy Efficiency ◽  
Channel Reservation

<span>In battery-based wireless sensor networks, energy-efficient operation is one of the most important factors. Especially, in order to improve energy efficiency in wireless sensor networks, various studies on low power operation have been actively conducted in the MAC layer. In recent years, mutual interference among various radio technologies using the same radio frequency band has become a serious problem. Wi-Fi, ZigBee, and Bluetooth use the same frequency band of 2.4GHz at the same time, which causes various signal interference problems. In this paper, we propose a novel channel reservation scheme, called IACR, to improve the energy efficiency of wireless sensor networks in an environment where interference occurs between various wireless technologies. The proposed scheme inserts a PN code into a long preamble for exchanging transmission status information between a transmitting node and a receiving node, thereby improving the transmission success probability while receiving less influence on transmission of other radio technologies. We performed an event-driven simulation and an experiment to measure the signal detection rate. As a result, it can be seen that the proposed technique reduces the packet drop rate by 15% and increases the discoverable distance of the control packet for channel reservation.</span>

scholarly journals An Information-Centric Semantic Data Collection Tree for Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6168
Author(s):  
Ngoc-Thanh Dinh ◽  
Younghan Kim
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
State Of The Art ◽  
Important Application ◽  
Wireless Sensor ◽  
Semantic Data ◽  
Construction Scheme ◽  
Semantic Tree

Data collection is an important application of wireless sensor networks (WSNs) and Internet of Things (IoT). Current routing and addressing operations in WSNs are based on IP addresses, while data collection and data queries are normally information-centric. The current IP-based approach incurs significant management overheads and is inefficient for semantic data collection and queries. To address the above issue, this paper proposes a semantic data collection tree (sDCT) construction scheme to build up a semantic data collection tree for wireless sensor networks. The semantic tree is rooted at the edge/sink and supports data collection tasks, queries, and configurations efficiently. We implement the sDCT in Contiki and evaluate the performance of the sDCT in comparison with the state-of-the-art scheme, 6LoWPAN/RPL and L2RMR, using telosb sensors under various scenarios. The obtained results show that the sDCT achieves a significant improvement in terms of the energy efficiency and the packet transmissions required for data collection or a query task compared to 6LoWPAN/RPL and L2RMR.

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