scholarly journals In-Motes EYE: A Real Time Application for Automobiles in Wireless Sensor Networks

2011 ◽  
Vol 03 (05) ◽  
pp. 158-166 ◽  
Author(s):  
Dimitrios Georgoulas ◽  
Keith Blow
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensor ◽  
Real Time Application

A Survey - Confrontation with Data Aggregation in Wireless Sensor Networks

2017 ◽  
Vol 9 (02) ◽  
pp. 119-124
Author(s):  
Jitendra Bahadur Singh ◽  
R. C. Tripathi
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Real Time ◽  
Sensor Network ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Research Challenges ◽  
Real Time Application

The main objective to use wireless sensor network (WSN) is to collect data across various nodes and send the collected data to sink for processing. This is typically the scenario in any real-time application of WSN. In this paper, the authors review various existing methods in data aggregation, list out the research challenges faced by the researchers and propose solutions for each method.

Real-Time Routing Based on On-Demand Multi-Hop Lookahead in Wireless Sensor Networks

2011 ◽  
Vol E94-B (2) ◽  
pp. 569-572
Author(s):  
Soochang PARK ◽  
Euisin LEE ◽  
Juhyun JUNG ◽  
Sang-Ha KIM
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensor ◽  
On Demand

SPREAD - A Routing Protocol to Meet End-to-end Adjusted Deadline in Real Time Wireless Sensor Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 63-78
Author(s):  
Neetika Jain ◽  
Sangeeta Mittal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Routing Protocol ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Packet Delivery ◽  
High Data ◽  
Hard Real Time

Background: Real Time Wireless Sensor Networks (RT-WSN) have hard real time packet delivery requirements. Due to resource constraints of sensors, these networks need to trade-off energy and latency. Objective: In this paper, a routing protocol for RT-WSN named “SPREAD” has been proposed. The underlying idea is to reserve laxity by assuming tighter packet deadline than actual. This reserved laxity is used when no deadline-meeting next hop is available. Objective: As a result, if due to repeated transmissions, energy of nodes on shortest path is drained out, then time is still left to route the packet dynamically through other path without missing the deadline. Results: Congestion scenarios have been addressed by dynamically assessing 1-hop delays and avoiding traffic on congested paths. Conclusion: Through extensive simulations in Network Simulator NS2, it has been observed that SPREAD algorithm not only significantly reduces miss ratio as compared to other similar protocols but also keeps energy consumption under control. It also shows more resilience towards high data rate and tight deadlines than existing popular protocols.

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