TMO-NanoQ+: A Real-Time Kernel for Sensor Networks Supporting Time-Triggered and Message-Triggered Tasks

2007 ◽  
Author(s):  
Jae-An Yi ◽  
Shin Heu ◽  
Byuongkyu Choi ◽  
Hyun-Ju Kim ◽  
Hanseok Sue ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Real Time

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

Two-Hop Neighborhood Information-Based Real-Time Routing Design for Sensor Networks

2010 ◽  
Vol 20 (7) ◽  
pp. 1931-1942 ◽  
Author(s):  
Yan-Jun LI ◽  
Zhi WANG ◽  
You-Xian SUN
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Neighborhood Information ◽  
Routing Design

An Overview of Data Aggregation Architecture for Real-Time Tracking with Sensor Networks

2006 ◽  
Author(s):  
Tian He ◽  
Lin Gu ◽  
Liqian Luo ◽  
Ting Yan ◽  
John A. Stankovic ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Real Time ◽  
Data Aggregation ◽  
Real Time Tracking

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.

Sign in / Sign up

Export Citation Format

Share Document