Hard real-time communication in multiple-access networks

1995 ◽  
Vol 8 (1) ◽  
pp. 35-77 ◽  
Author(s):  
Nicholas Malcolm ◽  
Wei Zhao
Keyword(s):  
Real Time ◽  
Multiple Access ◽  
Access Networks ◽  
Hard Real Time

Deterministic protocols for real-time communication in multiple access networks

1999 ◽  
Vol 22 (2) ◽  
pp. 128-136 ◽  
Author(s):  
Samphel Norden ◽  
S. Balaji ◽  
G. Manimaran ◽  
C.Siva Ram Murthy
Keyword(s):  
Real Time ◽  
Multiple Access ◽  
Access Networks

The Goal-Setting Model in a Multiagent Hard Real-Time System

Vestnik MEI ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 73-78
Author(s):  
Igor В. Fominykh ◽  
◽  
Sergey V. Romanchuk ◽  
Nikolay Р. Alekseev ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
Goal Setting ◽  
Time System ◽  
Real Time System ◽  
Hard Real Time

Efficient Scheduling Algorithm for Hard Real-Time Tasks in Primary-Backup Based Multiprocessor Systems

2009 ◽  
Vol 20 (10) ◽  
pp. 2628-2636 ◽  
Author(s):  
Jian WANG ◽  
Jian-Ling SUN ◽  
Xin-Yu WANG ◽  
Shen-Kang WANG ◽  
Jun-Bo CHEN
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Multiprocessor Systems ◽  
Hard Real Time

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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