scholarly journals Mind the SmartGap: A Buffer Management Algorithm for Delay Tolerant Wireless Sensor Networks

2015 ◽  
pp. 104-119 ◽  
Author(s):  
Pehr Söderman ◽  
Karl-Johan Grinnemo ◽  
Markus Hidell ◽  
Peter Sjödin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Buffer Management ◽  
Wireless Sensor ◽  
Management Algorithm ◽  
Delay Tolerant

An Improved Cluster Key Management Algorithm for Wireless Sensor Networks

2014 ◽  
Vol 998-999 ◽  
pp. 1092-1095
Author(s):  
Qi Sheng Zhao ◽  
Xiao Ming Liu ◽  
Hui Sheng Zhu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Key Management ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Authentication Mechanism ◽  
Management Algorithm ◽  
Management Scheme ◽  
Dynamic Key Management ◽  
Dynamic Key

The information security of wireless sensor networks is one of hot issues on the current research; this paper combines threshold key scheme with the management of security key sharing and group agreement and proposes dynamic key management scheme through clustering level key matrix of authentication mechanism from the cluster to node. The network is divided into different clusters, and the cluster head conducts the key authentication exchange and updates the key management with threshold key schemes, with no need of third authentication center, reduces the computing and communication costs, and promotes communication.

Impact of Buffer Management Solutions on MAC Layer Performance in Wireless Sensor Networks

2018 ◽  
Vol E101.B (9) ◽  
pp. 2058-2068 ◽  
Author(s):  
Derviş AYGÖR ◽  
Shafqat Ur REHMAN ◽  
Fatih Vehbi ÇELEBİ
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Buffer Management ◽  
Wireless Sensor ◽  
Mac Layer

scholarly journals A novel energy-aware routing protocol in intermittently connected delay-tolerant wireless sensor networks

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771738 ◽  
Author(s):  
Min Wook Kang ◽  
Yun Won Chung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Probabilistic Routing ◽  
History Of ◽  
Delay Tolerant ◽  
Overhead Ratio ◽  
Intermittently Connected

In delay-tolerant wireless sensor networks, messages for sensor data are delivered using opportunistic contacts between intermittently connected nodes. Since there is no stable end-to-end routing path like the Internet and mobile nodes operate on battery, an energy-efficient routing protocol is needed. In this article, we consider the probabilistic routing protocol using history of encounters and transitivity protocol as the base protocol. Then, we propose an energy-aware routing protocol in intermittently connected delay-tolerant wireless sensor networks, where messages are forwarded based on the node’s remaining battery, delivery predictability, and type of nodes. The performance of the proposed protocol is compared with that of probabilistic routing protocol using history of encounters and transitivity and probabilistic routing protocol using history of encounters and transitivity with periodic sleep in detail, from the aspects of delivery ratio, overhead ratio, delivery latency, and ratio of alive nodes. Simulation results show that the proposed protocol has better delivery probability, overhead ratio, and ratio of alive nodes, in most of the considered parameter settings, in spite of a small increase in delivery latency.

A Neural-Q-Learning Based Approach for Delay Tolerant Underwater Acoustic Wireless Sensor Networks

2014 ◽  
Vol 548-549 ◽  
pp. 1530-1535
Author(s):  
Lin Zou ◽  
De Feng Huang ◽  
Roberto Togneri
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Learning Algorithm ◽  
Wireless Sensor ◽  
Underwater Acoustic Communications ◽  
Frequency Channel ◽  
Underwater Acoustic ◽  
Continuous Space ◽  
Q Learning ◽  
Delay Tolerant

Delay tolerance is a major design concern for supporting underwater acoustic wireless sensor networks (UA-WSNs) to carry out tasks in harsh subsea environments. Due to the great difference between the underwater acoustic channel and the radio frequency channel, most of the existing routing protocols developed for terrestrial wireless sensor networks perform poorly in underwater acoustic communications. In this work, we present a Neural-Q-Learning algorithm based delay tolerant protocol for UA-WSNs. Due to the advantages of the artificial neural network along with the Q-Learning algorithm, the ferry node is capable of determining an optimal route in a two-dimensional continuous space to relay packets effectively and efficiently between sensors. Simulation results show that the delivery delay and delivery cost of the network significantly decrease by maximizing the meeting probability between the ferry node and sensors.

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