scholarly journals DS+: Reliable Distributed Snapshot Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Gamze Uslu ◽  
Kemal Cagri Serdaroglu ◽  
Sebnem Baydere
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Response Time ◽  
Wireless Sensor ◽  
Global State ◽  
Test Bed ◽  
Acquisition Performance ◽  
Node Network ◽  
Small Test ◽  
Fully Functioning

Acquiring the snapshot of a distributed system helps gathering system related global state. In wireless sensor networks (WSNs), global state shows if a node is terminated or deadlock occurs along with many other situations which prevents a WSN from fully functioning. In this paper, we present a fully distributed snapshot acquisition algorithm adapted to tree topology wireless sensor networks (WSNs). Since snapshot acquisition is through control messages sent over highly lossy wireless channels and congested nodes, we enhanced the snapshot algorithm with a sink based reliability suit to achieve robustness. We analyzed the performance of the algorithm in terms of snapshot success ratio and response time in simulation and experimental small test bed environment. The results reveal that the proposed tailor made reliability model increases snapshot acquisition performance by a factor of seven and response time by a factor of two in a 30-node network. We have also shown that the proposed algorithm outperforms its counterparts in the specified network setting.

scholarly journals Cluster-Based Arithmetic Coding for Data Provenance Compression in Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Qinbao Xu ◽  
Rizwan Akhtar ◽  
Xing Zhang ◽  
Changda Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Base Station ◽  
Arithmetic Coding ◽  
Wireless Sensor ◽  
Data Provenance ◽  
Mathematical Function ◽  
Test Bed ◽  
Coding Method ◽  
Data Source

In wireless sensor networks (WSNs), data provenance records the data source and the forwarding and the aggregating information of a packet on its way to the base station (BS). To conserve the energy and wireless communication bandwidth, the provenances are compressed at each node along the packet path. To perform the provenances compression in resource-tightened WSNs, we present a cluster-based arithmetic coding method which not only has a higher compression rate but also can encode and decode the provenance in an incremental manner; i.e., the provenance can be zoomed in and out like Google Maps. Such a decoding method raises the efficiencies of the provenance decoding and the data trust assessment. Furthermore, the relationship between the clustering size and the provenance size is formally analyzed, and then the optimal clustering size is derived as a mathematical function of the WSN’s size. Both the simulation and the test-bed experimental results show that our scheme outperforms the known arithmetic coding based provenance compression schemes with respect to the average provenance size, the energy consumption, and the communication bandwidth consumption.

Low-Power Wakeup-On-Demand Scheme for Wireless Sensor Networks with Very-Short Response Time

2010 ◽  
Vol E93-B (4) ◽  
pp. 1020-1023
Author(s):  
Byung-Bog LEE ◽  
Se-Jin KIM ◽  
Seung-Yeon KIM ◽  
Hyong-Woo LEE ◽  
Seung-Wan RYU ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Response Time ◽  
Low Power ◽  
Wireless Sensor ◽  
Short Response Time ◽  
On Demand

scholarly journals Enhancing and Securing the Routing Techniques in Wireless Sensor Networks

2020 ◽  
pp. 141-145
Author(s):  
Rupinder Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Network ◽  
Denial Of Service ◽  
Wireless Sensor ◽  
Physical Parameters ◽  
Network Node ◽  
Jamming Attacks ◽  
Proposed Model ◽  
Node Network

A wireless network node network (WSN) is defined as being composed of a large number of small light weighted nodes called network node nodes with routing, processing and communication facilities, which are densely deployed in physical or environmental condition. Each of these nodes collects data and its purpose is to route this information back to a sink. WSN is highly constrained type of network, having network node nodes with more capabilities. All network node nodes in the wireless network node network are interact with each other by intermediated network node nodes. Physical parameters computations are power, energy, memory, communication range and bandwidth. Wireless ad-hoc networks mainly use broadcast communication. Upon deployment, network node nodes automatically collaborate and form a network, start collecting data without any input from the user. The proposed model has been improved for the route metric calculation along with node and link load availability information module to avoid the connectivity loopholes and link congestions. The proposed model results have been obtained in the form of various network performance parameters such as network load, transmission delay, throughput, energy consumption, etc. In wireless sensor networks, there are many types of attacks that can hinder or obstruct the data to be deliver to the authenticated node so in order to check which node is authenticated various algorithms have been proposed. There are various attacks like Denial of Service, Distributed Denial of Service and various types of Jamming attacks that can disrupt or deny the communication between sender and receiver. It is important to develop some powerful tools for network analysis, design and managing the performance optimization of the network. In this paper some of the most common attacks and threats are explained and the prevention that can be taken by using various tools is implemented. Also the different routes are configured if the particular route is not available. All the nodes and the attacks are been shown by using a simulator NS2.

Enhancement of Asynchronous MAC Protocol in Wireless Sensor Networks for Smart Monitoring Applications

2017 ◽  
Vol 3 (1) ◽  
pp. 51
Author(s):  
Vo Que Son ◽  
Tran Truong Son
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Low Power ◽  
Mac Protocol ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Mac Layer ◽  
Test Bed ◽  
Monitoring Test

Up to now, many research works have been focusing on designs in MAC layer of Wireless Sensor Networks (WSNs) to target high throughput, low latency and solving the problem of idle listening. In this paper, an enhancement of Low-power asynchronous protocol for MAC layer, namely E-MAC, is proposed to target a long lifetime of sensor nodes working 6LoWPAN/IPv6 networks. Moreover, the E-MAC protocol is implemented on TI low-power platforms to verify the efficiency of the proposed design. Several parameters such as energy consumption, latency and packet delivery ratio are simulated and measured in a real monitoring test-bed to show the better performance in comparison with other popular MAC protocols.

scholarly journals Cognitive test-bed for wireless sensor networks

2014 ◽  
Author(s):  
Elena Romero ◽  
Javier Blesa ◽  
Agustin Tena ◽  
Guillermo Jara ◽  
Juan Domingo ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Cognitive Test ◽  
Test Bed
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