2014 IEEE International Conference on Distributed Computing in Sensor Systems / IEEE Staff.

Format:

Book

Author/Creator:

IEEE Staff, author, issuing body.

Language:

English

Subjects (All):

Electronic data processing--Distributed processing.

Electronic data processing.

Mobile computing--Congresses.

Mobile computing.

Multisensor data fusion--Congresses.

Multisensor data fusion.

Physical Description:

1 online resource

Other Title:

2014 IEEE International Conference on Distributed Computing in Sensor Systems

Distributed Computing in Sensor Systems

Distributed Computing in Sensor Systems (DCOSS), 2014 IEEE International Conference on

Place of Publication:

Piscataway, NJ : IEEE, 2014.

Summary:

Wireless Sensor Networks (WSNs) are deployed in a variety of topologies and configurations depending on specific applications and requirements. In this paper, we study a simple and yet very important class of the WSN topologies, the linear or chain topology in which the Sensor Nodes (SNs) are connected in a series and gather the sensed data at a single base station or sink at the end of the chain. WSNs with linear topology have many practical applications, e.g., in infrastructure monitoring and surveillance of civil constructions. There is a large body of research on efficient data gathering techniques to transmit the sensed data over WSNs' limited communication bandwidth. In particular for linear topology, data collection technique has to put a balanced load on all SNs to avoid breakage of the chain at the exhausted nodes. Compressed Sensing (CS) is an efficient data collection technique for WSNs that fulfills these requirements. In a failure-free scenario, CS avoids exhausted nodes by balancing the communication and processing load on the SNs. In this paper, we examine the performance of a special implementation of CS for WSNs, called Compressive Data Gathering (CDG) when a SN in a chain WSN encounters a failure and cannot forward messages to the next hop. We propose a method to enhance the robustness of CDG in such failure scenarios by transmitting the messages to the next healthy node and excluding the failed samples from CS signal recovery mechanism. Evaluations show that our method effectively withstands the failures without sacrificing the accuracy of the collected data. © 2014 IEEE.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9781479946174

1479946176