Version 1
: Received: 11 July 2018 / Approved: 11 July 2018 / Online: 11 July 2018 (14:47:31 CEST)
How to cite:
Hejazi, P.; Ferrari, G. Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks. Preprints2018, 2018070206. https://doi.org/10.20944/preprints201807.0206.v1
Hejazi, P.; Ferrari, G. Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks. Preprints 2018, 2018070206. https://doi.org/10.20944/preprints201807.0206.v1
Hejazi, P.; Ferrari, G. Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks. Preprints2018, 2018070206. https://doi.org/10.20944/preprints201807.0206.v1
APA Style
Hejazi, P., & Ferrari, G. (2018). Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks. Preprints. https://doi.org/10.20944/preprints201807.0206.v1
Chicago/Turabian Style
Hejazi, P. and Gianluigi Ferrari. 2018 "Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks" Preprints. https://doi.org/10.20944/preprints201807.0206.v1
Abstract
Load balancing, energy efficiency and fault tolerance are among the most important data dissemination issues in Wireless Sensor Networks (WSNs). In order to successfully cope with the mentioned issues, two main approaches (namely, Data-centric Storage and Distributed Data Storage) have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the mentioned problems, the proposed solutions typically focus on one issue at a time. In this paper, we integrate the Data-centric Storage (DCS) features into Distributed Data Storage (DDS) mechanisms and present a novel approach, denoted as Collaborative Memory and Energy Management (CoMEM), to overcome both problems and bring memory and energy efficiency to the data loss mechanism of WSNs. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms existing approaches in various WSN scenarios.
Keywords
storage and retrieval processes; load-balancing; fault tolerance; energy efficiency; memory efficiency; data loss
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Mahdi Nasrollahzadeh
The commenter has declared there is no conflict of interests.