An adaptive hybrid schema for data-centric storage in wireless sensor networks

Abstract

Storage, query cost, and energy efficiency are among the most important data dissemination issues in wireless sensor networks. Data-centric storage approach can be viewed as energy efficient and low cost solution to these issues, which itself suffers from hotspot storage problem. Some provided solutions tried to handle this mentioned problem and also brought load balancing and scalability to the network. In this article, we present a method called adaptive resilient datacentric storage which reduces the storage cost and also improves the load balancing and fault tolerance in the network by making data-centric storage adaptive based on the frequency of sensed events. Then, we propose a mathematical model to determine the threshold for the frequency of occurrence of sensed events. Finally, we developed a discreteevent-based simulator for two-dimensional graphical view of the network and collected the results. Simulations and analytical results show the superiority of the proposed method over the compared approaches with the miscellaneous frequency of events.

A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks

“…We integrate the DCS data storage mechanism into the DDS one and propose a novel scheme, denoted as CoMEM, which relies on the ideas presented in literature 9 10,12 . According to the CoMEM approach, we divide the network into zones on the basis of the target position.…”

“…Fault tolerance in the WSN is obtained by preventing data loss caused by energy or memory depletion in the storage node. The approaches reported in literatures 5–11 focus on data loss prevention due to energy shortages, whereas the approaches reported in literatures 12–14 concentrate on efficient memory usage of nodes in the WSN. The mechanism with which a replica is elected in DDS is based on local broadcasts between the neighbors of the storage node.…”

Energy and Memory Efficient Data Loss Prevention in Wireless Sensor Networks

“…We integrate the DCS data storage mechanism into the DDS one and propose a novel scheme, denoted as CoMEM, which relies on the ideas presented in [11], [8] and [9]. According to CoMEM approach, we divide the network into zones with similar dimensions.…”

“…The number of zones is assumed to be a power of 2 and depends on the network size. In some approaches, e.g., in [9], the number of zone changes on the basis of the occurrence frequency of sensed events. Here, we assume that the number of zones is constant.…”

“…Fault tolerance in the WSN is obtained by preventing data loss caused by energy or memory depletion in the storage node. The approaches in [4][5][6][7][8][9][10] focus on data loss prevention due to energy shortages, whereas the approaches in [11][12][13] concentrate on efficient memory usage of nodes in the WSN. The mechanism with which a replica is elected in DDS is based on local broadcasts between the neighbors of the storage node.…”