Q-NiGHT: Adding QoS to Data Centric Storage in Non-Uniform Sensor Networks

Abstract

Storage of sensed data in wireless sensor networks is essential when the sink node is unavailable due to failure and/or disconnections, but it can also provide efficient access to sensed data to multiple sink nodes. Recent approaches to data storage rely on Geographic Hash Tables for efficient data storage and retrieval. These approaches however do not support different QoS levels for different classes of data as the programmer has no control on the level of redundancy of data (and thus on data dependability). Moreover, they result in a great unbalance in the storage usage in each sensor, even when sensors are uniformly distributed. This may cause serious data losses, waste energy and shorten the overall lifetime of the sensornet. In this paper, we propose a novel protocol, Q-NiGHT, which (1) provides a direct control on the level of QoS in the data dependability, and (2) uses a strategy similar to the rejection method to build a hash function which scatters data approximately with the same distribution as sensors. The benefits of Q-NiGHT are assessed through a detailed simulation experiment, also discussed in the paper. Results show its good performance on different sensors distributions on terms of both protocol costs and load balance between sensors.

Using Failure Models for Controlling Data Availability in Wireless Sensor Networks

“…We also performed simulations in MATLAB varying the network size. The total cost of the solution grows linearly with the number of nodes, providing evidence of the scalability of our Pirrus 1 . Furthermore, we analyze the performance of Pirrus, focusing on its ability to extend the lifetime of the network, compared to other non-adaptive solutions implementable on WSNs.…”

“…The simulation collected data for a week of simulated time. 1 Results are not included for space constraint. Each replica in the system has a size of 80 Kbytes, storing enough samples for three days of information.…”

“…Furthermore, the concept of Quality of Service for replication is introduced in Q-NiGHT [1]. This work enhances the Geographic Hash Table storage [7] by adding the concept of explicit QoS guarantees for each class of data.…”

“…Traditional replication approaches use a fixed number of replicas defined a-priori during network deployment [1]. Given the dynamic failure potential of the nodes in the network, these static solutions are either too expensive or cannot provide enough availability during the network lifetime.…”

Efficient load balancing and QoS-based location aware service discovery protocol for vehicular ad hoc networks

“…The first tier comprises the servers and the second one comprises standard sensor nodes acting as server locators. Their localization and communication infrastructure uses Q-NiGHT [5], which is an improved version of the geographic hash table (GHT) [6]. The presented architecture permits the load balancing of queries to the servers and it is tolerant to server faults.…”