Quality Aware Data Aggregation Trees in Sensor Networks
14 Feb 2019-pp 557-567
TL;DR: An algorithm Quality Aware Data Aggregation Tree (QADAT) to construct a quality aware DAT is proposed and results show the effectiveness of the proposed algorithm and demonstrates quality awareness through DAT adaptability.
Abstract: Wireless Sensor Networks (WSNs) are key enablers for IoT and pervasive computing paradigm. While devices are being seamlessly enabled with connection and communication capabilities, exploring techniques to quantify and improve quality has gathered significance. This work explores quality of a Data Aggregation Tree (DAT) in sensor networks. DATs are building blocks for data collection in WSNs. In this work Quality of Experience (QoE) and Quality of Service (QoS) of DATs is evaluated using data aggregation ratio \(\alpha \) and generated data \(\delta \) respectively. An algorithm Quality Aware Data Aggregation Tree (QADAT) to construct a quality aware DAT is proposed. QADAT adapts the DAT to network and user expectation dynamics. Simulation results show the effectiveness of the proposed algorithm and demonstrates quality awareness through DAT adaptability.
Citations
More filters
01 Oct 2019
TL;DR: The study presents the techniques to estimate the communication and computation costs incurred for DAT construction, asymptotically and demonstrates the utilization of the proposed techniques to estimates the best and worst cases for communication and computations cost to meet the design objective of adhoc WSN deployments.
Abstract: In Wireless Sensor Networks (WSNs), Data Aggregation Trees (DATs) are employed for energy efficient data gathering. Energy efficient data collection is a primary requirement in the smart world of Internet of Things (IoT) as it facilitates to extend the survivability of the network. DATs gather data efficiently by employing data aggregation functions at the aggregator nodes. The employed aggregation function influences the cost of communication and cost of computation at a node. The study in this paper presents the techniques to estimate the communication and computation costs incurred for DAT construction, asymptotically. The strength of the proposed techniques is its ability to enable the estimation of best, average and worst case cost of DAT construction and rescheduling scenarios. Based on the asymptotic analysis, the study in this paper demonstrates the utilization of the proposed techniques to estimate the best and worst cases for communication and computation cost to meet the design objective of adhoc WSN deployments.
2 citations
Cites background from "Quality Aware Data Aggregation Tree..."
...Quality aware DATs are discussed in [13] and describe the impact of aggregation ratio on the quality of experience and quality of service of DATs....
[...]
TL;DR: A combined approach for DAT construction to improve NL reduces the communication overhead and relaxes the requirement of complete network information at the sink and demonstrates its suitability for hostile and critical environments.
1 citations
References
More filters
09 Dec 2002
TL;DR: This work presents the Tiny AGgregation (TAG) service for aggregation in low-power, distributed, wireless environments, and discusses a variety of optimizations for improving the performance and fault tolerance of the basic solution.
Abstract: We present the Tiny AGgregation (TAG) service for aggregation in low-power, distributed, wireless environments. TAG allows users to express simple, declarative queries and have them distributed and executed efficiently in networks of low-power, wireless sensors. We discuss various generic properties of aggregates, and show how those properties affect the performance of our in network approach. We include a performance study demonstrating the advantages of our approach over traditional centralized, out-of-network methods, and discuss a variety of optimizations for improving the performance and fault tolerance of the basic solution.
3,166 citations
02 Jul 2002
TL;DR: This paper model data-centric routing and compare its performance with traditional end-to-end routing schemes, and examines the complexity of optimal data aggregation, showing that although it is an NP-hard problem in general, there exist useful polynomial-time special cases.
Abstract: Sensor networks are distributed event-based systems that differ from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. Data-centric mechanisms that perform in-network aggregation of data are needed in this setting for energy-efficient information flow. In this paper we model data-centric routing and compare its performance with traditional end-to-end routing schemes. We examine the impact of source-destination placement and communication network density on the energy costs and delay associated with data aggregation. We show that data-centric routing offers significant performance gains across a wide range of operational scenarios. We also examine the complexity of optimal data aggregation, showing that although it is an NP-hard problem in general, there exist useful polynomial-time special cases.
1,536 citations
TL;DR: This article presents a survey of data-aggregation algorithms in wireless sensor networks and compares and contrast different algorithms on the basis of performance measures such as lifetime, latency, and data accuracy.
Abstract: Wireless sensor networks consist of sensor nodes with sensing and com- munication capabilities. We focus on data-aggregation problems in energy- constrained sensor networks. The main goal of data-aggregation algorithms is to gather and aggregate data in an energy efficient manner so that net- work lifetime is enhanced. In this article we present a survey of data-aggre- gation algorithms in wireless sensor networks. We compare and contrast different algorithms on the basis of performance measures such as lifetime, latency, and data accuracy. We conclude with possible future research directions.
943 citations
TL;DR: A comprehensive review of the existing literature on techniques and protocols for in-network aggregation in wireless sensor networks is provided, and suitable criteria to classify existing solutions are defined.
Abstract: In this article we provide a comprehensive review of the existing literature on techniques and protocols for in-network aggregation in wireless sensor networks. We first define suitable criteria to classify existing solutions, and then describe them by separately addressing the different layers of the protocol stack while highlighting the role of a cross-layer design approach, which is likely to be needed for optimal performance. Throughout the article we identify and discuss open issues, and propose directions for future research in the area
794 citations
01 Dec 2003
TL;DR: This paper proposes two new algorithms under name PEDAP (Power Efficient Data gathering and Aggregation Protocol), which are near optimal minimum spanning tree based routing schemes, where one of them is the power-aware version of the other.
Abstract: Recent developments in processor, memory and radio technology have enabled wireless sensor networks which are deployed to collect useful information from an area of interest. The sensed data must be gathered and transmitted to a base station where it is further processed for end-user queries. Since the network consists of low-cost nodes with limited battery power, power efficient methods must be employed for data gathering and aggregation in order to achieve long network lifetimes.In an environment where in a round of communication each of the sensor nodes has data to send to a base station, it is important to minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be achieved in terms of network lifetime.So far, besides the conventional protocol of direct transmission, two elegant protocols called LEACH and PEGASIS have been proposed to maximize the lifetime of a sensor network. In this paper, we propose two new algorithms under name PEDAP (Power Efficient Data gathering and Aggregation Protocol), which are near optimal minimum spanning tree based routing schemes, where one of them is the power-aware version of the other. Our simulation results show that our algorithms perform well both in systems where base station is far away from and where it is in the center of the field. PEDAP achieves between 4x to 20x improvement in network lifetime compared with LEACH, and about three times improvement compared with PEGASIS.
601 citations