E2RINA: an Energy Efficient and Reliable In-Network Aggregation for Clustered Wireless Sensor Networks

Abstract

We present E 2 RINA, an aggregation algorithm for wireless sensor network applications characterized by clustered topologies, such as building automation and manufacturing plants. Thank to an efficient use of the wireless channel, E 2 RINA offers the robustness of the gossip-based algorithms and, at the same time, the energy performance of the faster cluster headbased algorithms. We also developed a mathematical model to predict the performance of the algorithm with respect to the free variables without the need of extensive simulations. We validate our model and the robustness of E 2 RINA by running a simulation model of a test case consisting of a cluster of MICA nodes.

Inner-Cluster Data Aggregation Scheme for Wireless Sensor Networks

“…Simulation We use CDA (Cluster-based Data Aggregation) denotes most of existing cluster-based schemes (such as [6], [7], [8]) in which all inner-cluster sensor readings will be transmitted to the aggregator. The adopted network model as shown in Fig.1 and assume that number of nodes in each cluster is 40, we generate random numbers of normal distribution for all of nodes and Fig.4 shows the data graph of 5 clusters in one experiment.…”

“…Al-Karaki et al proposed exact and approximate aggrega-tion algorithms [1]; Aonishi et al studied the impact of agg-regation efficiency on GIT routing [2]; Villas et al proposed a scalable and dynamic data aggregation aware routing protocol for wireless sensor networks [3]; Heinzelman et al proposed LEACH [4] for the network clustering and cluster head election; Younis et al proposed HEED [5] in which the residual energy was taken into account cluster head election; NECCHI et al applied Gossip algorithm to data aggregation [6] and this method was improved in [7]; FAN et al proposed an efficient and robust sensor data aggregation using linear counting sketches [8].…”

Probabilistic Transmitting-based Data Aggregation Scheme for Wireless Sensor Networks

“…Al [5] in which the residual energy was taken into account cluster head election; NECCHI et al applied Gossip algorithm to data aggregation [6] and this method was improved in [7].…”

“…In WSN, sensors communicated with each other using wireless signal and the data transmitted by a sensor will received by all neighbors, thus the communication overhead is the major consumption of sensor's energy. Data aggregation is one of the most important methods to reduce the communication overhead and many schemes had been proposed for decreasing the redundant transmissions.Al [5] in which the residual energy was taken into account cluster head election; NECCHI et al applied Gossip algorithm to data aggregation [6] and this method was improved in [7].In wireless sensor networks, certain range of errors is acceptable and it can be used to reduce the communication overhead. But most of existing cluster-based aggregation schemes mainly focuses on how to reduce the energy consumption of fusion data transmission and take little care of reducing the inner-cluster communication overhead.…”

An Algorithm for Selecting the Cluster Leader in a Partially Connected Sensor Network

“…However, the energy constraint and limited resources of the sensor node introduce a new topic of research in aggregation and routing of data in wireless sensor networks. Thus, clustering topologies have been introduced where the sensor network is partitioned into several clusters to aggregate data and minimize the data transmission, ultimately saving precious energy [1], [4]. Because of the requirement of unattended operation in remote or even potentially hostile locations, sensor networks are extremely energy-limited.…”