Article
In-network data aggregation plays an important role on energy consumption from the point of reducing the amount of communication in cluster-based wireless sensor networks. The selection of cluster heads is usually based on two criteria which are the number of cluster heads network needed and the times of every node serving as the cluster head. Too much or too little cluster head number will shorten the network lifetime for the energy premature depletion of some sensor nodes, so it has a great
Mingxin Yang
International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1935–1955
Article
Data Aggregation (DA) is one of the most frequently used techniques in Wireless Sensor Networks (WSNs) to improve the network lifetime. It involves gathering, consolidating, and routing the sensory data collected by sensor nodes. However, research studies have demonstrated that the dependability of the DA process affects severely when malicious nodes are present in the network. Many security solutions using cryptography and Intrusion Detection System (IDS) have been proposed in the literature
P. Raghu Vamsi,
Krishna Kant
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 537–562
Article
We propose a routing scheme for data gathering and aggregation in wireless sensor networks. The scheme aims to optimise an aggregation tree in order to minimise the energy dissipation of data aggregation and transmission. A modified particle swarm optimisation algorithm is developed in the proposed scheme. In addition, the routing scheme uses a generic data aggregation model which accommodates different correlation conditions. The performance of the proposed scheme is evaluated and compared
Yuexian Wang,
Cheng Chew Lim
International Journal of Advanced Network, Monitoring and Controls , ISSUE 1, –
Article
G. Edwin Prem Kumar,
K. Baskaran,
R. Elijah Blessing,
M. Lydia
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 818–844
Research paper
individual data aggregation and deals with multivariate analysis of interval- valued, multi-valued and histogram data. The paper discusses the scale effect of MAUP which occurs in a gravity model of population migrations and shows how SDA can deal with this problem. Symbolic interval-valued data was used to determine the economic distance between regions which served as a separation function in the model. The proposed approach revealed that economic disparities in Poland are lower than official
Justyna Wilk
Statistics in Transition New Series , ISSUE 2, 243–264