Manchester Metropolitan University's Research Repository

Green Computing in Sensors Enabled Internet of Things: Neuro Fuzzy Logic Based Load Balancing

Kumar, Pankaj, Kumar, Sushil, Dohare, Upasana, Kumar, Vinod and Kharel, Rupak ORCID logoORCID: https://orcid.org/0000-0002-8632-7439 (2019) Green Computing in Sensors Enabled Internet of Things: Neuro Fuzzy Logic Based Load Balancing. Electronics, 8 (4). p. 384. ISSN 2079-9292

Published Version
Available under License Creative Commons Attribution.

Download (570kB) | Preview


Energy is a precious resource in sensors enabled Internet of Things (IoT). Unequal load on sensors deplete their energy quickly that may interrupt operations of the network. Further, single artificial intelligence technique is not to be enough to fulfill the problem of load balancing and minimize energy consumption because of integration of ubiquitous nature of smart sensors enabled IoT. In this paper, we present an adaptive neuro fuzzy clustering algorithm (ANFCA) to balance the load evenly among sensors. We synthesize fuzzy logic and neural network to counterbalance the selection of optimal number of cluster heads and evenly distribution of load among sensors. We develop fuzzy rules, sets, and membership functions of adaptive neuro fuzzy inference system to decide whether a sensor play the role of cluster head. The proposed ANFCA outperforms the state of the art algorithms in terms of node death percentage, number of alive nodes, average energy consumption, and standard deviation of residual energy.

Impact and Reach


Activity Overview
6 month trend
6 month trend

Additional statistics for this dataset are available via IRStats2.


Actions (login required)

View Item View Item