Minimum Weighted Clustering Algorithm for Wireless Sensor Networks * Apostolos Xenakis Industrial Systems Institute and University of Thessaly Electrical and Computer Engineering 37 Glavani and 28 October Str. Volos, Greece axenakis@uth.gr Fotis Foukalas Industrial Systems Institute and University of Thessaly Electrical and Computer Engineering 37 Glavani and 28 October Str. Volos, Greece foukalas@uth.gr George Stamoulis Industrial Systems Institute and University of Thessaly Electrical and Computer Engineering 37 Glavani and 28 October Str. Volos, Greece georges@uth.gr ABSTRACT Extending network lifetime is a primary design objective for a wireless sensor network (WSN). Efficient clustering among sensor nodes seems a promising solution to evenly balance energy consumption and thus extend node and network life- time. One of the most dominant clustering algorithms for energy efficient cluster formation is LEACH, because it bal- ances node energy consumption. However, stochastic clus- ter head election of LEACH poses problems. In this paper, we propose a new clustering algorithm, named Minimum Weighted Clustering Algorithm (MWCLA) and compare its effectiveness with LEACH. MWCLA functions as follows: 1) Selects cluster heads based on cost criterion and quan- tifies the suitability of candidate cluster head by applying weights and 2) Rotates cluster head roles among nodes in a deterministic way, based on residual energy levels. In our simulations, we compare MWCLA with LEACH in terms of network lifetime and we highlight the cases where MW- CLA is better in balancing node energy consumption, im- proving the efficiency in energy dissipation for communica- tion and prolonging network lifetime. Our comparisons are based on three metrics: FND (First Node Dies), HND (Half Node Dies) and LND (Last Node Dies). MWCLA succeeds a network lifetime extension of 20% - 30% as compared to LEACH. Keywords wireless sensor networks, clustering algorithm, balanced en- ergy consumption, network lifetime. 1. INTRODUCTION * (Produces the permission block, and copyright informa- tion). For use with SIG-ALTERNATE.CLS. Supported by ACM. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full cita- tion on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or re- publish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. PCI 2015, October 01-03, 2015, Athens, Greece c  2015 ACM. ISBN 978-1-4503-3551-5/15/10. . . $15.00 DOI: http://dx.doi.org/10.1145/2801948.2801999 A typical WSN consists of several low - cost, low - power sensor nodes which communicate through the wireless medium based on IEEE 802.15.4 protocol. A wide range of appli- cations for WSN include military, medical, environmental monitoring, agriculture and many others [1]. Sensor nodes rely on limited battery power supply, communication and processing capabilities. To this end, how to manage their en- ergy reserves efficiently , balance network energy consump- tion and extend network lifetime has become primary design objective for WSNs. Among current researches for energy efficiency in WSNs, clustering algorithms are considered as the most influential. Low - Energy Adaptive Clustering Hi- erarchy (LEACH) is a widely known and energy efficient clustering algorithm for WSNs [2]. It succeeds in extending network lifetime compared to deployments without cluster- ing and direct base station (BS) transmission. However, the stochastic cluster head selection and rotation in LEACH, which do not take into consideration the network topology, does not always succeed in balancing energy consumption efficiently and lead to premature energy depletion for the most of the sensor nodes. To deal with LEACH disadvantage, many algorithms were proposed afterwards which improve LEACH functionality. In most cases, these algorithms propose additional features in LEACH set up and steady phase. In [3], authors pro- pose an improvement to LEACH, the I-LEACH algorithm, by incorporating node’s residual energy and distance among cluster heads, into cluster - head election phase. Addition- ally, cluster heads transfer data to BS either with single hop of multi - hop manner for saving energy. To this end, I- LEACH uses node’s energy reserves more efficient and ex- tends network lifetime. Similarly, authors in [4] analyse the advantages and disad- vantages of LEACH and propose an improved LEACH ver- sion, the LEACH-L. This version also incorporates energy reserves in cluster head threshold parameter and considers the impact of distance among nodes and BS while electing a cluster head. The non-cluster head nodes choose to join a potential cluster not only via using signal strength indicator, but according to a cost function, which incorporates energy and distance metrics also. To this end, LEACH-L extends network lifetime by ×2 for various network set ups. Another variant of LEACH is proposed in [5], which ex- tends its the stochastic decision. As a consequence, a deter- ministic component in cluster head selection phase is pro-