Energy Efficient Clustering in Wireless Sensor Network

Journal of ICT Research and Applications

In wireless sensor networks, clustering provides an effective way of organising the sensor nodes to achieve load balancing and increasing the lifetime of the network. Unequal clustering is an extension of common clustering that exhibits even better load balancing. Most existing approaches do not consider node density when clustering, which can pose significant problems. In this paper, a fuzzy-logic based cluster head selection approach is proposed, which considers the residual energy, centrality and density of the nodes. In addition, a fuzzy-logic based clustering range assignment approach is used, which considers the suitability and the position of the nodes in assigning the clustering range. Furthermore, a weight function is used to optimize the selection of the relay nodes. The proposed approach was compared with a number of well known approaches by simulation. The results showed that the proposed approach performs better than the other algorithms in terms of lifetime and other metrics.

IAEME PUBLICATION, 2018

A Wireless Sensor Network (WSN) contains many tiny sensor nodes which have minimum battery power, low-cost, with computing and communication competences with limited range for communication with multi model and embedded sensing capability. Environment, habitat and military surveillance monitoring are the most significant application of WSN. The lifetime of the network depends on energy power of these sensor nodes. To efficiently improve the lifetime of the network, a cluster- based routing protocol is an effective scheme. In that, the numbers of sensor nodes are split into several groups known as Clusters. Based on some parameters, each cluster node will elect a node from their cluster to be the head, called as cluster head (CH). All sensor nodes gather the information from their surroundings and send it to the corresponding CHs. Afterward the data will be send to the Base Station (Sink) by the CHs. Thus, selecting the suitable CH can decline significant extent of energy dissipation. In this paper, we present a fuzzy based approach which will elect the CH with respect to energy and distance. On the other hand, we also exhibited the working benefits of using mobile sink, which travels in the network area and collects the information from sensor nodes, for improving the lifetime of the network, using different data collection strategies, instead of static base station. The Rendezvous nodes will have the ability to transfer data when the mobile sink comes near. The proposed technique is analyzed using network simulator.

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), 2013

Minimization of energy consumption is one of the most important research areas in Wireless Sensor Networks. Nowadays, the paradigms of computational intelligence (CI) are widely used in WSN, such as localization, clustering, energy aware routing, task scheduling, security, etc. Though many fuzzy based clustering techniques have been proposed earlier, many of them could not increase the total network life time in terms of LND (Last Node Dies) with comparing to LEACH. In this paper, a fuzzy logic based energy-aware dynamic clustering technique is proposed, which increases the network lifetime in terms of LND. Here, two inputs are given in the fuzzy inference system and a node is selected as a cluster head according to the fuzzy cost (output). The main advantage of this protocol is that the optimum number of cluster is formed in every round, which is almost impossible in LEACH (low-energy adaptive clustering hierarchy). Moreover, this protocol has less computational load and complexity. The simulation result demonstrates that this approach performs better than LEACH in terms of energy saving as well as network lifetime.

Indonesian Journal of Electrical Engineering and Computer Science, 2022

Clustering is the fundamental issue in terms of ensuring long-term operation of wireless sensor networks (WSNs). The problem of hot spots remains the most prominent research challenge relating to the design of energy-efficient clustering algorithm. This paper proposed a protocol, namely an uneven clustering and fuzzy logic-based energy-efficient (UCFLEE), for prolonging network lifetime. Depending on the communication distance, the UCFLEE protocol divides the network into uneven clusters for suppressing the hot spot problem. The fuzzy logic selects the optimal cluster head in accordance with certain parameters. The advocated method adopts a dynamic energy threshold to chnage the cluster head. The UCFLEE protocol is dependent on the iterative deepening A (IDA) star algorithm for identifying the routing path from the cluster heads to the base station. The IDA-star method is reliant upon a cost bounded method to select the optimal solution for the base station. The UCFLEE protocol is t...

7'th International Symposium on Telecommunications (IST'2014), 2014

Clustering is an effective approach for organizing network nodes into hierarchical topology, aggregating sending data to the base station and prolonging the network lifetime. However, it may cause sudden death of nodes in some network regions, i.e., hot spots, due to heavy traffic load leading to disruption in network services. This problem is traditional for data collection scenarios in which Cluster Heads (CHs) are responsible of gathering and relaying the sensed data. To balance the workload over the nodes, the CH role must be rotated among all nodes and the cluster size should be determined such that uniformly distribute the energy consumption in network. In this paper, we propose a clustering algorithm that selects the nodes with highest remaining energy in each region as candidate CHs in order to pick the best nodes among them as final CHs. To consider the hot spot issue it employs fuzzy logic in order to adjust the cluster radius of CH nodes based on some local information (distance to base station and local density). Simulation results show that the proposed approach achieves an improvement in terms of network lifetime through mitigating the hot spot problem.

2011 IEEE Colloquium on Humanities, Science and Engineering (CHUSER)

In general, environment monitoring cluster based hierarchical routing protocol is among the most common protocol being opted due to the load balancing among each other sensor. Sensors are randomly deployed in a specific area to collect useful information periodically for a few months or even a few years. Therefore, battery power limitation becomes a challenging issue. It is also impractical to maintain the network lifetime by changing the battery frequently. Low energy adaptive cluster hierarchical (LEACH) is one of the common clustering protocols that will elect the cluster head based on the probability model which will possibly lead to a reduce in network lifetime due to election of cluster head with a least desired location in the network. For wireless sensor networks, the distribution of cluster head selection directly influences the network's lifetime. This paper presents factors which will affect the network lifetime and apply fuzzy logic based cluster head selection conducted in base station. The base station considers two selection criteria from sensor nodes which are energy level and distance to the base station to select the suitable cluster head that will prolong the first node die (FND) time, data stream guaranteed for every round and also increase the throughput received by the base station before FND.

International Journal of Computational Intelligence Systems

Clustering is carried out to explore and solve power dissipation problem in wireless sensor network (WSN). Hierarchical network architecture, based on clustering, can reduce energy consumption, balance traffic load, improve scalability, and prolong network lifetime. However, clustering faces two main challenges: hotspot problem and searching for effective techniques to perform clustering. This paper introduces a fuzzy unequal clustering technique for heterogeneous dense WSNs to determine both final cluster heads and their radii. Proposed fuzzy system blends three effective parameters together which are: the distance to the base station, the density of the cluster, and the deviation of the node's residual energy from the average network energy. Our objectives are achieving gain for network lifetime, energy distribution, and energy consumption. To evaluate the proposed algorithm, WSN clustering based routing algorithms are analyzed, simulated, and compared with obtained results. These protocols are LEACH, SEP, HEED, EEUC, and MOFCA.

The wireless sensor networks combines sensing, computation, and communication into a single small device. These devices depend on battery power and may be placed in hostile environments replacing them becomes a tedious task. Thus improving the energy of these networks becomes important. Clustering in wireless sensor network looks several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network.

2013

In order to gather information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Most proposed clustering algorithms do not consider the location of the base station. This situation causes hot spot problems in multi-hop WSNs. In this paper, we analyze a fuzzy clustering algorithm (FCA) which aims to prolong the lifetime of WSNs. This algorithm adjusts the cluster-head radius considering the residual energy and distance to the base station parameters of the sensor nodes. This helps to decrease the intra-cluster work of the sensor nodes which are closer to the base station or have lower battery level. Fuzzy logic is utilized for handling the uncertainties in cluster-head radius estimation. We compare this algorithm with the low energy adaptive clustering hierarchy (LEACH) algorithm according to the parameters of first node dies half of the nodes alive and energy-efficiency metrics. Our simulation results show that the fuzzy clustering approach performs better than LEACH. Therefore, the FCA is a stable and energy-efficient clustering algorithm.

IRJET, 2021

The primary challenges in defining and organizing the operation of wireless sensor networks are the enhancement of energy utilization and the life of the system. Clustering is a powerful approach to aligning the system to the associated order, adjusting the load and improving the life of the system. In a cluster-based network, the cluster head closer to the sink depletes its energy quickly resulting in hot spot problems. Numerous algorithms on unequal clustering are being considered to conquer this problem. The downside in these algorithms is that the nodes that join the same cluster head will overburden the cluster head. So in this paper, we propose an algorithm called fuzzy based unequal clustering to improve the execution of a cluster. The proposed study is tested using simulation. The proposed algorithm is compared to two algorithms, one with an identical clustering algorithm called LEACH and the other with an unequal clustering algorithm called EAUCF. The simulation results using MATLAB show that the proposed algorithm offers better performance compared to the other two algorithms.