Analytical Model for Underwater Wireless Sensor Network Energy Consumption Reduction

In an Underwater Wireless Sensor Network (UWSN), extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system. Systems based on clustering strategies, instead of each node sending information by itself, utilize cluster heads to collect information inside the clusters for forwarding collective information to sink. This can effectively minimize the total energy loss during transmission. The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth. Round base clustering strategy works in rounds, where each round comprises three fundamental stages: cluster head selection, grouping or node association, and data aggregation followed by forwarding data to the sink. In UWSN, the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works. In this paper, the cluster head setup period has been considered the main contributor to extra energy utilizer. A numerical channel model is proposed to compute extra energy. It is performed by using a UWSN broad model. The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions

Adaptive energy efficient circular spinning protocol for dynamic cluster based UWSNs

Under Water Sensor Network (UWSN) is a novel paradigm for exploring marine environments such as offshore and mineral exploration, underwater surveillance, and sea habitat monitoring. However, a good quality underwater communication is difficult to achieve due to different constraints such as limited bandwidth, acoustic propagation issues, delays, battery replacement hitches, etc. In recent works, efficient energy-based designing and overall performance evaluation of the UWSN has become a major consideration. Cluster-based sensor networks have proven to be a successful way to increase the network's load congruency and scalability while lowering the system's total energy consumption. Usually, clustering algorithms work in three phases; cluster setup, data collection, and transmission to sink. In these types of dynamic cluster-based networks, energy consumed in cluster setup has been considered insignificant. Since these network energy consumptions are not part of data communication, we consider it extra energy consumption. In this paper, a new Energy Efficient Circular Spinning (EECS) dynamic clustering algorithm has been proposed to provide an improved cluster setup system and to minimize energy usage in re-clustering or cluster setup. Our proposed EECS mechanism suggests that system performance can improve by reducing the Cluster Head (CH) selection phase or cluster setup phase and can ultimately minimize the energy consumption of networks. It is demonstrated that by reducing the transmission of superfluous control messages during the cluster arrangement stage, approximately 21.5% to28.4% of the total network energy expended can be saved. This paper also compares the extra energy consumption, total network energy consumption, and life of the network in our proposed EECS mechanism to two different mechanisms, (1) Adaptive LEACH for UW, (2) UMOD-LEACH. The optimum value of cluster head has been calculated from energy consumption of different protocols and results show that our proposed EECS can prolong network lifetime by 21.5% and 28.4%from the above-mentioned algorithms consequently. In future, we will extend outwork for multi-hop dynamic cluster base mechanism for UW

A Uniform Clustering Mechanism for Wireless Sensor Networks

In wireless sensor networks with dynamic clustering, the cluster heads are usually not selected on the basis of their locations. This causes irregular distribution of cluster heads and highly variable number of nodes in the clusters. Also, some of the clusters are spread over large areas within the network, causing limited spatial correlation between associated sensor nodes. These irregularities in cluster placements and dimensions negatively impact the efficiency of a wireless sensor network. For example, for a cooperative data aggregation, it necessitates variable or large sized packets while the aggregations, based on spatial correlation of sensor nodes, cannot be exploited easily. In this paper, we have developed a Distributed Uniform Clustering Algorithm (DUCA) for cluster based WSN. In DUCA, cluster formation mechanism is based on a virtual-grid system and sensing ranges of nodes that provide even distribution of clusters, homogenized cluster sizes, and reduced energy consumption. Simulation results show that DUCA improves the distribution of cluster heads by more than 2 times and reduces the energy consumption within a range of 15% to 50% as compared to the existing protocols

A Survey of Energy Conservation Mechanisms for Dynamic Cluster Based Wireless Sensor Networks

WSN (Wireless Sensor Network) is an emerging technology that has unlimited potential for numerous application areas including military, crisis management, environmental, transportation, medical, home/ city automations and smart spaces. But energy constrained nature of WSNs necessitates that their architecture and communicating protocols to be designed in an energy aware manner. Sensor data collection through clustering mechanisms has become a common strategy in WSN. This paper presents a survey report on the major perspectives with which energy conservation mechanisms has been proposed in dynamic cluster based WSNs so far. All the solutions discussed in this paper focus on the cluster based protocols only.We have covered a vast scale of existing energy efficient protocols and have categorized them in six categories. In the beginning of this paper the fundamentals of the energy constraint issues of WSNs have been discussed and an overview of the causes of energy consumptions at all layers of WSN has been given. Later in this paper several previously proposed energy efficient protocols of WSNs are presented

Analytical Model for Underwater Wireless Sensor Network Energy Consumption Reduction

In an Underwater Wireless Sensor Network (UWSN), extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system. Systems based on clustering strategies, instead of each node sending information by itself, utilize cluster heads to collect information inside the clusters for forwarding collective information to sink. This can effectively minimize the total energy loss during transmission. The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth. Round base clustering strategy works in rounds, where each round comprises three fundamental stages: cluster head selection, grouping or node association, and data aggregation followed by forwarding data to the sink. In UWSN, the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works. In this paper, the cluster head setup period has been considered the main contributor to extra energy utilizer. A numerical channel model is proposed to compute extra energy. It is performed by using a UWSN broad model. The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions