A New MILP Formulation and Distributed Protocols for Wireless Sensor Networks Lifetime Maximization

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

Energy Efficiency and Network Lifetime Maximization in Wireless Sensor Networks Using Improved Ant Colony Optimization

Extensive research is being done on Wireless sensor Networks (WSNs) in present decade. WSNs consist of large number of sensor nodes which perform sensing of certain phenomena and send the sensed data to the sinks. This operation consumes energy of sensor nodes which effects the lifetime of a network. To prolong the lifetime of WSNs various strategies and routing algorithms have been proposed. Use of mobile sinks has proved effective in this respect. In this paper we are analyzing the impact of multiple mobile sinks with proactive hierarchical clustering protocols LEACH and network reactive hierarchical protocol TEEN. This paper will give simulation based analysis of using multiple mobile sinks in network and their effect on lifetime of a network. Performance analysis will be done on basis of dead nodes, alive nodes, throughput and residual energy.

In this paper we investigate the benefits of a heterogeneous architecture for wireless sensor networks composed of a few resource rich mobile nodes and a large number of simple static nodes. These mobile nodes can either act as mobile relays or mobile sinks. To investigate the performance of these two options and the trade-offs associated with these two options, we first consider a finite network. We then compute the lifetime for different routing algorithms for three cases (i) when the network is all static (ii) when there is one mobile sink and (iii) when there is one mobile relay. We find that using the mobile node as a sink results in the maximum improvement in lifetime. We contend however that in hostile terrains, it might not always be possible for the sink to be mobile. We then investigate the performance of a large dense network with one mobile relay and show that the improvement in network lifetime over an all static network is upper bounded by a factor of four. Also, the proof implies that the mobile relay needs to stay only within a two hop radius of the sink. We then construct a joint mobility and routing algorithm which comes close to the upper bound. However this algorithm requires all the nodes in the network to be aware of the location of the mobile node. We then proposed an alternative algorithm, which achieves the same performance, but requires only a limited number of nodes in the network to be aware of the location of the mobile. We finally compare the performance of the mobile relay and mobile sink and show that for a densely deployed sensor field of radius R hops, we require O(R) mobile relays to achieve the same performance as the mobile sink.

Wireless sensor networks (WSNs) face challenges in maintaining network lifetime due to energy limitations. To optimize energy usage, techniques such as node clustering and data transmission through the shortest path are employed. However, the selected Cluster Head (CH) node eventually becomes inactive as its energy is depleted during continuous transmission to the sink. To overcome this issue, we propose the utilization of Energy-Efficient Bat-Moth Flame Optimization (EEBMFO) in WSNs, aiming to enhance network lifetime. Our strategy makes use of the echolocation signal pattern that bats use to identify prey within a certain range. In a similar manner, nodes fall into clusters within the range of the CH, and the CH is chosen by looking at the highest residual energy. In addition, we use spiral path data transmission and Moth Flame optimization to route data from the source node to the CH. By combining bat and moth flame optimizations and considering each node’s residual energy, we aim to improve the network’s lifespan. With the use of simulations and performance measures such network lifetime, throughput, latency, dependability, and network stabilization, this research provides a thorough analysis of the suggested EEBMFO approach in WSNs. When compared to current techniques, the results show a noteworthy 11–16% increase in network longevity. These findings validate the efficacy of EEBMFO in prolonging the lifespan of WSNs, offering a promising solution for energy-efficient and sustainable wireless sensor networks.

Large scale Wireless Sensor Networks (WSNs) often utilize multiple mobile sink nodes to improve the network lifetime and scalability. However, most of the studies conducted in this context, consider unlimited buffer capacity for the sink nodes. But, this model cannot truly describe the behavior of WSNs and causes congestion in the sink nodes. To solve this problem, in this paper, we use limited buffer capacity for each mobile sink node in WSNs and present a two-level Fuzzy Logic Controller (FLC)-based dynamic clustering scheme and congestion prevention. In this scheme, sink nodes try to predict current load based on their loads in previous rounds by using ARIMA method and based on it, the first FLC selects the nearest uncongested sink node from multiple available mobile sink nodes. Then, the second FLC applies the output of the first FLC to select appropriate nodes as cluster heads to mitigate the energy consumption in the network. Extensive simulation results indicate the effectiveness of the proposed fuzzy logic-based solution in reducing congestion in the mobile sink nodes and improving load balancing in them which these result in the network lifetime improvement and decreasing the number of retransmissions.

Maximization of lifetime of wireless sensor network (WSN) is an emerging area of research in present scenario. Many authors are performing their research work, so that they could achieve lower energy consumption for the sensor network which leads to increase in lifetime of network. Our work focuses on sink mobility in a fixed trajectory within a wireless sensor network while sensed data are required to be collected. We divide the whole sensor network into two different regions as direct communication area (DCA) and multi-hop communication area (MCA). Sensors node that lies in DCA is at one hop count distance from the sink node trajectory while sensors within MCA are at more than one hop count from the trajectory. We considered all the sensors that are within DCA as subsink nodes. During sink mobility, whenever a subsink is closer to the mobile sink node, then it starts transmitting its data to the sink node. But those sensors that are within MCA needs to search an appropriate sink node for sending its sensed data to the subsink so that on further stage, that subsink could provide those data to the sink node whenever it is in nearest proximity of that subsink. Basically, a sink node is the ultimate destination for the data while a subsink node acts as a relay node for the nodes that are within MCA. So our work is to find out the appropriate subsink node from a given set of subsinks. For doing so, we used location-aided routing on global positioning system (GPS)-enabled sensors and sink node. Our work is validated through simulation experiments using NS-2.

Wireless sensor networks (WSNs) are formed using a cluster of sensor nodes (SNs), deployed randomly to perform sensing operations in an area under observation. Due to the unavailability of an external power source, the energy efficiency considered as one of the critical issues in WSNs. Selection of a sensor node (SN) from a wireless sensor network (WSN) cluster to serve as an aggregator or cluster head (CH), considered as an efficient method to increase the lifetime of wireless sensor network (WSN). In this paper, we have proposed an energy efficient CH selection scheme for WSN, to enhance the lifetime and average residual energy of a single WSN cluster. The proposed strategy nominates a group SNs as CHs, based on their channel condition with the base station (BS) and their residual energy. The proposed algorithm is helpful in solving the problem of unbalanced energy consumption in WSNs. Furthermore, the mechanism of using mobile sink during the hand-off stage helps to overcome the delay in data transmission. Moreover, the incorporation of energy harvesting significantly increases the lifetime of WSN. In comparison to a state-of-art technique available in the literature, our scheme shows a 33% increase in lifetime and presents a steady decrease in residual energy for the same rounds of data transmission.

The sensor network performs gathering, monitoring, and tracking of objects in the given area. The sensor nodes are normally distributed randomly in the network area for collecting the information. The major issues in Wireless Sensor Networks (WSN) are coverage, energy, and limited resources. Sensor Nodes’ (SN) performance depends on so many parameters but normally depends on Residual Energy (RE) and Distance from the base station. The Cluster Head (CH) cooperatively communicates with Base Station (BS) via routing protocols. The proposed Energy Efficient Multilevel Region Based (EEMRB) protocol performs the task by partitioning the entire network area into multiple levels and sub-levels. The sub-levels are partitioned to perform clusters to communicate the sensor via CH (s) using single/multi-hop communication to BS. The proposed protocol is compared with the Stable Election Protocol and shows improvement in network lifetime. Based on the proposed protocol data set, a Multivariate Polynomial Regression (MPR) Model is proposed to predict network lifetime. The model uses packet size and node density as network design parameters. The simulation results show that the size of the packet and network area play a major role in network lifetime. Therefore, the lifetime of the predicted model and EEMRB protocol are close to each other. This prediction model is suitable for the prediction of any network area's lifetime.

One of the major design goals in Wireless Sensor Networks (WSN) is to improve network lifetime. In this paper, an efficient clustering protocol with multi-hop routing is proposed which aims at increasing network lifetime. In the initialization phase, the base station elects cluster heads (CHs) based on the residual energy of the sensor nodes. The clusters formed by the CHs initially are maintained till all its member nodes die, while the cluster heads are rotated within the formed clusters based on the residual energy levels of the nodes at the beginning of each round. The cluster heads aggregate the data received from cluster members and send it to the base station in either one or two hops depending on whether the node is a level 1 CH or a level 2 CH, which is decided by the CH's distance from the base station. The proposed clustering protocol has shown a significant 300 percent improvement in network lifetime as measured by the time till the first death of a node and a 10 percent increase in the total number of packets delivered to the base station, when compared to conventional LEACH. The MATLAB simulation performed considers the network area to be rectangular (100m x 100m) with the base station outside the network area.

Wireless sensor networks with the mobile sink can help to prevent the hot-spot problem and improve the network lifetime. However, in practice, the trajectories of the sink can not ideally change due to the obstacle of the environment or the requirement of the application. The constraint on trajectory of the mobile sink causes the different connection time between the mobile sink and the sensor node, which might result in the imbalance depletion of energy. We propose here an efficient data gathering policy to jointly consider the constrained mobility of the sink and the different connection time at the sensor node. The policy increases the network lifetime in wireless sensor networks with path-constrained mobile sink by optimizing the assignment sensor node. In addition, we also propose the policy to cope with the overlapped connection time of the sink and sensor node due to the movement of the sink. The simulation results demonstrate the effectiveness of the proposed policy: by carefully considering the trajectory of the sink and effectively assigning the sensor node, the network lifetime is increased.

In WSN, sensors near the sink have to relay the data of the nodes away from the sink and as a result they drain their energy very quickly. It result in network partitioning and can significantly limit the network lifetime. This problem is termed as hotspot problem. Recently, formation of hot spot or energy hole near the sink has emerged as a critical issue for data gathering in WSN. In this paper, we address hotspot problem and purposed Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network. In MSRP, mobile sink moves in the clustered WSN to collect sensed data from the CHs within its vicinity. During data gathering mobile sink also maintains information about the residual energy of the CHs. Mobile sink based on the residual energy of CHs move to the CHs having higher energy. Consequently, the hotspot problem is minimized as the immediate neighbor of the sink is high energy node and it changes because of regular sink movement. It results in a balanced use of WSN energy and improves network life time. To evaluate the performance of the proposed strategy intensive simulation are carried out using OMNet-4.0. Performance of the proposed strategy is compared to the static sink and multiple sinks strategies, using metrics such as energy per packet, and throughput. The simulation results demonstrate that MSRP is effective in prolonging the network lifetime as well as in improving throughput than static sink and multiple sink strategies.

Clustering protocol for data gathering is one of the effective ways to solve the energy hole problem in wireless sensor networks. However, most of the existing clustering protocols focus on the network model with uniform node distribution. They cannot effectively apply to the real network where the sensor nodes are randomly non-uniformly deployed. In this paper, we propose an energy-balanced clustering routing protocol (EBCRP) based on task separation. In this scheme, the network is firstly divided into clusters by using global information. And each of them has the same number of sensor nodes in order to balance the energy consumption of intra-cluster. In succession, task separation, the tasks of traditional single cluster head are separated and achieved by two cluster heads respectively, is proposed to reduce the traffic burden for single cluster head. Then, we explore an energy-efficient and reliable inter-cluster routing algorithm, which considers comprehensively three factors: residual energy, distance and available buffer space of nodes. Simulation results and performance evaluation of EBCRP show significant improvement in network lifetime and energy balance.

Routing Algorithm determines the optimal route to transmit data packet from source to destination. The nodes in wireless sensor networks (WSN) are devoid of abundant energy and hence energy efficiency is the vital benchmarks for data transmission in WSN. The basic importance of wireless sensor networks (WSN) in present scenario is to reduce the node energy consumption such that it improves the data transmission efficiency and reliability to extend entire network life time. In these respect, we need to search the optimal route for data transmission in WSN. Here an Improved Ant Colony Optimization (IACO) based energy efficient routing algorithm is proposed in WSN to solve the issue. The function of improved Low Energy Adaptive Clustering Hierarchy (LEACH) routing algorithm is to select cluster heads (CH) by considering residual energy and the distance in between the nodes. To balance the energy consumption between the nodes, residual energy is used as an energy control factor, which affects the network life time and enhances the data transmission efficiency. An ACO algorithm is applied to search the optimal path from the various available routes in between CH and sink for data transmission. Simulation results show that the proposed method Improved Ant Colony Optimization based Low Energy Adaptive Clustering Hierarchy (IACOLEACH) is found to yield better results over other conventional algorithms.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .