A Forwarding Station Integrated with Optimal Cluster Number Selection in Wireless Sensor Networks

2012 ◽  
Vol 201-202 ◽  
pp. 745-748
Author(s):  
Tung Jung Chan ◽  
Ching Mu Chen ◽  
Tsair Rong Chen

In wireless sensor networks, power consumption is the most important issue. That is wireless sensors are normally deployed into unattended places where power of sensors is hard to be charged. Indeed, the network lifetime of wireless sensor networks equipped with city power or deployed into attended place is much longer than those wireless sensors equipped with batteries. In general, wireless sensor nodes are connected together and become a network after deployed into certain places. With the certain range places that wireless senor nodes deployed into, finding the optimal clusters can increase the entire network lifetime. Also, adding the forwarding station extends the network lifetime. Therefore, this paper proposes the integration of both the forwarding station and optimal clusters in ad-hoc wireless sensor networks. Simulation results show that the entire network lifetime proposed is extended in this paper compared to both optimal cluster number selection and normal forwarding station.

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668968 ◽  
Author(s):  
Sunyong Kim ◽  
Chiwoo Cho ◽  
Kyung-Joon Park ◽  
Hyuk Lim

In wireless sensor networks powered by battery-limited energy harvesting, sensor nodes that have relatively more energy can help other sensor nodes reduce their energy consumption by compressing the sensing data packets in order to consequently extend the network lifetime. In this article, we consider a data compression technique that can shorten the data packet itself to reduce the energies consumed for packet transmission and reception and to eventually increase the entire network lifetime. First, we present an energy consumption model, in which the energy consumption at each sensor node is derived. We then propose a data compression algorithm that determines the compression level at each sensor node to decrease the total energy consumption depending on the average energy level of neighboring sensor nodes while maximizing the lifetime of multihop wireless sensor networks with energy harvesting. Numerical simulations show that the proposed algorithm achieves a reduced average energy consumption while extending the entire network lifetime.


2005 ◽  
Vol 1 (2) ◽  
pp. 245-252 ◽  
Author(s):  
P. Davis ◽  
A. Hasegawa ◽  
N. Kadowaki ◽  
S. Obana

We propose a method for managing the spontaneous organization of sensor activity in ad hoc wireless sensor systems. The wireless sensors exchange messages to coordinate responses to requests for sensing data, and to control the fraction of sensors which are active. This method can be used to manage a variety of sensor activities. In particular, it can be used for reducing the power consumption by battery operated devices when only low resolution sensing is required, thus increasing their operation lifetimes.


2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881130 ◽  
Author(s):  
Jaanus Kaugerand ◽  
Johannes Ehala ◽  
Leo Mõtus ◽  
Jürgo-Sören Preden

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.


Author(s):  
Asfandyar Khan ◽  
Azween Abdullah ◽  
Nurul Hasan

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.


Author(s):  
Nandoori Srikanth ◽  
Muktyala Sivaganga Prasad

<p>Wireless Sensor Networks (WSNs) can extant the individual profits and suppleness with regard to low-power and economical quick deployment for numerous applications. WSNs are widely utilized in medical health care, environmental monitoring, emergencies and remote control areas. Introducing of mobile nodes in clusters is a traditional approach, to assemble the data from sensor nodes and forward to the Base station. Energy efficiency and lifetime improvements are key research areas from past few decades. In this research, to solve the energy limitation to upsurge the network lifetime, Energy efficient trust node based routing protocol is proposed. An experimental validation of framework is focused on Packet Delivery Ratio, network lifetime, throughput, energy consumption and network loss among all other challenges. This protocol assigns some high energy nodes as trusted nodes, and it decides the mobility of data collector.  The energy of mobile nodes, and sensor nodes can save up to a great extent by collecting data from trusted nodes based on their trustworthiness and energy efficiency.  The simulation outcome of our evaluation shows an improvement in all these parameters than existing clustering and Routing algorithms.<strong></strong></p>


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Baniata ◽  
Jiman Hong

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities. These advances are also helping to monitor smart cities and making our living environments workable. However, sensor nodes are constrained in energy supply if they have no constant power supply. Moreover, communication links can be easily failed because of unequal node energy depletion. The energy constraints and link failures affect the performance and quality of the sensor network. Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN. In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime. Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.


2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.


2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.


Author(s):  
Adarsh Sagar ◽  
T. G. Basavaraju ◽  
K. B. Surekha

In the most of the real world scenarios, wireless sensor networks are used. Some of the major tasks of these types of networks is to sense some information and sending it to monitoring system or tracking some activity etc. In such applications, the sensor nodes are deployed in large area and in considerably large numbers [1]-[3]. Each of these node will be having constrained resources whether it might be energy, memory or processing capability. Energy is the major resource constraint in these types of networks. Hence enough care to be taken in all aspects such that energy can be used very efficiently. Different Activities which will be taking place in a sensor node are sensing, radio operations and receiving and computing. Among all these operations, radio consumes maximum power. Hence there is a need of reducing the power consumption in such radio operations. In the proposed work a software module is developed which will reduce the number of transmissions done to the base station. The work compares the consecutively sensed data and if these data are same then the old data then the old data will be retained. In other case the newly sensed data will be sent to the sink node. This technique reduces the number of data transmissions in a significant way. With the reduced number of transmissions, the energy saved in each node will be more, which will increase the lifetime of the entire network.


The network delay and power consumptions are the two main factors governing the efficiency of wireless sensor networks. In this paper, our goal is to minimize the delay and maximize the lifespan of event-based wireless sensor networks in which activities occur infrequently.In such architectures, most of the power is fed on when the radios are on, ready for a packet to arrive.Sleep–wake scheduling is a highly efficient mechanism to prolong the lifetime of these power-constrained wireless sensor networks. However, sleep–wake scheduling could provide result with considerable delays. This research attempts to limit these delays by developing “anycast” based packet forwarding schemes that places each node opportunistically forwards a packet to the first neighboring node which wakes up amongst more than one candidate nodes.In this paper, we propose to optimize the anycast forwarding schemes by minimizing the anticipated packetdelivery delays from the sensor nodes to the sink node. Based on this analysis, we then provide a solution to the joint control problem of how to optimally manage the architecture parameters of the sleep–wake scheduling protocol and the any-cast packetforwarding protocol to maximize the network lifetime, with reference to a constraint on the expected end-to-end packetarriving delay.


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