Lifetime Maximization in Wireless Sensor Networks

2013 ◽  
pp. 107-120
Author(s):  
Vivek Katiyar ◽  
Narottam Chand ◽  
Surender Soni
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Status ◽  
Adaptive Clustering ◽  
Map Construction ◽  
Clustering Data

One of the fundamental requirements in wireless sensor networks (WSNs) is to prolong the lifetime of sensor nodes by minimizing the energy consumption. The information about the energy status of sensor nodes can be used to notify the base station about energy depletion in any part of the network. An energy map of WSN can be constructed with available remaining energy at sensor nodes. The energy map can increase the lifetime of sensor networks by adaptive clustering, energy centric routing, data aggregation, and so forth. In this paper, the authors describe use of energy map techniques for WSNs and summarize the applications in routing, aggregation, clustering, data dissemination, and so forth. The authors also present an energy map construction algorithm that is based on prediction.

Lifetime Maximization in Wireless Sensor Networks

2011 ◽  
Vol 1 (2) ◽  
pp. 16-29
Author(s):  
Vivek Katiyar ◽  
Narottam Chand ◽  
Surender Soni
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Status ◽  
Adaptive Clustering ◽  
Map Construction ◽  
Clustering Data

One of the fundamental requirements in wireless sensor networks (WSNs) is to prolong the lifetime of sensor nodes by minimizing the energy consumption. The information about the energy status of sensor nodes can be used to notify the base station about energy depletion in any part of the network. An energy map of WSN can be constructed with available remaining energy at sensor nodes. The energy map can increase the lifetime of sensor networks by adaptive clustering, energy centric routing, data aggregation, and so forth. In this paper, the authors describe use of energy map techniques for WSNs and summarize the applications in routing, aggregation, clustering, data dissemination, and so forth. The authors also present an energy map construction algorithm that is based on prediction.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2016 ◽  
pp. 79-114
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2020 ◽  
pp. 372-399
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

A Heuristic Optimized Algorithm for Energy Optimization in Wireless Sensor Networks

2010 ◽  
Vol 34-35 ◽  
pp. 1019-1023
Author(s):  
Zhao Feng Yang ◽  
Ai Wan Fan
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Optimal Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Battery Capacity

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. In this paper we propose an optimal algorithm with genetic algorithm taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH and LEACH-C, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, and data delivery at the base station than the other routing protocols. Key words: Wireless sensor networks, base station, heuristic optimized genetic algorithm, low energy adaptive clustering hierarchy

scholarly journals RBM: Region-Based Mobile Routing Protocol for Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Muhammad Fahad Mukhtar ◽  
Muhammad Shiraz ◽  
Qaisar Shaheen ◽  
Kamran Ahsan ◽  
Rizwan Akhtar ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Low Cost ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Key Technology ◽  
Adaptive Clustering ◽  
Normal Ranges

Wireless sensor networks (WSNs) are employed for different applications for the reason of small-sized and low-cost sensor nodes. However, several challenges that include a low powered battery of the sensor nodes restrict their functionality. Therefore, saving energy in the routing process to extend network life is a serious concern while deploying applications on WSN. To this end, the key technology is clustering, which helps maximize scalability and network lifecycle. Base station (BS) collects data, aggregates it, and extracts the required information. To obtain the maximum outcome, the lifetime of the network is maximized by the use of different techniques and protocols. Data transmissions consume most of the network energy, and the transmissions over normal ranges require less energy as compared to transmissions over long ranges. Moreover, the nodes closer to the BS deplete their energy faster as compared to distant nodes because of traffic overload. The proposed protocol is aimed at reducing energy consumption and increasing the network lifetime. For this purpose, the network is divided into two regions: region 1 closer to the BS communicating directly, whereas region 2 farther away from the BS having routing nodes to communicate with the BS. Routing nodes do not take part in sensing function but will only move in region 2 collecting data and forwarding it to BS. MATLAB is used as the simulation tool for evaluation, and the results are compared with the existing optimized region-based efficient routing (AORED) and low-energy adaptive clustering hierarchical protocol (LEACH) techniques. The comparison showed that energy conservation and lifetime increased by 15%, and throughput is increased by more than 5% approximately.

scholarly journals M-Connected Coverage Problem in Wireless Sensor Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
S. Mini ◽  
Siba K. Udgata ◽  
Samrat L. Sabat
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Coverage ◽  
Coverage Problem ◽  
Adaptive Clustering ◽  
Connected Coverage ◽  
Target Coverage Problem

Solving coverage problem alone is not adequate in a wireless sensor network, since data has to be transmitted to the base station. This leads to the lookout for an energy efficient method to solve connected coverage problem. This paper addresses M-connected (each sensor node will have at least M other sensor nodes within its communication range) target coverage problem in wireless sensor networks, where the required level of connectivity and coverage may be high or low as required. We propose a heuristic for M-connected target coverage problem, where initially a cover is decided and later on it is checked for M-connectivity. M-connectivity for simple coverage, k-coverage, and Q-coverage is focussed on in this paper. We use a Low-Energy Adaptive Clustering Hierarchy (LEACH) inspired model, where a cluster is considered as a set of sensor nodes satisfying M-connectivity and required level of coverage. It is enough if one among these nodes transmits the monitored information to the base station. When the required level of coverage are high, chances of nodes being connected in the cover is high. Simulation results show that our proposed method can achieve better results than Communication Weighted Greedy Cover (CWGC).

scholarly journals Mobile Device Based Dynamic Key Management Protocols for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Chin-Ling Chen ◽  
Chih-Cheng Chen ◽  
De-Kui Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Key Management ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Direct Access ◽  
Session Key ◽  
Dynamic Key Management ◽  
Dynamic Key

In recent years, wireless sensor network (WSN) applications have tended to transmit data hop by hop, from sensor nodes through cluster nodes to the base station. As a result, users must collect data from the base station. This study considers two different applications: hop by hop transmission of data from cluster nodes to the base station and the direct access to cluster nodes data by mobile users via mobile devices. Due to the hardware limitations of WSNs, some low-cost operations such as symmetric cryptographic algorithms and hash functions are used to implement a dynamic key management. The session key can be updated to prevent threats of attack from each communication. With these methods, the data gathered in wireless sensor networks can be more securely communicated. Moreover, the proposed scheme is analyzed and compared with related schemes. In addition, an NS2 simulation is developed in which the experimental results show that the designed communication protocol is workable.

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

scholarly journals Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Fan Chao ◽  
Zhiqin He ◽  
Renkuan Feng ◽  
Xiao Wang ◽  
Xiangping Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Center ◽  
Mobile Data ◽  
Tour Planning ◽  
Mobile Data Gathering

Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

A Node Authentication Model in Wireless Sensor Networks With Locked Cluster Generation

2021 ◽  
pp. 236-250
Author(s):  
C. R. Bharathi ◽  
Alapati Naresh ◽  
Arepalli Peda Gopi ◽  
Lakshman Narayana Vejendla
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Cluster Formation ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Generation ◽  
Secure Network

In wireless sensor networks (WSN), the majority of the inquiries are issued at the base station. WSN applications frequently require collaboration among countless sensor nodes in a network. One precedent is to persistently screen a region and report occasions. A sensor node in a WSN is initially allocated with an energy level, and based on the tasks of that sensor node, energy will be reduced. In this chapter, two proposed methods for secure network cluster formation and authentication are discussed. When a network is established then all the nodes in it must register with cluster head and then authentication is performed. The selection of cluster head is done using a novel selection algorithm and for authenticating the nodes. Also, a novel algorithm for authentication is used in this chapter. The validation and authorization of nodes are carried over by managing the keys in WSN. The results have been analyzed using NS2 simulator with an aid of list of relevant parameters.

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