Congestion Avoidance and Delay Minimization in Energy Aware Routing of Dynamic ieee 802.11s WMN

Author(s):  
S.P. Shiva Prakash ◽  
T.N. Nagabhushan ◽  
Kirill Krinkin

Minimization of delay in collecting the data at any base stations is one of the major concerns in cluster based Wireless Mesh Networks. several researches have proposed algorithms to control congestion considering static nature of a node. Mobility of a node results in high congestion due to frequent link breakages and high energy consumption due to re-establishment of route during routing process. Hence, the authors consider dynamic nodes with single hop inside the static cluster. The proposed model includes four modules namely, Cluster head selection, slot allocation, slot scheduling and data collection process. the cluster head selection is based on the maximum energy, number of links and link duration. Slot allocation is based on the available energy () and the required energy (). Slot scheduling is carried out based on the link duration. Data at the base station will be collected as they are scheduled. Model is tested using Network Simulator-3 (NS3) and results indicate that the proposed model achieves least delay besides reducing the congestion compared to the existing methods.

2020 ◽  
pp. 164-193
Author(s):  
S.P. Shiva Prakash ◽  
T.N. Nagabhushan ◽  
Kirill Krinkin

Minimization of delay in collecting the data at any base stations is one of the major concerns in cluster based Wireless Mesh Networks. several researches have proposed algorithms to control congestion considering static nature of a node. Mobility of a node results in high congestion due to frequent link breakages and high energy consumption due to re-establishment of route during routing process. Hence, the authors consider dynamic nodes with single hop inside the static cluster. The proposed model includes four modules namely, Cluster head selection, slot allocation, slot scheduling and data collection process. the cluster head selection is based on the maximum energy, number of links and link duration. Slot allocation is based on the available energy () and the required energy (). Slot scheduling is carried out based on the link duration. Data at the base station will be collected as they are scheduled. Model is tested using Network Simulator-3 (NS3) and results indicate that the proposed model achieves least delay besides reducing the congestion compared to the existing methods.


2018 ◽  
Vol 7 (2.7) ◽  
pp. 494
Author(s):  
Kale Navnath Dattatraya ◽  
K Raghava Rao ◽  
D Satish Kumar

It is well known that WSN is one of the leading techniques in granting pervasive computing for various applications regarding health sector and communication sector. However, the raising of issues in WSN is still a burden cause because of certain renowned terms like energy consumption and network lifetime extension. Clustering is a major contribution in any network and moreover Cluster Head selection is also a vital role since it is additively responsible in sending data to the base station, which means that Cluster Head directly makes its communication with base station. Day by day, the researches in cluster head selection get increased, but the requirements are not yet fulfilled. This paper proposes a energy efficient cluster head selection algorithm for maximizing the WSN lifetime. This paper develops a hybrid optimization process termed Group Search Ant Lion with Levy Flight (GAL-LF) for selecting the Cluster head in WSN. The proposed model is compared to the conventional models such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Group Search Optimization (GSO), Ant Lion Optimization (ALO) and Cuckoo Search (CS). The outcome of the simulation result shows the superiority of the proposed model by prolonging the lifetime of the network.  


Author(s):  
Sandeep Kaur ◽  
Dr. Rajeev Bedi ◽  
Mohit Marwaha

In WSNs, the only source to save life for the node is the battery consumption. During communication with other area nodes or sensing activities consumes a lot of power energy in processing the data and transmitting the collected/selected data to the sink. In wireless sensor networks, energy conservation is directly to the network lifetime and energy plays an important role in the cluster head selection. A new threshold has been formulated for cluster head selection, which is based on remaining energy of the sensor node and the distance from the base station. Proposed approach selects the cluster head nearer to base station having maximum remaining energy than any other sensor node in multi-hop communication. The multi hop approach minimizing the inter cluster communication without effecting the data reliability.


2020 ◽  
Author(s):  
Hamid Reza Farahzadi ◽  
Mostafa Langarizadeh ◽  
Mohammad Mirhosseini ◽  
Seyed Ali Fatemi Aghda

AbstractWireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.


Author(s):  
Praveen Kumar Reddy Maddikunta ◽  
Rajasekhara Babu Madda

Energy efficiency is a major concern in Internet of Things (IoT) networks as the IoT devices are battery operated devices. One of the traditional approaches to improve the energy efficiency is through clustering. The authors propose a hybrid method of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. The performance of the hybrid algorithm is evaluated using energy, delay, load, distance, and temperature of the IoT devices. Performance of the proposed method is analyzed by comparing with the conventional methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSO algorithms. The performance of the hybrid algorithm is evaluated using of number of alive nodes, convergence estimation, normalized energy, load and temperature. The proposed algorithm exhibits high energy efficiency that improves the life time of IoT nodes. Analysis of the authors' implementation reveals the superior performance of the proposed method.


2013 ◽  
Vol 392 ◽  
pp. 872-875 ◽  
Author(s):  
Gu Jia ◽  
Yu Wen Wang ◽  
Fan Ji Meng ◽  
Guo Hua Ye ◽  
Guo Lin Wang

The media access control (MAC) protocol based on fixed slot allocation has low throughput and high delay in high load wireless mesh network. In order to improve the performance of wireless mesh network, we propose a scalable adaptive time division multiple access (TDMA) slot allocation algorithm based on the existing fixed TDMA. The algorithm uses the network structure of clustering and builds a more optimized frame structure, cluster head dynamically allocates time slot according to the packet number of the cluster member sent and the priority level, at the same time taking into account the situation of nodes joining and leaving to improve the scalability of the network The simulation results on OPNET network simulation platform show that the algorithm is superior to fixed TDMA algorithm in both throughput and delay.


2019 ◽  
Vol 8 (4) ◽  
pp. 11996-12003

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.


2017 ◽  
Vol 16 (5) ◽  
pp. 6913-6919
Author(s):  
Ramandeep Kaur ◽  
Dinesh Kumar

The lower cost and easier installation of the WSNs than the wired counterpart pushes industry and academia to pay more attention to this promising technology. Large scale networks of small energy-constrained sensor nodes require techniques and protocols which are scalable, robust, and energy-efficient. The most efficient approach provided by clustering the nodes is hierarchy. The one node will send the data to another node and the another node will send to its neightbouring node. In smart cities, wireless sensor networks (WSNs) act as a type of core infrastructure that collects data from the city to implement smart services. Our thesis work included the region based clustering, cluster head selection and energy efficient communication using static base station and movable mobile nodes. Since it was earlier proposed that clustering improves the network lifetime. We modified the region based clustering by dividing the network area into n regions with cluster head chosen for each region and proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. We have used the mobile nodes for each section with controlled trajectory path as a reference to compare the performance of each of the clustering methods.


Author(s):  
Gaurav Kumar Nigam ◽  
Chetna Dabas

Background & Objective: Wireless sensor networks are made up of huge amount of less powered small sensor nodes that can audit the surroundings, collect meaningful data, and send it base station. Various energy management plans that pursue to lengthen the endurance of overall network has been proposed over the years, but energy conservation remains the major challenge as the sensor nodes have finite battery and low computational capabilities. Cluster based routing is the most fitting system to help for burden adjusting, adaptation to internal failure, and solid correspondence to draw out execution parameters of wireless sensor network. Low energy adaptive clustering hierarchy is an efficient clustering based hierarchical protocol that is used to enhance the lifetime of sensor nodes in wireless sensor network. It has some basic flaws that need to be overwhelmed in order to reduce the energy utilization and inflating the nodes lifetime. Methods : In this paper, an effective auxiliary cluster head selection is used to propose a new enhanced GC-LEACH algorithm in order to minimize the energy utilization and prolonged the lifespan of wireless sensor network. Results & Conclusion: Simulation is performed in NS-2 and the outcomes show that the GC-LEACH outperforms conventional LEACH and its existing versions in the context of frequent cluster head rotation in various rounds, number of data packets collected at base station, as well as reduces the energy consumption 14% - 19% and prolongs the system lifetime 8% - 15%.


2014 ◽  
Vol 626 ◽  
pp. 20-25
Author(s):  
K. Kalaiselvi ◽  
G.R. Suresh

In wireless sensor networks Energy-efficient routing is an important issue due to the limited battery power within the network, Energy consumption is one of the important performance factors. Specifically for the election of cluster head selection and distance between the cluster head node and base station. The main objective of this proposed system is to reduce the energy consumption and prolong the network lifetime. This paper introduces a new clustering algorithm for energy efficient routing based on a cluster head selection


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