scholarly journals PARAMETER ADAPTATION FOR ANT COLONY SYSTEM IN WIRELESS SENSOR NETWORK

Author(s):  
Husna Jamal Abdul Nasir ◽  
Ku Ruhana Ku-Mahamud ◽  
Eiji Kamioka

The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). Solving these problems is complicated as packets need to be submitted through sensor nodes which are spatially distributed and heterogeneous by nature. Without an effective packet routing algorithm, energy consumption will be increased while network lifetime will be reduced. Most researches are focused on optimizing the routing process by using predefined parameters within a certain range. However, this approach will not guarantee optimal performance. This paper presents the parameter adaptation values for ACS experimental set-up in validating its performance. Possible values of each parameter within a defined range were employed. Experiments were conducted to obtain the best value of each parameter to be used for throughput, energy consumption, and latency. Results of this study can be adopted to achieve optimal performance for the packet routing process.  

Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.


Author(s):  
Rajiv R Bhandari ◽  
K Rajasekhar

<p>In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer &amp; Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.</p>


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.


2015 ◽  
Vol 764-765 ◽  
pp. 838-842
Author(s):  
Young Long Chen ◽  
Yung Chi Chang ◽  
Yu Ling Zeng

Wireless sensor networks (WSNs) are a group of wireless sensor nodes, those sensor nodes with sensing and monitoring of environmental information. Energy consumption is an important topic; the node's power is limited. Therefore, we proposed an Opportunistic Large Array Concentric Geographic Routing Algorithm (OLACGRA) to reduce the node’s energy consumption and analysis the characteristic of energy model. The sink position of our proposed OLACGRA is at the center of concentric topology architecture. The source node wants to transmit data that it needs to calculate the distance between source node and sink node. If this distance bigger than threshold value, we use the multi-hop manner. Otherwise, source node transmits data to sink node directly. Simulation results show that our proposed algorithm can effectively reduce the node’s energy consumption.


2012 ◽  
Vol 263-266 ◽  
pp. 954-958
Author(s):  
Xiang Yang Liu ◽  
Da Wang ◽  
Jin Pan

The ant colony optimization algorithm is good at solving multidimensional optimization problem. The allocation of power resource of a node in wireless sensor networks should make the detection performance of the whole network maximum, which is complex due to the detection probability of the whole system cannot be expressed explicitly. Therefore, continuous ant colony system (CACS) is adopted to optimize the allocation of each node’s power between sensing and communications. The results show that it can lead to a good power allocation. At the same time, the scheme that all sensor nodes have identical power assignment can achieve nearly the same detection performance as compared that achieved by the best scheme searched by CACS. As a result, particu-larly for a large number of sensors, an identical power allocation scheme for each node can be employed to achieve nearly the best detection performance.


2013 ◽  
Vol 850-851 ◽  
pp. 689-692
Author(s):  
Li Fu Wang ◽  
Jian Ding ◽  
Zhi Kong

A wireless sensor network (WSN) consists of spatially distributed wireless sensor nodes. The node power constrains the development of WSN. Employing techniques of clustering can reduce energy consumption of wireless sensor nodes and prolong the network lifetime. Therefore, in the study a new clustering routing algorithm is presented. The clustering algorithm uses the double-layer sensor nodes to communicate. And in order to optimize power energy consumption for WSN node energy, PSO algorithm is employed to find cluster head in each layer. Simulation results show that the algorithm not only can equal power energy of node, but also can reduce consumption in the long distance data transmission.


2018 ◽  
Vol 8 (4) ◽  
pp. 3177-3183 ◽  
Author(s):  
S. D. Chavan ◽  
A. V. Kulkarni

The main challenge of a wireless sensor network (WSN) in disaster situations is to discover efficient routing, to improve quality of service (QoS) and to reduce energy consumption. Location awareness of nodes is also useful or even necessary. Without knowing the position of sensor nodes, collected data is insignificant. Ant colony optimization (ACO) is a unique form of optimization method, which is highly suitable for adaptive routing and guaranteed packet delivery. The primary drawbacks of ACO are data flooding, huge overhead of control messages and long convergence time. These drawbacks are overcome by considering location information of sensor nodes. An event-based clustering localized energy efficient ant colony optimization (EBC_LEE-ACO) algorithm is proposed to enhance the performance of WSN. The main focus of the proposed algorithm is to improve QoS and minimize the network energy consumption by cluster formation and selecting the optimal path based on the biological inspired routing-ACO and location information of nodes. In clustering, data is aggregated and sent to the sink (base station) through cluster head (CH) which reduces overheads. EBC_LEE-ACO is a scalable and energy efficient reactive routing algorithm which improves QoS, lifetime and minimizes energy consummation of WSN as compared to other routing algorithms like AODV, ACO, ACO using RSSI. The proposed algorithm reduces energy consumption by approximately 7%, in addition to improvement in throughput, packet delivery ratio and increase in packet drop which has been observed in comparison with other algorithms, i.e. autonomous localization based eligible energetic Path_with_Ant Colony optimization (ALEEP with ACO) of the network. Use of IEEE 802.11 standard in proposed work increased packet drop.


Wireless Sensor Network (WSN) is a huge collection of sensor nodes deployed without any predetermined infrastructure. They are powered by batteries and energy consumption is one of the major issues in WSN. Hence to prolong the lifetime of the networks, it is important to design the energy efficient optimized routing algorithm. In this paper, two hop forwarding scheme in AODV and Fuzzy Logic is proposed to find an optimal routing protocol and intermediate node acknowledgement is deducted by the use of Fuzzy rules. The parameters such as remaining energy, data packet transmission, packet received acknowledgement and number of rounds is given as input to the fuzzy system which gives an optimized routing decision. The efficacy of the proposed algorithm is evaluated using NS2 and compared with Fuzzy-based Energy-Aware Routing Mechanism (FEARM). The simulation results shows that the Fuzzy based AODV routing algorithm reduces the energy consumption, minimizes the routing response packets and improves the network life time compared to other similar routing protocols.


Sign in / Sign up

Export Citation Format

Share Document