scholarly journals Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ranganathan Mohanasundaram ◽  
Pappampalayam Sanmugam Periasamy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Data Storage ◽  
Research Work ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Concern ◽  
Optimization Approach ◽  
Hybrid Particle Swarm Optimization

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

scholarly journals An efficient approach for secured communication in wireless sensor networks

2020 ◽  
Vol 10 (2) ◽  
pp. 1641
Author(s):  
Jyothi R. ◽  
Nagaraj G. Cholli
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Key Management ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Concern ◽  
Limited Bandwidth ◽  
New Type ◽  
Symmetric Key ◽  
Secured Communication

Wireless sensor network (WSN) have limited bandwidth, low computational functions, energy constraints. Inspite of these constraints, WSN is useful where communication happens without infrastructure support. The main concern of WSN is the security as the sensor nodes may be attacked and information may be hacked. Security of WSN should have the capability to ensure that the message received was sent by the particular sent node and not modified during transmission. WSN applications require lightweight and strong authentication mechanisms for obtaining data from unprivileged users. In wireless sensor networks, authentication is the effective method to stop unauthorized and undisrupted communication service. In order to strengthen the authenticated communication, several researchers have developed mechanisms. Some of the techniques work with identifying the attacked node or detecting injected bogus message in the network. Encryption and decryption are the popular methods of providing the security. These are based on either public-key or symmetric-key cryptosystems Many of the existing solutions have limitations in communication and computational expertise. Also, the existing mechanisms lack in providing strength and scalability of the network. In order address these issues; a polynomial based method was introduced in recent days. Key distribution is a significant aspect in key management in WSNs. The simplest method of distribution of key is by hand which was used in the days of couriers. Now a days, most distribution of keys is done automatically. The automatic distribution of keys is essential and convenient in networks that require two parties to transmit their security keys in the same communication medium. In this work, a new type of key exchange mechanism is proposed. The proposed method for authentication among sensor nodes proves to be promising as per the simulation results. The nodes which are unknown to each other setup a private however arbitrary key for the symmetric key cryptosystem.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

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.

scholarly journals Evaluation of Energy Consumption using Receiver–Centric MAC Protocol in Wireless Sensor Networks

2018 ◽  
Vol 8 (1) ◽  
pp. 87
Author(s):  
Ananda Kumar K S ◽  
Balakrishna R
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mac Protocol ◽  
Research Work ◽  
Data Communication ◽  
Reliable Data ◽  
Sensor Nodes ◽  
Wireless Sensor

At present day’s wireless sensor networks, obtain a lot consideration to researchers. Maximum number of sensor nodes are scattered that can communicate with all others. Reliable data communication and energy consumption are the mainly significant parameters that are required in wireless sensor networks. Many of MAC protocols have been planned to improve the efficiency more by enhancing the throughput and energy consumption. The majority of the presented medium access control protocols to only make available, reliable data delivery or energy efficiency does not offer together at the same time. In this research work the author proposes a novel approach based on Receiver Centric-MAC is implemented using NS2 simulator. Here, the author focuses on the following parametric measures like - energy consumption, reliability and bandwidth. RC-MAC provides high bandwidth without decreasing energy efficiency. The results show that 0.12% of less energy consumption, reliability improved by 20.86% and bandwidth increased by 27.32% of RC-MAC compared with MAC IEEE 802.11.

scholarly journals SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network

2021 ◽  
Vol 1 (2) ◽  
pp. 16-20
Author(s):  
Mohammed M. Ahmed*
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Minimum Spanning Tree ◽  
Fitness Function ◽  
Shortest Paths ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimization Approach ◽  
Sink Node ◽  
Swarm Optimization

In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node location we create transmission paths between the sink node and rest of nodes using Prim's minimum spanning tree to choose shortest paths. Accordingly, for fitness function that used to decrease energy consumption for a network. Simulation results clarify that our proposed algorithm that solves localization of sink node presents the best results for prolonging the network's lifetime compared to Cat Swarm Optimization algorithm (CSA) and Particle Swarm Optimization (PSO).

An Ant Colony Optimization Approach to Power Allocation in Wireless Sensor Networks

2012 ◽  
Vol 263-266 ◽  
pp. 954-958
Author(s):  
Xiang Yang Liu ◽  
Da Wang ◽  
Jin Pan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Power Allocation ◽  
Detection Performance ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ant Colony System ◽  
Optimization Approach

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.

scholarly journals Sequential Monte Carlo Localization Methods in Mobile Wireless Sensor Networks: A Review

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Ammar M. A. Abu Znaid ◽  
Mohd. Yamani Idna Idris ◽  
Ainuddin Wahid Abdul Wahab ◽  
Liana Khamis Qabajeh ◽  
Omar Adil Mahdi
Keyword(s):  
Wireless Sensor Networks ◽  
Monte Carlo ◽  
Sensor Networks ◽  
Sequential Monte Carlo ◽  
Research Work ◽  
Computational Cost ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Future Research ◽  
Advantages And Disadvantages

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages and disadvantages. The similarities and differences of each scheme are investigated on the basis of significant parameters, namely, localization accuracy, computational cost, communication cost, and number of samples. We discuss the challenges and direction of the future research work for each parameter.

Doubly Cognitive Architecture Based Cognitive Wireless Sensor Networks

2011 ◽  
Vol 1 (2) ◽  
pp. 30-35 ◽  
Author(s):  
Sumit Kumar ◽  
Deepti Singhal ◽  
Garimella Rama Murthy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Pattern Analysis ◽  
Research Work ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Research Centre ◽  
Periodic Pattern ◽  
Ongoing Research ◽  
Cognitive Wireless Sensor Networks

Scarcity of spectrum is increasing not only in cellular communication but also in wireless sensor networks. Adding cognition to the existing wireless sensor network (WSN) infrastructure has helped. As sensor nodes in WSN are limited with constraints like power, efforts are required to increase the lifetime and other performance measures of the network. In this article, the authors propose Doubly Cognitive WSN, which works by progressively allocating the sensing resources only to the most promising areas of the spectrum and is based on pattern analysis and learning. As the load of sensing resource is reduced significantly, this approach saves the energy of the nodes and reduces the sensing time dramatically. The proposed method can be enhanced by periodic pattern analysis to review the strategy of sensing. Finally the ongoing research work and contribution on cognitive wireless sensor networks in Communication Research Centre (IIIT-H) is discussed.

scholarly journals Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Felicia Engmann ◽  
Ferdinand Apietu Katsriku ◽  
Jamal-Deen Abdulai ◽  
Kofi Sarpong Adu-Manu ◽  
Frank Kataka Banaseka
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Management ◽  
Research Work ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Future Research ◽  
Primary Means ◽  
Management Schemes ◽  
Management Techniques

There has been an increase in research interest in wireless sensor networks (WSNs) as a result of the potential for their widespread use in many different areas like home automation, security, environmental monitoring, and many more. Despite the successes gained, the widespread adoption of WSNs particularly in remote and inaccessible places where their use is most beneficial is hampered by the major challenge of limited energy, being in most instances battery powered. To prolong the lifetime for these energy hungry sensor nodes, energy management schemes have been proposed in the literature to keep the sensor nodes alive making the network more operational and efficient. Currently, emphasis has been placed on energy harvesting, energy transfer, and energy conservation methods as the primary means of maintaining the network lifetime. These energy management techniques are designed to balance the energy in the overall network. The current review presents the state of the art in the energy management schemes, the remaining challenges, and the open issues for future research work.

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