scholarly journals Architecture of an MAS-Based Intelligent Communication in a WSN

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mostefa Bendjima ◽  
Mohammed Feham

Wireless sensor networks (WSNs) are designed to collect information across a large number of sensor nodes with limited batteries. Therefore, it is important to minimize energy consumption of each node, so as to extend the lifetime of the network. This paper proposes the use of an intelligent WSN communication architecture based on a multiagent system (MAS), to ensure optimal data collection. MAS refers to a group of agents that interact and cooperate to achieve a specific goal. To ensure this objective, we propose the integration of a migrating agent into each node to process data and enhance cooperation between neighboring nodes, while mobile agents (MAs) can be used to reduce data transfer between the nodes and send them to the base station (Sink). The collaboration of these agents generates a simple message that summarizes important information to be transmitted by an MA. To reduce the size of MAs, nodes in the network sectors are grouped in such way that, for each MA, an optimal itinerary is established, using a minimum amount of energy with efficient data aggregation within a minimum time. Successive simulations in large-scale sensor networks show the good performance of our proposal in terms of energy consumption and packet delivery rate.

Author(s):  
Mostefa Bendjima ◽  
Mohammed Feham

Wireless Sensor Networks (WSN) is designed to collect information across a large number of limited battery sensor nodes. Therefore, it is important to minimize the energy consumption of each node, which leads to the extension of the network life. Our goal is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent has been migrated to each node in order to process the information and to cooperate with these neighboring nodes while Mobile Agents (MA) can be used to reduce information between nodes and send those to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the Multi Agent System (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the nodes of the network have been grouped into sector. As for each MA, we have established an optimal itinerary, consuming a minimum amount of energy with the data aggregation efficiency in a minimum time. Successive simulations in large scale wireless sensor networks through the SINALGO simulator show the performance of our proposal, in terms of energy consumption and package delivery rate.


2018 ◽  
Vol 10 (9) ◽  
pp. 91 ◽  
Author(s):  
Mostefa Bendjima ◽  
Mohammed Feham

Wireless sensor networks (WSN) are designed to collect information by means of a large number of energy-limited battery sensor nodes. Therefore, it is important to minimize the energy consumed by each sensor, in order to extend the network life. The goal of this work is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent is sent to each sensor in order to process the information and to cooperate with neighboring sensors while mobile agents (MA) can be used to reduce information shared between source nodes (SN) and send them to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the multi-agent system (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the sensors of the network have been grouped into sectors. For each MA, we have established an optimal itinerary, consuming a minimum amount of energy with data aggregation efficiency in a minimum time. Successive simulations in large-scale wireless sensor networks through the SINALGO (published under a BSD license) simulator show the performance of the proposed method, in terms of energy consumption and package delivery rate.


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).


2021 ◽  
Author(s):  
Jenice Prabu A ◽  
Hevin Rajesh D

Abstract In Wireless sensor network, the major issues are security and energy consumption. There may be several numbers of malicious nodes present in sensor networks. Several techniques have been proposed by the researchers to identify these malicious nodes. WSNs contain many sensor nodes that sense their environment and also transmit their data via multi-hop communication schemes to the base station. These sensor nodes provides power supply using battery and the energy consumption of these batteries must be low. Securing the data is to avoid attacks on these nodes and data communication. The aggregation of data helps to minimize the amount of messages transmitted within the network and thus reduces overall network energy consumption. Moreover, the base station may distinguish the encrypted and aggregated data based on the encryption keys during the decryption of the aggregated data. In this paper, two aspects of the problem is concerned, we investigate the efficiency of data aggregation: first, how to develop cluster-based routing algorithms to achieve the lowest energy consumption for aggregating data, and second, security issues in wsn. By using Network simulator2 (NS2) this scheme is simulated. In the proposed scheme, energy consumption, packet delivery ratio and throughput is analyzed. The proposed clustering, routing, and protection protocol based on the MCSDA algorithm shows significant improvement over the state-of - the-art protocol.


Author(s):  
SHYAM D. BAWANKAR ◽  
SONAL B. BHOPLE ◽  
VISHAL D. JAISWAL

Large-scale networks of wireless sensors are becoming an active topic of research.. We review the key elements of the emergent technology of “Smart Dust” and outline the research challenges they present to the mobile networking and systems community, which must provide coherent connectivity to large numbers of mobile network nodes co-located within a small volume. Smart Dust sensor networks – consisting of cubic millimeter scale sensor nodes capable of limited computation, sensing, and passive optical communication with a base station – are envisioned to fulfil complex large scale monitoring tasks in a wide variety of application areas. RFID technology can realize “smart-dust” applications for the sensor network community. RFID sensor networks (RSNs), which consist of RFID readers and RFID sensor nodes (WISPs), extend RFID to include sensing and bring the advantages of small, inexpensive and long-lived RFID tags to wireless sensor networks. In many potential Smart Dust applications such as object detection and tracking, fine-grained node localization plays a key role.


2018 ◽  
Vol 7 (4.15) ◽  
pp. 178
Author(s):  
Komal Memon ◽  
Nafeesa Bohra ◽  
Faisal K Shaikh

There is a great demand of an Underwater Sensor Networks (UWSNs) in applications of water monitoring and offshore exploration. In such applications, network comprises of multiple sensor nodes which are deployed at different locations and depths of water. Sensor nodes perform collective tasks such as data collection and data transmission to other nodes or Base Station (BS). The bottom nodes are located at depth of water, and are not able to communicate directly with the surface level nodes, these nodes require multi-hop communication with appropriate routing protocol. Therefore, an energy efficient routing protocols are used for such scenarios, which is necessary as well as challenging task. As sensors are battery operated devices, which are really problematic to recharge or replace. The error and propagation path delays are high in acoustic channels therefore underwater communication is much effected. Realizing the circumstances, more attention has been given to compare energy efficient routing protocols which comparatively consume low energy and achieve high throughput. This paper, comprises of analysis and comparison of existing UWSN based efficient energy routing protocols. Based upon the analysis and comparison, VBF and DBR have been proposed that fulfill the requirements. The analysis is done on NS-2 and for comparison, the performance metrics which are evaluated are: Packet delivery Ratio (PDR), energy consumption, throughput and average End to End (E2E) delay. The results show that VBF protocol consume very large amount of energy as compared to DBR protocol. Whereas DBR protocol have characteristics like low energy consumption, minimum delay high PDR and high throughput than VBF protocol.  


The wireless sensor networks consist of numerous small nodes which are also called as energy resource-constrained sensor nodes. The communication of these nodes can be done in a various way. There is also the processing of signal tasks which is done through the various computational resources provided by the networks. The energy of the sensor nodes gets consumed when transmit the data or receive data from the network. To reduce energy consumption of the network various techniques has been proposed which are known as clustering techniques. In the proposed work the mobile sink is deployed in the network which reduces overhead in the network. Experimental results shows that the proposed work outperforms the existing one in terms of reduced energy consumption of the network, increased throughput of the network, reduced delay in the network.


Author(s):  
Khushboo Jain ◽  
Anoop Kumar

Continuous-monitoring applications in sensor network applications require periodic data transmissions to the base-station (BS), which may lead to unnecessary energy depletion. The energy-efficient data aggregation solutions in sensor networks have evolved as one of the favorable fields for such applications. Former research works have recommended many spatial-temporal designs and prototypes for successfully minimizing the data-gathering overheads, but these are constrained to their relevance. This work has proposed a data aggregation technique for homogeneous application set-ups in sensor networks. For this, the authors have employed two ways of model generation for reducing correlated spatial-temporal data in cluster-based sensor networks: one at the Sensor nodes (SNs) and the other at the Cluster heads (CHs). Building on this idea, the authors propose two types of data filtration, first at the SNs for determining temporal redundancies (TRs) in data readings by both relative deviation (RD) and adaptive frame method (AFM) and second at the CHs for determining spatial redundancies (SRs) by both RD and AFM.


Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4072
Author(s):  
Tanzila Saba ◽  
Khalid Haseeb ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Ayman Altameem ◽  
...  

In recent times, the field of wireless sensor networks (WSNs) has attained a growing popularity in observing the environment due to its dynamic factors. Sensor data are gathered and forwarded to the base station (BS) through a wireless transmission medium. The data from the BS is further distributed to end-users using the Internet for their post analysis and operations. However, all sensors except the BS have limited constraints in terms of memory, energy and computational resources that degrade the network performance concerning the network lifetime and trustworthy routing. Therefore, improving energy efficiency with reliable and secure transmissions is a valuable debate among researchers for critical applications based on low-powered sensor nodes. In addition, security plays a significant cause to achieve responsible communications among sensors due to their unfixed and variable infrastructures. Keeping in view the above-mentioned issues, this paper presents an energy-aware graph clustering and intelligent routing (EGCIR) using a supervised system for WSNs to balance the energy consumption and load distribution. Moreover, a secure and efficient key distribution in a hierarchy-based mechanism is adopted by the proposed solution to improve the network efficacy in terms of routes and links integrity. The experimental results demonstrated that the EGCIR protocol enhances the network throughput by an average of 14%, packet drop ratio by an average of 50%, energy consumption by an average of 13%, data latency by an average of 30.2% and data breaches by an average of 37.5% than other state-of-the-art protocols.


2013 ◽  
Vol 5 (3) ◽  
pp. 34-54
Author(s):  
Shiow-Fen Hwang ◽  
Han-Huei Lin ◽  
Chyi-Ren Dow

In wireless sensor networks, due to limited energy, how to disseminate the event data in an energy-efficient way to allow sinks quickly querying and receiving the needed event data is a practical and important issue. Many studies about data dissemination have been proposed. However, most of them are not energy-efficient, especially in large-scale networks. Hence, in this paper the authors proposed an energy-efficient data dissemination scheme in large-scale wireless sensor networks. First, the authors design a data storage method which disseminates only a few amount event data by dividing the network into regions and levels, and thus reducing the energy consumption. Then, the authors develop an efficient sink query forwarding strategy by probability analysis so that a sink can query events easily according to its location to reduce the delay time of querying event data, as well as energy consumption. In addition, a simple and efficient maintenance mechanism is also provided. The simulation results show that the proposed scheme outperforms TTDD and LBDD in terms of the energy consumption and control overhead.


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