An Energy and Fault Aware Mechanism of Wireless Sensor Networks Using Multiple Mobile Agents

2020 ◽  
Vol 11 (3) ◽  
pp. 22-41
Author(s):  
Rajendra Kumar Dwivedi ◽  
Rakesh Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Fault Tolerant ◽  
Wireless Sensor ◽  
Task Completion ◽  
Agent Based ◽  
Multi Agent ◽  
Power Capability ◽  
The Impact

Wireless sensor networks find several applications in hard-to-reach areas. As sensors have limited battery power, many energy aware protocols based on negotiation, clustering, and agents have been developed to increase lifetime of the network. This article finds limitation with some multi-agent-based protocols as they place the sink node at the centre of the monitoring region which is quite difficult in hard-to-reach areas. Therefore, a multi-agent-based energy and fault-aware protocol for hard-to-reach territories (MAHT) is proposed which uses technique of impact factor to identify the high power capability of the central node and dynamic itinerary planning to make the protocol fault tolerant. Its agent migration technique results in improvement ofn energy efficiency, task completion time and network lifetime. MAHT is simulated using Castalia simulator and the impact of payload size, network size, node failures, etc., on various performance metrics is analysed. The proposed protocol found outperforming over the existing ones.

Multi-Agent-Based Acoustic Sensor Node Deployment in Underwater Acoustic Wireless Sensor Networks

2020 ◽  
Vol 13 (4) ◽  
pp. 136-155
Author(s):  
Basaprabhu S. Halakarnimath ◽  
Ashok V. Sutagundar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Propagation Loss ◽  
Wireless Sensor ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Agent Based ◽  
Node Deployment ◽  
Multi Agent

The deployment of acoustic sensor nodes in 3-D underwater acoustic wireless sensor networks (UAWSN) is a difficult task due to various aquatic conditions and physical obstacles. This work proposes multi-agent-based acoustic sensor node deployment (MASD) to deploy the acoustic nodes at ideal positions to enhance coverage and seamless connectivity. The proposed scheme works is threefold: 1) AUV initiates random walk in the network to gather the information and prospective common reference points; 2) the base station gets this information through surface buoys and computes the routing path, feasible locations for deploying new nodes; and 3) AUV collects this information and follows the path to deploy nodes with the help of agents. The multi-agent-enabled deployment framework (MADF) is proposed to support the deployment process at each level of the proposed MASD scheme. The performance of propagation loss, coverage, and overhead tradeoffs are analyzed to validate the proposed scheme. Mobility issues can be further re-investigated in shallow water as a future direction to the MASD scheme.

A survey on agent learning architecture that adopts internet of things and wireless sensor networks

2020 ◽  
pp. 2030002
Author(s):  
T. Joshva Devadas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Swot Analysis ◽  
Wireless Sensor ◽  
Agent Architectures ◽  
Agent Based ◽  
Intelligent Software ◽  
Agent Learning ◽  
Multi Agent

Trustworthy and reliable applications built using intelligent software agents aim to provide improved performance using its characteristics. Agents introduced in various architectures represent its functionality as functional elements of the architecture and shows the interaction between other components present in the architecture. The Internet of things (IoT) reveals as a frequent technology that allows accessing the physical objects present in the world. IoT systems utilize wireless sensor network to transmit and receive data by establishing communication. Wireless Sensor Networks transmits digital signals to the cyber-world for analyzing and processing the information into useful data by either formulating or communicating with the intelligent and innovative system. While talking about IoT and WSN, agents introduced in such environments assist in making decisions quickly by perceiving the input from the environment. The number of agents needed for an application depends upon the complexity of the problem. Multi-Agent architectures discussed in the article describe their association, roles, functionality and interaction. This paper gives a detailed survey of various agent/multi-agent learning architectures introduced over IoT and WSN. Moreover, this survey with the performance and the SWOT analysis on the Agent-based learning architecture helps the reader and paves a way to pursue research on Agent-based architectural deployment over IoT and WSN paradigms.

scholarly journals Bicriteria Optimization in Wireless Sensor Networks: Link Scheduling and Energy Consumption

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jian Chen ◽  
Jie Jia ◽  
Enliang Dai ◽  
Yingyou Wen ◽  
Dazhe Zhao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Data Communication ◽  
Wireless Sensor ◽  
Link Scheduling ◽  
Nsga Ii ◽  
Routing Tree ◽  
The Impact

Link scheduling is important for reliable data communication in wireless sensor networks. Previous works mainly focus on how to find the minimum scheduling length but ignore the impact of energy consumption. In this paper, we integrate them together and solve them by multiobjective genetic algorithms. As a contribution, by jointly modeling the route selection and interference-free link scheduling problem, we give a systematical analysis on the relationship between link scheduling and energy consumption. Considering the specific many-to-one communication nature of WSNs, we propose a novel link scheduling scheme based on NSGA-II (Non-dominated Sorting Genetic Algorithm II). Our approach aims to search the optimal routing tree which satisfies the minimum scheduling length and energy consumption for wireless sensor networks. To achieve this goal, the solution representation based on the routing tree, the genetic operations including tree based recombination and mutation, and the fitness evaluation based on heuristic link scheduling algorithm are well designed. Extensive simulations demonstrate that our algorithm can quickly converge to the Pareto optimal solution between the two performance metrics.

scholarly journals Simulating and Analysing the Impact of Routing Protocols on Different Parameters of WSNs

2015 ◽  
Vol 6 (1) ◽  
pp. 27-37
Author(s):  
Anish Soni ◽  
Rajneesh Randhawa
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Performance Metrics ◽  
Data Dissemination ◽  
Wireless Sensor ◽  
Stress Sensors ◽  
The Impact

Energy efficiency of Wireless Sensor Networks has become an essential requirement and is the main issue for researchers. Various routing, data dissemination and energy efficient protocols have been designed for Wireless Sensor Networks where energy issue has been given more stress. Sensors in wireless sensor networks work on battery and have limited energy. Hence, network has limited lifetime. Routing protocol plays a major role in deciding for how much time a network will survive. All routing algorithms tend to increase the lifetime of WSN while maintaining factors like successful and real-time delivery of a message. This paper aims towards studying different categories of routing protocols and finally four hierarchical routing protocols LEACH, EHRP, SEP and FAIR have been simulated. The performance of each routing protocol has been measured on some performance metrics like network lifetime, packets transferred to BS, number of dead nodes etc and finally concluded that how a routing protocol can impact the network lifetime.

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

Sign in / Sign up

Export Citation Format

Share Document