Efficient Zone-based Routing Protocol of Sensor Network in agriculture monitoring systems

Karim, Lutful; Salti, Tarek El

doi:10.1109/iccitechnol.2011.5762672

Cited by 14 publications

(16 citation statements)

References 9 publications

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“…We use randomly connected Unit Disk Graphs (UDGs) on an area of 100 meters × 100 meters as a network simulation model. We set the number of zones and nodes to 6 and 36, place BS outside and center of all zones at the coordinates (50,115) and (50,53), respectively, and vary the sensor's data collection time between 3 and 12.…”

Section: Experiments Resultsmentioning

confidence: 99%

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An integrated framework for wireless sensor network management

Karim

Mahmoud

Khan

2012

Wirel. Commun. Mob. Comput.

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Wireless Sensor Networks (WSNs) have significant potential in many application domains, and are poised for growth in many markets ranging from agriculture and animal welfare to home and office automation. Although sensor network deployments have only begun to appear, the industry still awaits the maturing of this technology to realize its full benefits. The main constraints to large scale commercial adoption of sensor networks are the lack of available network management and control tools for determining the degree of data aggregation prior to transforming it into useful information, localizing the sensors accurately so that timely emergency actions can be taken at exact location, and scheduling data packets so that data are sent based on their priority and fairness. Moreover, due to the limited communication range of sensors, a large geographical area cannot be covered, which limits sensors application domain. Thus, we investigate a scalable and flexible WSN architecture that relies on multi-modal nodes equipped with IEEE 802.15.4 and IEEE 802.11 in order to use a Wi-Fi overlay as a seamless gateway to the Internet through WiMAX networks. We focus on network management approaches such as sensors localization, data scheduling, routing, and data aggregation for the WSN plane of this large scale multimodal network architecture and find that most existing approaches are not scalable, energy efficient, and fault tolerant. Thus, we introduce an efficient approach for each of localization, data scheduling, routing, and data aggregation; and compare the performance of proposed approaches with existing ones in terms of network energy consumptions, localization error, end-to-end data transmission delay and packet delivery ratio. Simulation results, theoretical and statistical analysis show that each of these approaches outperforms the existing approaches. To the best of our knowledge, no integrated network management solution comprising efficient localization, data scheduling, routing, and data aggregation approaches exists in the literature for a large scale WSN. Hence, we efficiently integrate all network management components so that it can be used as a single network management solution for a large scale WSN, perform experimentations to evaluate the performance of the proposed framework, and validate the results through statistical analysis. Experimental results show that our proposed framework outperforms existing approaches in terms of localization energy consumptions, localization accuracy, network energy consumptions and end-to-end data transmission delay.

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Section: Experiments Resultsmentioning

confidence: 99%

“…We run the same experiment by placing BS outside, and center of all zones at coordinates (50,101) and (50,51). is very close to each other and overlaps at some data collection time.…”

Section: Experiments Resultsmentioning

confidence: 99%

An integrated framework for wireless sensor network management

Karim

Mahmoud

Khan

2012

Wirel. Commun. Mob. Comput.

Self Cite

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“…The work done by Karimi E. also, Akbari B. [33] also proposes a proposed queue programming algorithmic system for Wireless transmission detecting component Nodes. amid this programming topic, cradle zone of middle of the road nodes is part into four lines to convey 3 varying sorts of video casings and one consistent learning outlines.…”

Section: Number Of Queuementioning

confidence: 99%

Packet Scheduling for Wireless Sensor Network

Reddy¹

2014

IJWD

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“…Sensor nodes having different queues in which all packets are placed. Figure3 [12] shows the working of the Dynamic multilevel priority scheme. This scheme assumes that the nodes are organized hierarchically like a tree.…”

Section: Dmp Schemementioning

confidence: 99%

“…2 scheduling of tasks in diff. queues [12] In this scheme we are considering there are maximum three level of queues that means for a queue there are three levels. The pr1 is for priority one.…”

Section: Dmp Schemementioning

confidence: 99%

Hybrid Model for Packet Scheduling in Wireless Sensor Network

Praddyumna¹

2018

IJRASET

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The Wireless Sensor Network (WSN) is the wide area as compared to the others in networking domain. So when we deal with it, there are many things on which we have to concentrate. One of the most important among them is "Scheduling of the packets through the Network". It is having so much importance for the energy consumption and end to end data transmission delay. So the focused area should be the end to end data transmission delay. There are lot many Schemes used before like First Come First Serve also called as FCFS, Earliest Deadline First that is EDF and others to achieve the less end to end delay while sending the packet from one end to another. Some Schemes like Pre-emptive priority, Non Pre-emptive priority also used. But these Schemes are having certain disadvantages. These Scheduling algorithms incurred high processing overhead and it is not recommended. These Schemes also suffers from the large data transmission delay. In this paper, we are improving the Scheme that is used before named as "Dynamic Multilevel Priority Packet Scheduling Scheme". In the DMP scheme, except the nodes that are present at the last level of the hierarchy in the topology have the three levels of the priority queues. The three levels are priority one, priority two, and priority three. In this paper we are mostly focused on avoiding the drop of the packets. So we are avoiding this by using taking other queue for non real time packets so that they don't have to wait long time because of continuous arrival of real time packets. We are also reducing the hop count of the packet while sending to neighbour nodes. Keywords: Multi-hop, Hoping, Non-real time packets, Packet Scheduling, Real time packets, Wireless Sensor Network I. INTRODUCTIONThere are different big design issues in the wireless sensor network such as the data aggregation, routing protocols but among them the most important is Scheduling of the different types of packets through the network. Because of the delivery of the packet is notified through this. So here we are focusing on the packet scheduling with different schemes and priorities for different packets. So there are mainly two types of packets such as Real time packets and the non-real time packets. Real time packets are those which should be used as fast as they can and non-real time packets are those which are not that important as real time packets. These real time packets should have the highest priority. Most of the operating systems in the Wireless Sensor Networks uses First Come First Serve (FCFS) [1] scheme. This scheme processes the data packets as their arrival time. Means that whichever packet comes earlier that packet will process first. So here the drawback of the scheme is that the data packets which are at the back they will have higher processing overhead. Those packets will wait for longer time and it can be expire. So it requires more time to reach the destination. The packets should reach the destination in its given interval of time otherwise they will get expired. Other schemes whi...

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Efficient Zone-based Routing Protocol of Sensor Network in agriculture monitoring systems

Cited by 14 publications

References 9 publications

An integrated framework for wireless sensor network management

An integrated framework for wireless sensor network management

Packet Scheduling for Wireless Sensor Network

Hybrid Model for Packet Scheduling in Wireless Sensor Network

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