Data Flow in Wireless Sensor Network Protocol Stack by Using Bellman-Ford Routing Algorithm
01 Mar 2017-Bulletin of Electrical Engineering and Informatics (Universitas Ahmad Dahlan)-Vol. 6, Iss: 1, pp 81-87
TL;DR: This paper study and analysis Bellman-Ford routing algorithm and check the flow of data between these protocol layers and uses Qualnet 5.0.2 simulator tool for simulation purpose.
Abstract: Wireless sensor network consists various sensor nodes that are used to monitor any target area like forest fire detection by our army person and monitoring any industrial activity by industry manager. Wireless sensor networks have been deployed in several cities to monitor the concentration of dangerous gases for citizens. In wireless sensor network when sensor nodes communicate from each other then routing protocol are used for communication between protocol layers. Wireless sensor network protocol stack consist five layers such as Application layer, Transport layer, Network layer, MAC Layer, Physical layer. In this paper we study and analysis Bellman-Ford routing algorithm and check the flow of data between these protocol layers. For simulation purpose we are using Qualnet 5.0.2 simulator tool.
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TL;DR: An overview of WSN, the wireless sensor network constructed from sensor devices to send collected data to the base station for monitoring and analysis, is provided.
Abstract: Small devices that can sense and collect data from the surrounding environment have been produced with the rapid development of wireless technology and digital electronics. As a result, a wireless sensor network (WSN) was constructed from these sensor devices to send collected data to the base station for monitoring and analysis. This paper provides an overview of WSN, as well as its architecture and applications.
14 citations
TL;DR: Wake-up receiver used in WSN save power and prolong the lifetime of batteries and thus extending the operational lifetime of WSN.
Abstract: Wireless sensor network (WSN) consists of base stations and sensors nodes to monitor physical and environmental conditions. Power consumption is a challenge in WSN due to activities of nodes. High power consumption is required for the main transceiver in WSN to receive communication requests all the time. Hence, a low power wake-up receiver is needed to minimize the power consumption of WSN. In this work, a low power wake-up receiver using ultrasound data communication is designed. Wake-up receiver is used to detect wake-up signal to activate a device in WSN. Functional block modelling of the wake-up receiver is developed in Silterra CMOS 130nm process technology. The performance of the wake-up receiver has been analyzed and achieving low power consumption which is 22.45μW. A prototype to demonstrate a wireless sensor node with wake-up receiver has been developed incorporating both ultrasonic and RF for internal and external communication respectively. We achieve 99.97% of power saving for 10s operation in the experimental setup for the WSN with and without wake-up receiver. Wake-up receiver used in WSN save power and prolong the lifetime of batteries and thus extending the operational lifetime of WSN.
5 citations
Cites background from "Data Flow in Wireless Sensor Networ..."
...Power consumption is a main constraint in WSN as the operational lifetime of WSN is considered as a critical issue for deployment of the network [5-9]....
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TL;DR: Simulation results shows Cross layer based AntSenseNet protocol outperforms Ant Sense routing protocol and cross layer routing protocol in terms of throughput and packet delivery ratio.
Abstract: Wireless Multimedia Sensor Network (WMSN) is comprised of tiny, low cost multimedia devices such as video cameras and microphones. These networks can transfer scalar as well as multimedia data into real time as well as non-real time applications. However addition of such devices exposes additional challenges on both QoS assurance and energy efficiency for efficient use of resources. This paper presents cross layer based AntSenseNet protocol to meet various QoS requirements such as throughput, jitter, lifetime and packet delivery ratio in order to improve network lifetime. Cross layer routing protocol utilizes scheduling algorithm and AntSenseNet protocol builds hierarchical structure and able to use multipath routing protocol. Simulation results shows Cross layer based AntSenseNet protocol outperforms Ant Sense routing protocol and cross layer routing protocol in terms of throughput and packet delivery ratio.
4 citations
Cites background from "Data Flow in Wireless Sensor Networ..."
...Wireless sensor network consists of various sensor nodes that are used to monitor any target area like forest fire detection by our army person and monitoring any industrial activity by industry manager [4]....
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TL;DR: To improve the steadfast routing in Wireless Sensor Networks with little interfering and avoid packet collision, the entire node has the option of electing next Data Communication Node (DCN).
Abstract: This article objective is to improve the steadfast routing in Wireless Sensor Networks with little interfering and avoid packet collision. In the scheme, the entire node has the option of electing next Data Communication Node (DCN). The next data communication node is chosen depend on the intensity of link, remaining energy, and the node with distance towards the Base Station. Thus, the sender node transmits the information to the best DCN. Instantly, the DCN sends the acknowledgement (ACK) along with the number of packets received back to the node from which it obtains the data. The sender node assures the delivery of the transmitted packets by comparing the value of number of packets sent with the value obtained with the acknowledgement. If they are equivalent, it will send the verification identity to the DCN. If it is not equivalent, it will decide another node with highest link intensity. After that, the data chooses the DCN and repeat the process until the data reaches the Base Station.
2 citations
Cites background from "Data Flow in Wireless Sensor Networ..."
...moving around, it helps for army soldiers to fire detection in forests as well as for communication among them using algorithms for privacy connection in sensor nodes [8]....
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01 Jan 2020
TL;DR: It is concluded that although hybrid WSN-NGPON2 network has challenges, but also it provides the lots of numerous advance applications for smart world.
Abstract: The emerging wireless sensor network (WSN) is a wireless network of low-power, high-resolution nodes for sensing the environment. WSN, a future technology, has been deployed for numerous smart world applications such as smart agriculture, homes, cities, transportation, hospitals etc. But, the presence of limited bandwidth, small coverage and the limited energy sensor nodes retards the lifetime of the WSNs. Thus to remove all these shortcomings of sensor network at a high data rate over long reach distance, the passive optical network (PON) plays an important role for WSNs. Further, an attractive and energy-efficient next generation passive optical network stage 2 (NG-PON2) provides a higher data rate and better quality of services at a low cost. Furthermore, the hybrid wireless sensor network- next generation passive optical network stage 2 (WSN-NGPON2) is a future proof energy efficient optical network for a smart world. In this chapter, the hybrid WSN-NGPON2 network is studied and compared with other PON architectures like gigabit passive optical network (GPON), ethernet passive optical network (EPON), next generation passive optical network stage 1 (NG-PON1) etc. In addition of describing the key challenges of hybrid WSN-NGPON2 network, this chapter also presents the various applications in different smart fields. It is concluded that although hybrid WSN-NGPON2 network has challenges, but also it provides the lots of numerous advance applications for smart world.
2 citations
References
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TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.
17,936 citations
"Data Flow in Wireless Sensor Networ..." refers background in this paper
...Such constraints combined with a typical deployment of large number of sensor nodes, have posed many challenges to the design and management of sensor networks and necessitate energy-awareness at all layers of networking protocol stack [1-2]....
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04 Jan 2000
TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.
Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
12,497 citations
01 Jan 2000
TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have signicant impact on the overall energy dissipation of these networks. Based on our ndings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
11,412 citations
TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Abstract: Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
10,296 citations
"Data Flow in Wireless Sensor Networ..." refers background in this paper
...Wireless Sensor Network A wireless sensor network consists distributed autonomous sensors nodes that are used to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and to cooperatively pass their data to the base station [2-3]....
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TL;DR: A survey of state-of-the-art routing techniques in WSNs is presented and the design trade-offs between energy and communication overhead savings in every routing paradigm are studied.
Abstract: Wireless sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. In this article we present a survey of state-of-the-art routing techniques in WSNs. We first outline the design challenges for routing protocols in WSNs followed by a comprehensive survey of routing techniques. Overall, the routing techniques are classified into three categories based on the underlying network structure: flit, hierarchical, and location-based routing. Furthermore, these protocols can be classified into multipath-based, query-based, negotiation-based, QoS-based, and coherent-based depending on the protocol operation. We study the design trade-offs between energy and communication overhead savings in every routing paradigm. We also highlight the advantages and performance issues of each routing technique. The article concludes with possible future research areas.
4,701 citations
"Data Flow in Wireless Sensor Networ..." refers methods in this paper
...In this paper we analyze Bellman-Ford routing algorithm and check the data flow between protocol layers [9]....
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