Energy-Balanced Routing for Maximizing Network Lifetime in WirelessHART

Zhang, Sheng; Yan, Ao; Ma, Tingfeng

doi:10.1155/2013/173185

Cited by 18 publications

(14 citation statements)

References 26 publications

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“…Energy depletion at regular intervals despite of low connectivity is one the major issues faced by the sensor networks. Zhang et al [18] developed a new algorithm that is capable of balancing the energy in the network. The algorithm developed by the authors uses a link cost function formed by a combination of various parameters such as residual energy and load factors to select the optimal route between the nodes.…”

Section: Related Workmentioning

confidence: 99%

“…set Flag = 0 (3) while (transmission != end) do (4) markthesource(∈ ) (5) broadcast "Hello" ← (6) = segment of current source (∈ ) (7) while (next hop found != true) do (8) sort nodes in order of their attraction (9) select upper node and check for its connections (10) if (connections available == true) then (11) c o n t i n u e (12) else (13) select next optimal node (14) end if (15) check for satisfaction of (9) and (15) (16) if (satisifaction == true) then (17) select node as next hop (18) F l a g=0 (19) else (20) F l a g=1 (21) end if (22) UAVs coordination, and UAV to UAV coordination, as shown in Algorithms 1, 2, and 3, respectively. Algorithm 1 is used in case of sensors to sensors routing.…”

Section: Attractiveness Using Fire Fly Optimizationmentioning

confidence: 99%

“…(1) Input: , (2) = number of UAVs per segment, such that = × (3) while (transmission != end) do (4) if ( == 1) then (5) = select the UAV (6) fi n dl oc a ti o nf o r th UAV 7if (base station is within the range of th UAV) then (8) transmit() (9) exit(0) (10) else (11) broadcast message for new attraction value (12) sort and select the UAV with highest attraction value (13) repeat check from step (5) onwards (14) end if (15) else (16) mark the distance and attraction vale (17) if (count(distance and attraction vale) > 1) then (18) select the node which has not be used earlier (19) else (20) transmit() (21) exit(0) (22) end if (23) end if (24) end while Algorithm 3: Data dissemination: UAV to UAV. data towards the base station.…”

Section: Routing Loop Problemmentioning

confidence: 99%

“…(1) Input: current routing state (2) while (transmission != end) do (3) checkfornexthop (4) if (next hop == false) then (5) check for current attraction value (6) if (Conditions (9) and (15)) == true then (7) perform re-announcements and re-route (8) else (9) check for next node which is not selected earlier (10) mark the node and check for degree of connectivity (11) if (slots available == true) then (12) connect and proceed (13) exit(0) (14) else (15) select node with next in the order of attraction (16) reduce the number of outgoing and incoming connections (17) c h e c kf o rs t e p s( 5)-(11) (18) end if (19) end if (20) end if (21) end while Algorithm 4: Route rehabilitation and maintenance. A network with better lifetime operates for longer duration.…”

Section: Performance Evaluationmentioning

confidence: 99%

See 3 more Smart Citations

Energy Efficient Data Dissemination in Multi-UAV Coordinated Wireless Sensor Networks

Sharma

You

Kumar

2016

Mobile Information Systems

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With the requirement of better connectivity and enhanced coverage, collaborative networks are gaining a lot of popularity these days. One of such collaborative networks is formed between the wireless sensor networks (WSNs) and the unmanned aerial vehicles (UAVs). WSNs comprise static nodes arranged in a flat grid topology which may be randomly deployed or by some particular distribution. With the sensors operating on batteries, WSNs face a crucial issue of energy depletion during network operations. Integration of WSNs with UAVs can provide a solution to this excessive utilization of energy resources. UAVs provide a maneuvering support by playing a pivotal role of a manager node in these networks. However, integration of these networks demands an improved approach for data dissemination for effective utilization of network resources. For this, we propose a new data dissemination approach, which utilizes the attraction properties of fire fly optimization algorithm to provide energy efficient relaying. The proposed approach provides continuous connectivity, better lifetime, and improved coverage in the UAV coordinated WSNs. The performance of the proposed model is presented in terms of significant gains attained for parameters, namely, throughput, coverage, mean hops, lifetime, and delays, in comparison with the EEGA, ERIDSR, and I-ERIDSR approaches.

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Section: Related Workmentioning

confidence: 99%

Section: Attractiveness Using Fire Fly Optimizationmentioning

confidence: 99%

Section: Routing Loop Problemmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

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Energy Efficient Data Dissemination in Multi-UAV Coordinated Wireless Sensor Networks

Sharma

You

Kumar

2016

Mobile Information Systems

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“…A joint routing algorithm for maximizing network lifetime (JRMNL) was proposed in [ 62 ]. It is based on the WirelessHART graph routing topology and defines a link cost function for choosing the best next hop node in order to achieve the objective of the maximum network lifetime.…”

Section: State-of-the-art For Wirelesshart Routing Schemesmentioning

confidence: 99%

Routing and Scheduling Algorithms for WirelessHARTNetworks: A Survey

Nobre

Silva

Guedes

2015

Sensors

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Wireless communication is a trend nowadays for the industrial environment. A number of different technologies have emerged as solutions satisfying strict industrial requirements (e.g., WirelessHART, ISA100.11a, WIA-PA). As the industrial environment presents a vast range of applications, adopting an adequate solution for each case is vital to obtain good performance of the system. In this context, the routing and scheduling schemes associated with these technologies have a direct impact on important features, like latency and energy consumption. This situation has led to the development of a vast number of routing and scheduling schemes. In the present paper, we focus on the WirelessHART technology, emphasizing its most important routing and scheduling aspects in order to guide both end users and the developers of new algorithms. Furthermore, we provide a detailed literature review of the newest routing and scheduling techniques for WirelessHART, discussing each of their features. These routing algorithms have been evaluated in terms of their objectives, metrics, the usage of the WirelessHART structures and validation method. In addition, the scheduling algorithms were also evaluated by metrics, validation, objectives and, in addition, by multiple superframe support, as well as by the redundancy method used. Moreover, this paper briefly presents some insights into the main WirelessHART simulation modules available, in order to provide viable test platforms for the routing and scheduling algorithms. Finally, some open issues in WirelessHART routing and scheduling algorithms are discussed.

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Reliable and Energy Efficient Routing Algorithm for WirelessHART

Zhang

Feng

et al. 2014

Algorithms and Architectures for Parallel Processing

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Energy-Balanced Routing for Maximizing Network Lifetime in WirelessHART

Cited by 18 publications

References 26 publications

Energy Efficient Data Dissemination in Multi-UAV Coordinated Wireless Sensor Networks

Energy Efficient Data Dissemination in Multi-UAV Coordinated Wireless Sensor Networks

Routing and Scheduling Algorithms for WirelessHARTNetworks: A Survey

Reliable and Energy Efficient Routing Algorithm for WirelessHART

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