SAERP: An energy efficiency Real-time Routing protocol in WSNs

Yaeghoobi, Kaebeh; Tyagi, S. S.; Soni, M. K.; E., Omid Mahdi Ebadati

doi:10.1109/icroit.2014.6798323

Cited by 8 publications

(3 citation statements)

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“…To conserve the energy of the CM and to balance the cluster over energy failure, the nodes are frequently transited over the active and idle state. Transiting the nodes between active and idle states is called duty‐cycling 34,35 . In an idle state, the CM keeps its radio receiver in an ON state to receive broadcast from the CH.…”

Section: Proposed Genetic Algorithm‐based Routing and Fault Route Recovery In Manetsmentioning

confidence: 99%

“…The energy utilized by the node in an idle state is comparatively less than in the active state. The energy utilized by the node in idle state (E idle ) is given by Equation () 34,35

E_{idle} = P_{idle} * T_{idle},

where P idle is the power used by the node in idle state and T idle is the time until which the node remains in idle state.…”

Section: Proposed Genetic Algorithm‐based Routing and Fault Route Recovery In Manetsmentioning

confidence: 99%

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A novel clustering method for fault recovery and routing in mobile ad‐hoc networks

Gurumoorthy¹,

Devaraj²,

Gopinath

et al. 2021

Int J Communication

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Summary Mobile ad‐hoc network (MANET) is a group of self‐organized autonomous wireless devices that serve communication in human unattended and emergency environments. The network is decentralized and uses wireless links for communication, which is vulnerable to network resource depletion rapidly. Energy and link stability are vital factors that support the prolonged operation of the network, obstructing earlier resource depletions. These depletions are overwhelmed with the help of scattered, isolated nodes; the process of augmenting them increases the control overhead. We propose a genetic algorithm‐based routing (GAR) with fault route recovery (FRR) caused due to isolated nodes. In this method, clustering is used for energy balancing for retaining the live nodes' count reliably. The FRR phase prevents cluster head flooding using the local rerouting process. The former phase of GAR‐FFR governs the network's energy optimization aiming at controlled energy consumption. The later part reduces routing overhead due to route failures, preventing backtracking to the cluster head. The proposed GAR‐FFR is analyzed using the following metrics: throughput, packet delivery ratio, live nodes count, remaining energy, and routing overhead. The proposed GAR‐FRR achieves 15.4% high throughput, 16.29% high live nodes, 8.9% high remaining energy, and 21.04% fewer control packets for different rounds, compared with the existing A‐ECOPS and REAC‐IN methods.

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Section: Proposed Genetic Algorithm‐based Routing and Fault Route Recovery In Manetsmentioning

confidence: 99%

“…The energy utilized by the node in an idle state is comparatively less than in the active state. The energy utilized by the node in idle state (E idle ) is given by Equation () 34,35

E_{idle} = P_{idle} * T_{idle},

where P idle is the power used by the node in idle state and T idle is the time until which the node remains in idle state.…”

Section: Proposed Genetic Algorithm‐based Routing and Fault Route Recovery In Manetsmentioning

confidence: 99%

A novel clustering method for fault recovery and routing in mobile ad‐hoc networks

Gurumoorthy¹,

Devaraj²,

Gopinath

et al. 2021

Int J Communication

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“…Furthermore, as these sensors are mostly deployed in the areas that are not accessible (facing difficulty in replacing or recharging the batteries) the use of particular efficiency theorem is visible. For this aspect, figure 1 shows the maximum power consumption, which is related to the trans-receiver task [1,2]. Generally, in the existing protocols, sensors mostly stay on idle mode, which consumes much energy and leads to the requirement of proposing a better efficiency model to take the advantage of the sleep mode.…”

Section: Introductionmentioning

confidence: 99%

Dynamic and Real-time Sleep Schedule Protocols for Energy Efficiency in WSNs

Yaeghoobi¹,

Soni²,

Tyagi³

2016

IJCNIS

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Wireless Sensor Networks are emerging technologies that are diverse on energy consumption from different aspects. In the task mode, energy consumption of sensor nodes is categorized in, data packet transmitting, data processing and idle mode. Fundamentally, higher power is required and utilized at the time of data transreceive as comparing to idle mode. However, power consumption of sensor in idle mode is necessarily important. To conserve energy, the network must provide quality of service sleep schedule, and use a mechanism to turn off the radio receiver periodically in coordinating method. Moreover, through dynamically round task management of sensors, significant energy saving can be achieved. Based on tasks and sleep schedules, nodes can form their clusters. It is necessary for real-time wireless applications to cogitate data transmit at the actual and response time based on the queries or tasks. This paper proposes Dynamic Immediate Data Report (DIDR) for real-time communication to schedule sleep mode of sensors in the network. Furthermore, to minimize the network energy consumption, Dynamic Schedule Data Report (DSDR) method is proposed. This method shows its efficiency by reducing the active time of nodes in the network. The performance analysis of the proposed works, illustrate effectively more energy efficiency as compared to existing methods.

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