HDDS: Hierarchical Data Dissemination Strategy for energy optimization in dynamic wireless sensor network under harsh environments

Mazumdar, Nabajyoti; Nag, Amitava; Nandi, Sukumar

doi:10.1016/j.adhoc.2020.102348

Cited by 35 publications

(15 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In EAUCA [54], the number of CHs is not explicitly calculated but it depends on the input parameters, so it is adaptive. ECPF [44], DSBCA [47], ECFU [50], OSC [13], MOFCA [51], HDDS [55] and TTDFP [52] do not take in consideration this factor. Instead, they elect a random number of CHs in each round.…”

Section: B Discussionmentioning

confidence: 99%

“…DSBCA [47], EBUC [62] and MMDCP [68] add other criteria related to network density and the desired size of clusters to balance the energy usage between the CHs. In HDDS [55], a multiobjective function which takes into account the CHs remain-ing energy and the transmission energy that will be spent by a SN to reach a CH is used to decide which CH to join. This has the advantage of optimizing the energy dissipation of both CH and non-CH SNs.…”

Section: B Discussionmentioning

confidence: 99%

“…Likewise, single-hop is also used in several protocols for inter-cluster communication. However, some clustering protocols add multi-hop routing between CHs and BS, including LEACH-DT [41], ECPF [44], EBUC [62], TPSO-CR [40], ETPSO-CR [16], LPOBC [66], TTCH-WSN [67], MMDCP [68], MOFCA [51], TTDFP [52], EAUCA [54], HDDS [55], UCMR-FL [56]. Since the transmission energy is proportional to the transmission distance, the use of multi-hop routing between the CHs and the BS can improve the energy efficiency of the WSN.…”

Section: B Discussionmentioning

confidence: 99%

“…HDDS: Mazumdar et al proposed HDDS [55], an energyefficient hierarchical protocol aiming at enhancing the network coverage and supporting the dynamic changes in the WSN topology. To select the optimal set of CHs, every SN triggers a delay timer which is tuned to match the better candidates for the CH role with the smaller values.…”

Section: ) Distributed Protocolsmentioning

confidence: 99%

See 3 more Smart Citations

Towards Energy Efficient Clustering in Wireless Sensor Networks: A Comprehensive Review

2021

View full text Add to dashboard Cite

Clustering is one of the fundamental approaches used to optimize energy consumption in wireless sensor networks. Clustering protocols proposed in the literature can be classified according to different criteria related to their features such as the clustering methodology, objectives, cluster count and size, etc. This paper reviews the existing feature-based classifications of clustering protocols and elaborates a more generic and unified classification. It also analyzes and discusses the relevant design factors that may influence the energy efficiency of clustering protocols and accordingly proposes a new energy-oriented taxonomy. State-of-the-art clustering solutions are then reviewed and evaluated following the proposed taxonomy.

show abstract

Section: B Discussionmentioning

confidence: 99%

Section: B Discussionmentioning

confidence: 99%

Section: B Discussionmentioning

confidence: 99%

Section: ) Distributed Protocolsmentioning

confidence: 99%

See 2 more Smart Citations

Towards Energy Efficient Clustering in Wireless Sensor Networks: A Comprehensive Review

2021

View full text Add to dashboard Cite

show abstract

“…Mazumdar and their team proposed Hierarchical Data Dissemination Strategy for energy optimization of wireless sensor network especially in the harsh environment. Along with the fault tolerance strategy at steady phase of communication confirms the an uninterrupted data communication 20 . In 2020, Kundaliya and Hadia proposed a modified version of RPSS (M‐RPSS).…”

Section: Introductionmentioning

confidence: 88%

Implementation and comparative analysis of evolutionary algorithms for energy optimization in wireless sensor networks

Kundaliya

Hadia

2021

Int J Communication

View full text Add to dashboard Cite

Summary Wireless sensor networks will be at the epitome of applications in near future. It is going through tremendous positive changes. Although it suffers from some limitations and it sorts out its limitations day by day. The biggest limitation of wireless sensor networks is the limited energy of the nodes. Most of the energy is used during the routing of the data. An optimized way of routing will save the valuable energy of the node and helpful for increasing the network's lifetime. The optimization algorithms are indeed utterly helpful in many applications across the different fields to optimize the resources. In the proposed worked we have applied Adaptive Particle Swarm Optimization (APSO), Ant Colony Optimization (ACO), Genetic Algorithms (GA), and Simulated Annealing (SA) to a Modified Rendezvous Point Selection Scheme and observed the effect on the network lifetime and energy consumption in the network. We have made an exhaustive comparison of all the optimization algorithms with considerable simulations.

show abstract

Fault‐tolerance based on augmenting approach in wireless sensor networks

Belkadi

Lehsaini

Tahraoui

2022

Concurrency and Computation

View full text Add to dashboard Cite

A critical node is a sensor whose failure causes loss of connectivity and network fragmentation. In wireless sensor networks, the failure of a critical node, like the failure of all sensor nodes, can be caused by energy depletion or physical failure. To overcome the problem of failure of such nodes, this article proposes a fault-tolerant strategy that allows a routing protocol to tolerate the failure of a critical node. The proposed strategy is carried out in two phases. In the first phase, a hybrid genetic algorithm with a local search heuristic called genetic algorithm-critical node problem (GA-CNP) is used to select the critical nodes and in the second phase, an algorithm called Aug-CNP is involved to deal with the augmentation problem by deploying additional wireless edges to preserve network connectivity in case of critical node failure. Our proposal has been developed using the OMNET++ simulator, evaluated, and compared to the AODV protocol. The simulation results showed that the GA-CNP algorithm selects the critical nodes whose failure can degrade the network lifetime with a rate of 40%. Moreover, the Aug-CNP algorithm applied to the AODV protocol brings improvements in terms of network lifetime which reaches 22% compared to the traditional AODV protocol.

show abstract

HDDS: Hierarchical Data Dissemination Strategy for energy optimization in dynamic wireless sensor network under harsh environments

Cited by 35 publications

References 33 publications

Towards Energy Efficient Clustering in Wireless Sensor Networks: A Comprehensive Review

Towards Energy Efficient Clustering in Wireless Sensor Networks: A Comprehensive Review

Implementation and comparative analysis of evolutionary algorithms for energy optimization in wireless sensor networks

Fault‐tolerance based on augmenting approach in wireless sensor networks

Contact Info

Product

Resources

About