Energy efficient multiple sink placement in wireless sensor networks

Bhattacharjee, Sanghita; Agarwal, Kavisha

doi:10.1109/nsyss2.2017.8267787

Cited by 5 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some approaches are basing the fog operation on 5G technology [46], [47], while other approaches (e.g., [48]) try to optimally localize the virtual machines in the fog network. Additionally, there exits a large body of research focused on multi-sink localization in WSNs [22], [23], [26], [27], [29], [49]- [53]. In one of the studies, the sink placement problem was considered as an optimization problem with an energy saving objective function.…”

Section: Related Workmentioning

confidence: 99%

“…In one of the studies, the sink placement problem was considered as an optimization problem with an energy saving objective function. For example, an optimal solution was proposed in [22], where different heuristics were used based on Cuckoo [23], Local search [26], Bactria [27], and Backbone information [29]. However, energy saving in WSNs may also depend on the used routing algorithms.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Energy Coherent Fog Networks Using Multi-Sink Wireless Sensor Networks

et al. 2021

View full text Add to dashboard Cite

Fog computing (FC) models the cloud computing paradigm expedient by bridging the breach between centralized data servers and diverse terrestrially distributed applications. It wields various wireless sensor networks (WSNs) that sprawl in the core of any IoT applications. Consequently, the operation of fog network turns on the efficiency of WSNs operation, while the all-inclusive network energy consumption depends on both FC and WSNs operation. This paper addresses how dissimilar organizations of a fog network can influence its effectiveness and energy savings. Chiefly, it appraises whether deploying multisink nodes in close enough vicinity to the fog nodes can give in energy savings and foster coherent data communication between WSNs and fog networks. To assess the multi-sink assignment problem the following four criteria are used: (i) Distance from the fog network nodes; (ii) Nodes degree; (iii) Sink nodes energy; and (iv) Sink nodes processing capabilities. This paper suggests four novel solutions to the multisink connectivity for some challenges of fog networks deeming: (i) Window Nondominant Set (WNS); (ii) Evaluation Based Approach (EBA); (iii) Harris Hawks Optimizer (HHO); and (iv) Modified HHO (MHHO). Distinct sets of experiments are conducted to check out algorithmic performance. The performance of all algorithms is measured and then compared to each other in terms of power consumption, runtime, packet loss, and localization error. One of the key supremacies of our approaches is the utilization of fog network for sensor networks data processing, principally with the large-scale networks. Yet, the communication challenges could need further study due to the limited communication range of the sensors.

show abstract