Energy Coherent Fog Networks Using Multi-Sink Wireless Sensor Networks

Abstract

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.

A Hybrid Heuristic Model for Duty Cycle Framework Optimization

“…For instance, in the study of Draz et al, a Data Packet Forwarding Algorithm (DFPA) and Watchman Layer Update Mechanism (WLUM) were implemented [18] in WSNs to maintain energy efficiently. Also, Ramadan et al presented a method of placing multisink nodes close to fog nodes that can save energy and facilitate coherent data transfer between WSNs and fog networks [19]. However, the crucial concerns of WSNs face are lowering energy usage and increasing network longevity.…”

A new clustering‐based optimised energy approach for fog‐enabled IoT networks

“…Routing protocols based on hierarchical clustering algorithms have proven to be effective techniques that can be implemented in a Fog computing environment in order to reduce energy consumption, redundancy of data generated by IoT devices, and interference caused by communications established between the IoT and Fog layers [25]. This can be accomplished by selecting a predefined number of sensors or IoT devices, called Small Proxy (SP) servers, as a gateway for the benefit of other nodes to reach the Fog Node (FN) as shown in Figure 1.…”