## 2 Related Research Work  
Various researchers have focused on proposing different routing protocols for WSNs based on different parameters, such as end-end delay, successful packets delivered to sink, network lifetime, overall energy consumption, control packet overhead, and sink node mobility, etc. [PERSON] et al. [21] presented a detailed survey for energy efficient and energy balanced routing protocols for WSNs. The authors argued that energy efficiency, packet delivery ratio and average end-end delay are the most critical and significant parameters for delay-tolerant and delay-sensitive applications involving WSNs. Furthermore, in this survey, the taxonomy of cluster-based routing protocols for WSNs was also discussed in terms of the energy efficiency and energy balancing aspects. Routing protocols in WSNs can be segmented into two main categories, i.e., hierarchical and non-hierarchical routing protocols. Non-hierarchical routing protocols are proposed on the basis of overhearing, flooding, and information related to the advertisement of the sink's position through agent node selection, whereas hierarchical routing protocols are proposed on the basis of (i) grid-based, tree-based, cluster-based and area-based routing. Different hierarchical routing protocols have their own merits and demerits, but as far as cluster-based hierarchical routing protocols are concerned, researchers have been challenged with a task of achieving an optimal balance between end-end delay and energy consumption [4; 5; 6; 21]. [PERSON] et al. [22] introduced an emerging concept--the 'utilization of working-sleeping cycle' of sensor nodes to prolong the network lifetime. The working-sleeping cycle can be segmented into two categories--synchronous and asynchronous working-sleeping cycle. Recent studies have revealed that a synchronous working-sleeping cycle in sensor nodes could lead to an improvement in energy consumption, but significant contribution is required for efficient synchronization of sensor nodes. [PERSON] et al. [23] presented an energy-efficient synchronization algorithm for sensor nodes in which counter-based and exponential smoothing algorithms could improve the energy consumption using adaptive adjustment of traffic and wakeup period. Moreover, the asynchronous working-sleeping cycle strategy was explored in recent studies as well. Asynchronous working-sleeping schedules depend on network connectivity requirements in terms of traffic coverage area [8; 9]. [PERSON] et al. [24] proposed an asynchronous working-sleeping schedule technique in which required network coverage was achieved with a minimum number of awake sensor nodes. Due to the independent working-sleeping cycle of each sensor node in asynchronous working-sleeping strategy, opportunistic node connection can be established between sensor node and its neighbors, thus we need an Opportunistic Connection Random Graph (OCRG) theory to form a spanning tree formation of sensor nodes having opportunistic node connections between each other. In [25], [PERSON] et al. proposed a novel random graph modeling for heterogeneous sensor networks based on different transmission ranges and a new routing metric supporting opportunistic node connections. [PERSON] et al. [26] proposed an energy-efficient multi-disjoint path opportunistic node connection routing protocol for smart grids (SGs) neighborhood area networks (NAN) inspired by opportunistic connection random graph theory in WSNs with sink mobility. This routing protocol reduces the overall energy consumption, increases the PDR, increases the network lifetime and decreases the end-end network delay against existing benchmark schemes. Many recent studies have addressed the problem of WSN clustering. Low Energy Adaptive Clustering Hierarchy (LEACH) variants were proposed by [PERSON] et al. [27], [PERSON] et al. [28] and [PERSON] et al.