Improve Energy Consumption and Signal Transmission Quality of Routings in Wireless Sensor Networks

Abstract

Wireless (smart) sensor networks (WSNs) comprise a myriad of embedded wireless smart sensors. They play a cardinal role in the functioning of many applications, such as the Internet of Things, smart grids, smart production systems, and smart homes, which ultimately render them paramount instruments in the modern age. Recent advances in WSNs have resulted in the rapid development of sensors. However, WSNs will only able to achieve better execution efficiencies if their energy consumption-owing to limited battery life and difficulty of recharging-can be better controlled. Moreover, signal transmission quality determines WSN performance. Hence, two main concerns-energy consumption and signal transmission quality-should be addressed to improve the performance of WSNs. Thus, a new bi-objective simplified swarm optimization algorithm (bSSO) is proposed by employing the concepts of simple routing, SSO, and crowd distance. The performance and applicability of the proposed bSSO using eight different parameter settings are demonstrated through an experiment involving ten WSN benchmarks ranging from 100 to 1000 sensors. The proposed algorithm is then compared with NSGA-II, which is an algorithm widely used to solve multi-objective problems. The results show that the proposed bSSO can successfully achieve the aim of this work.

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

“…Network reliability is the most well-known technique for estimating the probability that the network is still operational under predefined conditions, including signal quality [11], budget [12], transition time [13], transition rate [14,15], weight [16], volume [17], production numbers [18], and flow [19].…”

“…Exact reliability methods can be categorized as direct [20,21] (e.g., state-space algorithm [44,45] and the binary-decision diagram (BDD) [39,40,41]) and indirect [1,4,5,8,11,12,19,25,26,29,30,31,33,34,35,36,38,41,42,43]. Indirect methods are based on minimal cuts (MCs) [41,42,43] or minimal paths (MPs) [1,4,5,8,11,12,19,25,26,29,30,31,33,34,35,36,38] and need to solve an NP-hard problem (or a #P-Hard problem) to obtain all the MPs or MCs [20,21]. arXiv 2020/11/15 -3 -Subsequently...…”

“…The state-space algorithm of direct methods is less efficient than identifying the MPs or MCs of indirect methods, and the BDD is challenging to code [3,40,41]. Therefore, indirect methods based on MCs or MPs are more popular than direct methods [1,4,5,8,11,12,19,25,26,29,30,31,33,34,35,36,38,41,42,43]. However, one study suggests that the BAT direct method [44] solves one NP-hard problem to obtain all connected vectors or disconnected vectors and is more efficient than using indirect methods and solving two NP-hard problems [20,21].…”

A Novel Constraints Model of Credibility-Fuzzy for Reliability Redundancy Allocation Problem by Simplified Swarm Optimization

“…The objective function to maximize the system reliability for the complex (bridge) system in Figure 3 is shown in above Equation (11). The constraints of cost, weight and volume are shown in above Equations ( 12)-( 14), respectively.…”

“…The reliability enhancement has increasingly become important in most systems because the system reliability is an important measure of system performance in many practical systems. For example, medical systems [1], video systems [2], traffic systems [3], industrial intelligence systems [4], network systems [5][6][7][8][9], wireless sensor networks [10,11], power transmission networks [12], social networks [13], and Internet of Things [14,15]. The evaluation and enhancement of system reliability must be optimized in the early design stage because the enhancement of reliability is the most efficient at this stage [16,17].…”