An efficient genetic algorithm for large-scale transmit power control of dense industrial wireless networks

Abstract The industrial wireless local area network (IWLAN) is increasingly dense, not only due to the penetration of wireless applications into factories and warehouses, but also because of the rising need of redundancy for robust wireless coverage. Instead of powering on all the nodes with the maximal transmit power, it becomes an unavoidable challenge to control the transmit power of all wireless nodes on a large scale, in order to reduce interference and adapt coverage to the latest shadowing effects in the environment. Therefore, this paper proposes an efficient genetic algorithm (GA) to solve this transmit power control (TPC) problem for dense IWLANs, named GATPC. Effective population initialization, crossover and mutation, parallel computing as well as dedicated speedup measures are introduced to tailor GATPC for the large-scale optimization that is intrinsically involved in this problem. In contrast to most coverage-related optimization algorithms which cannot deal with the prevalent shadowing effects in harsh industrial indoor environments, an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects is used in GATPC, in order to enable accurate yet simple coverage prediction. Experimental validation and numerical experiments in real industrial cases show the promising performance of GATPC in terms of scalability to a hyper-large scale, up to 37-times speedup in resolution runtime, and solution quality to achieve adaptive coverage and to minimize interference.

Keywords: Genetic algorithms, high performance computing, interference suppression, radio propagation, scalability, wireless networks

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1. Introduction The dominant wireless local area network (WLAN) technology IEEE802.11 or WiFi is penetrating into factories to promote factories of the future (FoF) [1]. Compared to cabled technologies for interconnection of machines or devices, wireless technologies are superior regarding mobility, flexibility and cheap installation and maintenance. Compared to other wireless technologies, IEEE802.11 has the advantages of low cost, high data rate and considerable coverage distance. An industrial WLAN (IWLAN) is emerging as a basic infrastructure for manufacturing operations. For instance, production cell controllers can connect to other intelligent devices such as robot arms via an IWLAN on the shop floor [2], in order to realize agile production. The other industrial operations that are increasingly relying on IWLANs are illustrated as intra-factory transportation by automated guided vehicles (AGVs), video monitoring, process monitoring, etc. However, a typical industrial indoor environment is harsh in terms of radio propagation. Either a shop floor or a warehouse is dominant by various metal facilities, such as production machines/lines, storage racks, steel bars, metal plates, pipes, AGVs, cranes and forklifts. These metals easily shadow radio propagation [1, 3]. Consequently, this creates coverage hole for a WLAN that is already deployed. Moreover, an industrial indoor layout may occasionally be altered with the prevalence of flexible manufacturing [4]. This makes it increasingly difficult to maintain the expected wireless coverage in the presence of these shadowing effects. Therefore, it is of strategic importance to conceive an effective method to tackle these shadowing effects for robust wireless connection of personnel, machines, materials and products in FoF. Furthermore, an IWLAN is denser compared to a public WLAN. This is not only due to the large size of an industrial indoor environment, but also driven by the increasing industrial need for redundant coverage to ensure high network availability [5]. While large-scale optimization is increasingly desired [6, 7], most research on coverage optimization problems neglects the scalability of an optimization algorithm [8-12]. In addition, these studies tend to focus on optimization problems of wireless sensor networks (WSNs), although dense WLANs are showing up their application significance [13, 14]. Several powering-on/off solutions for dense WLANs have been introduced in literature, to enable energy- efficient dense WLANs. A concept of resource on demand (RoD) was proposed in [15], where redundant APs are powered off when they are detected to remain idle according to the volume and location of user demand. A more general model was proposed in [16] to further demonstrate the effectiveness of RoD. Energy savings up to 87% were proven to be achieved during low-traffic periods, with ha

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