An efficient genetic algorithm for large-scale planning of robust industrial wireless networks

An industrial indoor environment is harsh for wireless communications compared to an office environment, because the prevalent metal easily causes shadowing effects and affects the availability of an industrial wireless local area network (IWLAN). On the one hand, it is costly, time-consuming, and ineffective to perform trial-and-error manual deployment of wireless nodes. On the other hand, the existing wireless planning tools only focus on office environments such that it is hard to plan IWLANs due to the larger problem size and the deployed IWLANs are vulnerable to prevalent shadowing effects in harsh industrial indoor environments. To fill this gap, this paper proposes an overdimensioning model and a genetic algorithm based over-dimensioning (GAOD) algorithm for deploying large-scale robust IWLANs. As a progress beyond the state-of-the-art wireless planning, two full coverage layers are created. The second coverage layer serves as redundancy in case of shadowing. Meanwhile, the deployment cost is reduced by minimizing the number of access points (APs); the hard constraint of minimal inter-AP spatial paration avoids multiple APs covering the same area to be simultaneously shadowed by the same obstacle. The computation time and occupied memory are dedicatedly considered in the design of GAOD for large-scale optimization. A greedy heuristic based over-dimensioning (GHOD) algorithm and a random OD algorithm are taken as benchmarks. In two vehicle manufacturers with a small and large indoor environment, GAOD outperformed GHOD with up to 20% less APs, while GHOD outputted up to 25% less APs than a random OD algorithm. Furthermore, the effectiveness of this model and GAOD was experimentally validated with a real deployment system

An efficient genetic algorithm for large-scale transmit power control of dense and robust wireless networks in harsh industrial environments

The industrial wireless local area network (IWLAN) is increasingly dense, due to not only the penetration of wireless applications to shop floors and warehouses, but also the rising need of redundancy for robust wireless coverage. Instead of simply powering on all access points (APs), there is an unavoidable need to dynamically control the transmit power of APs on a large scale, in order to minimize interference and adapt the coverage to the latest shadowing effects of dominant obstacles in an industrial indoor environment. To fulfill this need, this paper formulates a transmit power control (TPC) model that enables both powering on/off APs and transmit power calibration of each AP that is powered on. This TPC model uses an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects, to enable accurate yet simple coverage prediction. An efficient genetic algorithm (GA), named GATPC, is designed to solve this TPC model even on a large scale. To this end, it leverages repair mechanism-based population initialization, crossover and mutation, parallelism as well as dedicated speedup measures. The GATPC was experimentally validated in a small-scale IWLAN that is deployed a real industrial indoor environment. It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC. Moreover, sensitivity analysis was performed to reveal the produced interference and the qualification rate of GATPC in function of varying target coverage percentage as well as number and placement direction of dominant obstacles. (C) 2018 Elsevier B.V. All rights reserved

EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

Handover Necessity Estimation for 4G Heterogeneous Networks

One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively

An algorithm for optimal network planning and frequency channel assignment in indoor WLANs

The increased use of wireless local area networks has led to an increased interference and a reduced performance, as a high amount of access points are often operating on the same frequency channel. This paper presents a network planning algorithm that minimizes the number of access points required for a certain throughput and optimizes the frequency allocated to each AP, leading to reduced interference. The network planning algorithm is based on a heuristic and the frequency planning algorithm on a combination of a greedy algorithm and a Vertex-Coloring-Based Approach. The algorithm provides a good performance and has a limited computation time

Coverage prediction and optimization algorithms for indoor environments

A heuristic algorithm is developed for the prediction of indoor coverage. Measurements on one floor of an office building are performed to investigate propagation characteristics and validations with very limited additional tuning are performed on another floor of the same building and in three other buildings. The prediction method relies on the free-space loss model for every environment, this way intending to reduce the dependency of the model on the environment upon which the model is based, as is the case with many other models. The applicability of the algorithm to a wireless testbed network with fixed WiFi 802.11b/g nodes is discussed based on a site survey. The prediction algorithm can easily be implemented in network planning algorithms, as will be illustrated with a network reduction and a network optimization algorithm. We aim to provide an physically intuitive, yet accurate prediction of the path loss for different building types

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Traffic agents for improving QoS in mixed infrastructure and ad hoc modes wireless LAN

As an important complement to infrastructured wireless networks, mobile ad hoc networks (MANET) are more flexible in providing wireless access services, but more difficult in meeting different quality of service (QoS) requirements for mobile customers. Both infrastructure and ad hoc network structures are supported in wireless local area networks (WLAN), which can offer high data-rate wireless multimedia services to the mobile stations (MSs) in a limited geographical area. For those out-of-coverage MSs, how to effectively connect them to the access point (AP) and provide QoS support is a challenging issue. By mixing the infrastructure and the ad hoc modes in WLAN, we propose in this paper a new coverage improvement scheme that can identify suitable idle MSs in good service zones as traffic agents (TAs) to relay traffic from those out-of-coverage MSs to the AP. The service coverage area of WLAN is then expanded. The QoS requirements (e.g., bandwidth) of those MSs are considered in the selection process of corresponding TAs. Mathematical analysis, verified by computer simulations, shows that the proposed TA scheme can effectively reduce blocking probability when traffic load is light