Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570985
S. Rinaldi, P. Ferrari, E. Sisinni, A. Depari, A. Flammini
During the last years, the industrial automation field was radically revolutionized by Industry 4.0 paradigm. The possibility to interconnect industrial machinery to the cyber world through Cyber Physical System (CPS) enables innovative services, but open new challenges on communication and data management sides. In fact, it is important to identify not only which CPS generated an information, but also where it is located on the production plant, since the configuration of the automation could dynamically change in function of the product being produced. In our research work, a low-cost (and low power) approach for the estimation of the relative position of CPS in industrial plant has been investigated. The proposed solution exploits the Direction Finding service introduced by Bluetooth 5.0. The Angle of Arrival (AoA) method in connection-less mode is used to estimate the angle between a tag and the receiving anchors. In this way, the computational power (and, the relative power consumption) of the tag is limited. The preliminary characterization of this solution shows as the maximum error angle is about 5° at a distance of 4 m between anchor and tag. This result is promising, although the application of the BLE Direction Finding service requires a careful design of the array of antennas and of its radiation pattern to allow a proper localization in the three-dimensional space.
{"title":"An Evaluation of Low-Cost Self-Localization Service Exploiting Angle of Arrival for Industrial Cyber-Physical Systems","authors":"S. Rinaldi, P. Ferrari, E. Sisinni, A. Depari, A. Flammini","doi":"10.1109/africon51333.2021.9570985","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570985","url":null,"abstract":"During the last years, the industrial automation field was radically revolutionized by Industry 4.0 paradigm. The possibility to interconnect industrial machinery to the cyber world through Cyber Physical System (CPS) enables innovative services, but open new challenges on communication and data management sides. In fact, it is important to identify not only which CPS generated an information, but also where it is located on the production plant, since the configuration of the automation could dynamically change in function of the product being produced. In our research work, a low-cost (and low power) approach for the estimation of the relative position of CPS in industrial plant has been investigated. The proposed solution exploits the Direction Finding service introduced by Bluetooth 5.0. The Angle of Arrival (AoA) method in connection-less mode is used to estimate the angle between a tag and the receiving anchors. In this way, the computational power (and, the relative power consumption) of the tag is limited. The preliminary characterization of this solution shows as the maximum error angle is about 5° at a distance of 4 m between anchor and tag. This result is promising, although the application of the BLE Direction Finding service requires a careful design of the array of antennas and of its radiation pattern to allow a proper localization in the three-dimensional space.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570963
A. Ogunjuyigbe, T. Ayodele, Chimeremeze Praise Lasarus, A. Yusuff, T. Mosetlhe
One of the primary tasks of electric utilities is to accurately predict the load demand requirements of consumers, especially for short term prediction. In view of this, different methods have been proposed for load prediction. In this paper, three methods (i.e. Multiple Linear Regression (MLR), Seasonal Auto Regressive Integrated Moving Average with Exogenous Variables (SARIMAX) and Long Short Term Memory (LSTM)) are compared to forecast load consumption in a typical Nigerian University. The main objective is to determine which of the techniques best model the load consumption pattern of the University accurately. Load forecast was made for weekdays (Monday-Friday) and weekends (Saturday and Sunday). The result showed that the LSTM technique is the best performing model achieving the least errors. The technique returns the mean absolute error (MAE) that varies between 0.029-0.093, mean square error (MSE) ranging between 0.0014-0.014 and root mean square error that has values between 0.037-0.12.
{"title":"Comparative Analysis of Short-Term Load Forecasting Methods","authors":"A. Ogunjuyigbe, T. Ayodele, Chimeremeze Praise Lasarus, A. Yusuff, T. Mosetlhe","doi":"10.1109/africon51333.2021.9570963","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570963","url":null,"abstract":"One of the primary tasks of electric utilities is to accurately predict the load demand requirements of consumers, especially for short term prediction. In view of this, different methods have been proposed for load prediction. In this paper, three methods (i.e. Multiple Linear Regression (MLR), Seasonal Auto Regressive Integrated Moving Average with Exogenous Variables (SARIMAX) and Long Short Term Memory (LSTM)) are compared to forecast load consumption in a typical Nigerian University. The main objective is to determine which of the techniques best model the load consumption pattern of the University accurately. Load forecast was made for weekdays (Monday-Friday) and weekends (Saturday and Sunday). The result showed that the LSTM technique is the best performing model achieving the least errors. The technique returns the mean absolute error (MAE) that varies between 0.029-0.093, mean square error (MSE) ranging between 0.0014-0.014 and root mean square error that has values between 0.037-0.12.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123210889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570946
Craig S. Carlson, D. M. Rubin, Vilma Heikkilä, M. Postema
Accurately modelling the susceptibility, infection, and recovery of populations with regards to the COVID-19 pandemic is highly relevant for the implementation of countermeasures by governing bodies. In the past year, several thousands of articles on COVID-19 modelling were published. The spread of the pandemic has frequently been modelled using the Susceptible-Infected-Recovered (SIR) epidemic model owing to the low level of complexity. In recognition of its simplicity, we developed an SIR model to represent the spread of disease on a global scale, irrespective of mutation and countermeasures. The SIR parameters were reverse-engineered from aggregated global data. This model is the first to retrospectively deduce the initial incidence. The average transmission and recovery parameters were computed to be 0.33 week−1 and 0.23 week−1, respectively. These values lie well within the range of reported values on COVID-19 determined from geographically different regions. The model was simulated in the Ventana® simulation environment Vensim® for a 65-weeks duration and an adjusted initial infection incidence, which was presumed three times the reported initial infection incidence. The simulated data visually aligns with the real incidence data. We attribute the discrepancy between the presumed initial value and the reported value to lack of testing facilities on the starting date of 1 March 2020. Our parameter extraction suggests a novel methodology to quantify undertesting retrospectively in epidemics.
{"title":"Extracting transmission and recovery parameters for an adaptive global system dynamics model of the COVID-19 pandemic","authors":"Craig S. Carlson, D. M. Rubin, Vilma Heikkilä, M. Postema","doi":"10.1109/africon51333.2021.9570946","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570946","url":null,"abstract":"Accurately modelling the susceptibility, infection, and recovery of populations with regards to the COVID-19 pandemic is highly relevant for the implementation of countermeasures by governing bodies. In the past year, several thousands of articles on COVID-19 modelling were published. The spread of the pandemic has frequently been modelled using the Susceptible-Infected-Recovered (SIR) epidemic model owing to the low level of complexity. In recognition of its simplicity, we developed an SIR model to represent the spread of disease on a global scale, irrespective of mutation and countermeasures. The SIR parameters were reverse-engineered from aggregated global data. This model is the first to retrospectively deduce the initial incidence. The average transmission and recovery parameters were computed to be 0.33 week−1 and 0.23 week−1, respectively. These values lie well within the range of reported values on COVID-19 determined from geographically different regions. The model was simulated in the Ventana® simulation environment Vensim® for a 65-weeks duration and an adjusted initial infection incidence, which was presumed three times the reported initial infection incidence. The simulated data visually aligns with the real incidence data. We attribute the discrepancy between the presumed initial value and the reported value to lack of testing facilities on the starting date of 1 March 2020. Our parameter extraction suggests a novel methodology to quantify undertesting retrospectively in epidemics.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115934767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9571015
Wondale Kebede Abitew, Y. Negash
This research work proposes new constraint-based hybrid resiliency mechanisms that are the combination of different disjoint flavors of 1+1 Dedicated Path Protection (DPP) and Restoration schemes. The proposed resiliency mechanisms are 1+1 Link-Disjoint DPP + Restoration, 1+1 Node-Disjoint DPP + Restoration and 1+1 SRG-Disjoint DPP + Restoration. Their performance is evaluated using Net2plan simulation tool. The results show that network availability and recoverability are improved when it is compared to non-combined counter parts. 1+1 Node-Disjoint + Restoration shows best recoverability at lower traffic loads during link or SRG failures. At higher traffic loads, 1+1 SRG-Disjoint + Restoration performs best in recoverability during SRG failures. For instance, 1+1 SRG-Disjoint + Restoration has on average 16.8% higher recoverability than 1+1 Link-Disjoint + Restoration at higher traffic loads. These performance enhancements are obtained with cost of relatively higher blocking probability.
{"title":"Constraint-Based Hybrid Resiliency Mechanisms for Better Resource Utilization and Service Performance Quality in ASON SLA","authors":"Wondale Kebede Abitew, Y. Negash","doi":"10.1109/africon51333.2021.9571015","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9571015","url":null,"abstract":"This research work proposes new constraint-based hybrid resiliency mechanisms that are the combination of different disjoint flavors of 1+1 Dedicated Path Protection (DPP) and Restoration schemes. The proposed resiliency mechanisms are 1+1 Link-Disjoint DPP + Restoration, 1+1 Node-Disjoint DPP + Restoration and 1+1 SRG-Disjoint DPP + Restoration. Their performance is evaluated using Net2plan simulation tool. The results show that network availability and recoverability are improved when it is compared to non-combined counter parts. 1+1 Node-Disjoint + Restoration shows best recoverability at lower traffic loads during link or SRG failures. At higher traffic loads, 1+1 SRG-Disjoint + Restoration performs best in recoverability during SRG failures. For instance, 1+1 SRG-Disjoint + Restoration has on average 16.8% higher recoverability than 1+1 Link-Disjoint + Restoration at higher traffic loads. These performance enhancements are obtained with cost of relatively higher blocking probability.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115960360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570937
Lusani Mamushiane, Lawrence Mboweni, H. Kobo, M. Mudumbe, Joyce B. Mwangama, A. Lysko
Active radio access network (RAN) infrastructure sharing has emerged as a promising solution for efficient spectrum utilization, capital and operational cost savings, improved MVNO penetration rates and lower broadband retail prices in both emerging and developed markets. This paper presents a tutorial on the testbed implementation of an active RAN sharing architecture, leveraging multi-vendor virtualized 5G and 4G core networks running on commodity hardware and proprietary 4G RAN equipment (eNodeB). Troubleshooting techniques used for different implementation challenges encountered are also presented in this contribution. The performance of the proposed architecture was validated using end-user quality of experience (QoE) as the key performance indicator. The results show no performance degradation when RAN sharing is being utilized.
{"title":"4G RAN Infrastructure Sharing by 5G Virtualized Mobile Network Operators: A Tutorial","authors":"Lusani Mamushiane, Lawrence Mboweni, H. Kobo, M. Mudumbe, Joyce B. Mwangama, A. Lysko","doi":"10.1109/africon51333.2021.9570937","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570937","url":null,"abstract":"Active radio access network (RAN) infrastructure sharing has emerged as a promising solution for efficient spectrum utilization, capital and operational cost savings, improved MVNO penetration rates and lower broadband retail prices in both emerging and developed markets. This paper presents a tutorial on the testbed implementation of an active RAN sharing architecture, leveraging multi-vendor virtualized 5G and 4G core networks running on commodity hardware and proprietary 4G RAN equipment (eNodeB). Troubleshooting techniques used for different implementation challenges encountered are also presented in this contribution. The performance of the proposed architecture was validated using end-user quality of experience (QoE) as the key performance indicator. The results show no performance degradation when RAN sharing is being utilized.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132019632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570933
T. Ayodele, A. Ogunjuyigbe, Olubiyi Sulaiman, T. Mosetlhe, A. Yusuff, M. Okelola
Accessibility to electricity has been a pain point to residential end-users mostly in remote and rural areas due to high installation costs and high tariff rates. This paper presents a standalone PV system for a typical residential building that incorporates load management using mixed-integer linear programming. This was evaluated by taking the energy profile of a building and using forecasted solar irradiance to obtained optimal sizing of PV and battery system. The appliances considered under this study were classified into controllable and uncontrollable as prescribed by the owner. The scheduling pattern of appliances was modeled using the mixed-integer linear programming constrained due to battery state of charge, season variation, and present load demand. Three cases were considered during the implementation of this study, the initial capacity of the battery bank was rated at 25kWh, the battery state of charge (SOC) was maintained at less than 50% of its capacity throughout the cases, also, the demand satisfaction of the end-users varies between 78%-88% which ensures higher weighted appliances in terms of priority were guaranteed for operation. The significance of this paper is to enable residential users to improve their standard of living with respect to an available and accessible source of power (photovoltaic system) with optimal scheduling of appliances
{"title":"Load Management Strategy for Residential Stand-Alone Photovoltaic Systems using Mixed-Integer Linear Programming","authors":"T. Ayodele, A. Ogunjuyigbe, Olubiyi Sulaiman, T. Mosetlhe, A. Yusuff, M. Okelola","doi":"10.1109/africon51333.2021.9570933","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570933","url":null,"abstract":"Accessibility to electricity has been a pain point to residential end-users mostly in remote and rural areas due to high installation costs and high tariff rates. This paper presents a standalone PV system for a typical residential building that incorporates load management using mixed-integer linear programming. This was evaluated by taking the energy profile of a building and using forecasted solar irradiance to obtained optimal sizing of PV and battery system. The appliances considered under this study were classified into controllable and uncontrollable as prescribed by the owner. The scheduling pattern of appliances was modeled using the mixed-integer linear programming constrained due to battery state of charge, season variation, and present load demand. Three cases were considered during the implementation of this study, the initial capacity of the battery bank was rated at 25kWh, the battery state of charge (SOC) was maintained at less than 50% of its capacity throughout the cases, also, the demand satisfaction of the end-users varies between 78%-88% which ensures higher weighted appliances in terms of priority were guaranteed for operation. The significance of this paper is to enable residential users to improve their standard of living with respect to an available and accessible source of power (photovoltaic system) with optimal scheduling of appliances","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132056019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570902
Thomas Nyajowi, N. Oyie, M. Ahuna
Vandalism is a deliberate damage to property by humans and it has become rampant in the engineering fields. The activity results into huge financial and social loses and the vice is declared when human image is detected in the restricted area without authority to cause an unauthorized change in a predetermined scene that could be vandalized. This act requires an automated real-time detection of the presence of the vandal so that he can be stopped from damaging the property. Human Image recognition process is the best method for detection of vandalism. In this research paper, we propose a deep learning architecture combining Convolutional Neural Networks and Long Short Term memory (CNN-LSTM) which has the ability to exhaust spatial relationship and temporal prediction of the output. The main objective of this research work is to develop, train, test and validate CNN-LSTM against CNN and LSTM models to prove the superiority of the proposed model in image recognition. Image detection is achieved by feeding the images captured by installed image sensors (CCD camera) to a hybrid neural network classifier which is trained to recognize human images. The CNN-LSTM hybrid approach not only improves the predictive accuracy of image recognition from raw data but also reduces the computational complexity. The model is trained and tested with image-Net dataset which is the largest clean image dataset for vision research. Results show that the proposed model is able to achieve a training accuracy of 98% while a standalone CNN achieved 88%. The result show that the hybrid model is superior.
{"title":"CNN Real-Time Detection of Vandalism Using a Hybrid -LSTM Deep Learning Neural Networks.","authors":"Thomas Nyajowi, N. Oyie, M. Ahuna","doi":"10.1109/africon51333.2021.9570902","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570902","url":null,"abstract":"Vandalism is a deliberate damage to property by humans and it has become rampant in the engineering fields. The activity results into huge financial and social loses and the vice is declared when human image is detected in the restricted area without authority to cause an unauthorized change in a predetermined scene that could be vandalized. This act requires an automated real-time detection of the presence of the vandal so that he can be stopped from damaging the property. Human Image recognition process is the best method for detection of vandalism. In this research paper, we propose a deep learning architecture combining Convolutional Neural Networks and Long Short Term memory (CNN-LSTM) which has the ability to exhaust spatial relationship and temporal prediction of the output. The main objective of this research work is to develop, train, test and validate CNN-LSTM against CNN and LSTM models to prove the superiority of the proposed model in image recognition. Image detection is achieved by feeding the images captured by installed image sensors (CCD camera) to a hybrid neural network classifier which is trained to recognize human images. The CNN-LSTM hybrid approach not only improves the predictive accuracy of image recognition from raw data but also reduces the computational complexity. The model is trained and tested with image-Net dataset which is the largest clean image dataset for vision research. Results show that the proposed model is able to achieve a training accuracy of 98% while a standalone CNN achieved 88%. The result show that the hybrid model is superior.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131497279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570949
E. Okafor, J. Sompo, F. Igboamalu, K. Ouahada
Numerical modeling has been instrumental in studying the behavior of continuous wave (CW) erbium-doped ring cavity fiber laser (EDFRL). This can be obtained by providing a customized solution for a large parameter. In this paper, erbium-doped ring cavity fiber laser model is presented. The proposed model is obtained using a simple application of a fast-shooting algorithm combined with a secant-method. The performance results show that this algorithm is a flexible tool that can be used in modeling and simulation. However, the solution can also be implemented in other types of fiber lasers including, ytterbium, and thulium as well as co-doped fiber lasers
{"title":"Numerical Approach for CW ring cavity fiber laser Using Shooting Method","authors":"E. Okafor, J. Sompo, F. Igboamalu, K. Ouahada","doi":"10.1109/africon51333.2021.9570949","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570949","url":null,"abstract":"Numerical modeling has been instrumental in studying the behavior of continuous wave (CW) erbium-doped ring cavity fiber laser (EDFRL). This can be obtained by providing a customized solution for a large parameter. In this paper, erbium-doped ring cavity fiber laser model is presented. The proposed model is obtained using a simple application of a fast-shooting algorithm combined with a secant-method. The performance results show that this algorithm is a flexible tool that can be used in modeling and simulation. However, the solution can also be implemented in other types of fiber lasers including, ytterbium, and thulium as well as co-doped fiber lasers","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127057108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9570896
Y. B. Bekele, Y. Negash
Due to the growth in data traffic volume and diversification of applications that use telecom network infrastructure, more power consuming telecommunication network equipments have been deployed. This scenario has led to an increase in the power consumption of the sector. In order to overcome this problem, stakeholders are striving to come up with ways to minimize this power consumption. In this work, a sleep mode operational strategy which takes the Physical Layer Impairment (PLI) and power loss/attenuation is proposed and an Integer Linear Programming (ILP) formulation is given. An implementation of the approach is carried out using GLPK optimizer and TOTEM toolbox simulation environments and results analyzed taking two Ethio Telecom backbone Optical Transport Network (OTN) segments. These optimizations & simulations help to analyze the impacts on Quality of Service (QoS) of applying this approach in addition to its main goal of power consumption minimization. Results show that a power saving of upto 51% for Addis Ababa backbone OTN and 44% for North-East backbone OTN can be achieved at maximum link utilization thresholds of 70% and 50% respectively. Link utilization constraint is used to ensure network QoS is maintained.
{"title":"Power-Aware Routing in Optical Transport Networks With Physical Layer Impairment Constraints","authors":"Y. B. Bekele, Y. Negash","doi":"10.1109/africon51333.2021.9570896","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570896","url":null,"abstract":"Due to the growth in data traffic volume and diversification of applications that use telecom network infrastructure, more power consuming telecommunication network equipments have been deployed. This scenario has led to an increase in the power consumption of the sector. In order to overcome this problem, stakeholders are striving to come up with ways to minimize this power consumption. In this work, a sleep mode operational strategy which takes the Physical Layer Impairment (PLI) and power loss/attenuation is proposed and an Integer Linear Programming (ILP) formulation is given. An implementation of the approach is carried out using GLPK optimizer and TOTEM toolbox simulation environments and results analyzed taking two Ethio Telecom backbone Optical Transport Network (OTN) segments. These optimizations & simulations help to analyze the impacts on Quality of Service (QoS) of applying this approach in addition to its main goal of power consumption minimization. Results show that a power saving of upto 51% for Addis Ababa backbone OTN and 44% for North-East backbone OTN can be achieved at maximum link utilization thresholds of 70% and 50% respectively. Link utilization constraint is used to ensure network QoS is maintained.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125854058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9571001
V. O. Nyangaresi
Sensitive and private information flows over smart home networks and it is therefore paramount that proper authentication be accomplished among the communicating entities. To achieve this, schemes based on techniques such as elliptic curve cryptography, public key cryptosystem, digital certificates, blockchains and bilinear pairing operations have been presented. However, these schemes either incur high computation and communication costs or do not consider most common attack scenarios in smart homes. In this paper, a protocol that leverages on lightweight XOR and hashing operations is developed. Security analysis using BAN logic shows that this protocol ensures secure mutual authentication among the communicating entities. It is also shown to be resilient against traceability, privacy, de-synchronization, stolen smart home device, session hijacking, man-in-the-middle, packet replay and insider attacks. In addition, it provides perfect forward key secrecy and exhibits average computation and communication overheads compared with its peers.
{"title":"Lightweight Key Agreement and Authentication Protocol for Smart Homes","authors":"V. O. Nyangaresi","doi":"10.1109/africon51333.2021.9571001","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9571001","url":null,"abstract":"Sensitive and private information flows over smart home networks and it is therefore paramount that proper authentication be accomplished among the communicating entities. To achieve this, schemes based on techniques such as elliptic curve cryptography, public key cryptosystem, digital certificates, blockchains and bilinear pairing operations have been presented. However, these schemes either incur high computation and communication costs or do not consider most common attack scenarios in smart homes. In this paper, a protocol that leverages on lightweight XOR and hashing operations is developed. Security analysis using BAN logic shows that this protocol ensures secure mutual authentication among the communicating entities. It is also shown to be resilient against traceability, privacy, de-synchronization, stolen smart home device, session hijacking, man-in-the-middle, packet replay and insider attacks. In addition, it provides perfect forward key secrecy and exhibits average computation and communication overheads compared with its peers.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124640170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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