Vol. 75, n° 7-8, July-August 2020
Content available on Springerlink
Nathalie Mitton, Inria, Lille, France
Luís Henrique M. K. Costa, Poli/COPPE, Universidade Federal do Rio de Janeiro, Rio de
Bhaskar Krishnamachari, University of South California, Los Angeles, CA, USA
Tommaso Pecorella, University of Florence, Florence, Italy
Mohit Tahiliani, National Institute of Technology Karnataka, Mangalore, India
Green data collection and processing in smart cities
Nathalie Mitton, Luís Henrique M. K. Costa, Bhaskar Krishnamachari, Tommaso Pecorella, Mohit Tahiliani, Nicolas Puech
Comparison of energy simulation applications used in green building
Amin H. Al Ka’bi1
(1) Australian College of Kuwait, Kuwait City, Kuwait
Abstract The main goal of green building is to provide comfortable life for its residents, while encountering the negative impacts on the surrounding environment. This goal can be achieved by applying effective methodologies throughout the entire life cycle of the building and maintaining an efficient usage of the available energy resources. As part of “building information modeling (BIM),” there are numerous software simulation applications that can be used for analyzing, and modeling energy consumption in all stages of green building, starting from the initial stages of planning and design, up to the final stages of operation and maintenance. In this research work, we conduct a thorough investigation, analysis, and comparison of the performance of most common software applications used for simulating and modeling the energy consumption in green building, and subsequently, the best application is recognized based on unified selection criteria, which include various sets of design parameters and operating conditions.
Keywords Software applications . Energy efficiency . Green building . Smart building . Energy simulation
M/M/1model of Energy-Efficient Ethernet with byte-based
Nataša Maksić1, Milan Bjelica1
(1) School of Electrical Engineering, University of Belgrade, Bul. Kralja Aleksandra 73, Belgrade 11000, Serbia
Abstract Communication networks have been recognized as substantial energy consumer. However, the ubiquity of Ethernet links provides opportunity for energy savings with Energy-Efficient Ethernet standard and packet coalescing. So far, theoretical analysis of coalescing algorithms for Energy-Efficient Ethernet has assumed that the coalescing limit is expressed in packets; however, as Ethernet links are byte-congestible resources in nature, we argue that byte-based coalescing algorithms should be employed. To that goal, we propose an M/M/1 model for byte-based coalescing on Ethernet links compliant to Energy-Efficient Ethernet standard. The model is based on compound Poisson distribution and provides single formula for calculation of expected low-power state duration and, in turn, of energy savings. The model is applicable to 10GBASET Ethernet and to emerging 2.5GBASE-T and 5GBASE-T standards. Detailed simulation results show a good match of achieved energy savings to those predicted by the model. The paper discusses application of the proposed model for the evaluation of energy efficiency of 10GBASE-T Ethernet links in future IoT data centers within Smart Cities.
Keywords Energy-Efficient Ethernet · Packet coalescing · Compound Poisson distribution · Queuing theory · Internet of Things · Data center · Smart City
An anonymous and identity-trackable data transmission scheme for smart grid under smart city notion
Fan Wu1 · Xiong Li2,3 · Lili Xu4 · Saru Kumari5 · Dingbao Lin1 · Joel J. P. C. Rodrigues6,7
(1) Department of Computer Science and Engineering, Xiamen Institute of Technology, Xiamen, China
(2) Center for Cyber Security, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
(3) School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China
(4) School of Informatics, Xiamen University, China
(5) Department of Mathematics, Chaudhary Charan, Singh University, Meerut, India
(6) Federal University of Piauı, Teresina, PI, Brazil
(7) Instituto de Telecomunicações, Covilhã, Portugal
Abstract In addition to changing service management, smart devices connect people and objects around them and collect data from them on and on, in order to construct the notion of a smart city. Such data produced by embedded devices and automatically transmitted over the Internet provides people with the information to make decisions. A smart grid is one of the most popular applications for a smart city. Due to the insecurity of the wireless channels, the security of data transmission in a smart grid has become a hot issue nowadays. Many schemes for data protection have been proposed, but weaknesses exist generally. We present a new data transmission scheme for a smart grid among the smart meter (SM), the electricity utility (EU), and the trusted authority (TA). The EU can obtain the power consumption of each SM, but cannot get the real identity of the SM. To keep the privacy of the user, if the consumption value is over the threshold in special time span or identity of SM is required for public affairs, TA could track the identity in time. Formal proof with random oracle model and security analysis are expressed to show the security of the proposed scheme. Via the performance and network simulation, it is easy to see that our scheme is practical for a smart city.
Keywords Keywords Traceability · Smart grid · Random oracle · ns-3 · Smart meter
Density-connected cluster-based routing protocol in vehicular ad hoc networks
Anant Ram1, Manas Kumar Mishra2
(1) Department of Computer Engineering and Applications, GLA, University Mathura, Mathura, India
(2) School of Computing Science and Engineering, VIT Bhopal University, Bhopal, India
Abstract With the development of Vehicular ad hoc networks (VANETs), intelligent transportation system is gaining more attention for providing many services. However, mobility characteristic of VANETs causes frequent route disconnection, particularly during the data delivery. Clustering is one ofmost efficient approaches to achieve stable structure of topology. The real-time applications need the data transmission delay time to be relatively stable. In position based routing with sufficient density in the neighborhood can achieve the above objective easily. In this work, we propose density-connected cluster-based routing (DCCR) protocol, a position based density adaptive clustering oriented routing protocol. The approach maintains the connectivity between two successive forwarders by considering different matrices like density and standard deviation of average relative velocity. The proposed protocol demonstrates improvement in the packet delivery ratio, end-to-end delay compared with existing approaches.
Keywords Cluster head . Best fit forwarder . Clustermember . Gateways member .VANETs
A study of the LoRa signal propagation in forest, urban,
and suburban environments
Ana Elisa Ferreira1,2, Fernando M. Ortiz1, Luıs Henrique M. K. Costa1, Brandon Foubert3, Ibrahim Amadou3, Nathalie Mitton3
(1) Federal University of Rio de Janeiro – GTA/PEE/COPPE, Rio de Janeiro, Brazil
(2) Federal Technology Education Center Celso Suckow da Fonseca – UneDPetrópolis/CEFET-RJ, Petrópolis, Brazil
(3) Inria, Lille, France
Abstract Sensing is an activity of paramount importance for smart cities. The coverage of large areas based on reduced infrastructure and low energy consumption is desirable. In this context, Low Power Wide Area Network (LPWAN) plays an important role. In this paper, we investigate LoRa, a low-power technology offering large coverage, but low transmission rates. Radio range and data rate are tunable by using different spreading factors and coding rates, which are configuration parameters of the LoRa physical layer. LoRa can cover large areas but variations in the environment affect link quality. This work studies the propagation of LoRa signals in forest, urban, and suburban vehicular environments. Besides being environments with variable propagation conditions, we evaluate scenarios with node mobility. To characterize the communication link, we mainly use the Received Signal Strength Indicator (RSSI), Signal to Noise Ratio (SNR), and Packet Delivery Ratio (PDR). As for node mobility, speeds are chosen according to prospective applications. Our results show that the link reaches up to 250 m in the forest scenario, while in the vehicular scenario it reaches up to 2 km. In contrast, in scenarios with high-density buildings and human activity, the maximum range of the link reaches up to 200 m in the urban scenario.
Keywords Smart cities · Low power wide area networks · Wireless sensor networks · LoRa technology
Performance analysis of DRXmechanism using batch arrival vacation queueing system withN-policy in LTE-A networks
Anupam Gautam1, Gautam Choudhury2, S. Dharmaraja1
(1) Department of Mathematics, Indian Institute of Technology Delhi, Hauzkhas, Delhi, India
(2) Mathematical Sciences Division Institute of Advanced Study in Science and Technology, Paschim Boragaon, Guwahati, Assam, India
Abstract Power saving and Quality of Service (QoS) are the two significant aspects of Long Term Evolution-Advanced (LTE-A)networks. DRX (“Discontinuous Reception”) is a mechanism, commonly exercised to enhance the power saving competency of a User Equipment (UE) in LTE-A net works. In this paper, based on the kind of traffic running at the UE, a new appliance is proposed to switch the DRX mechanism from the power active state to the power saving state and vice versa. We mathematically investigate this switching technique in DRX mechanism using the M[X]/G/1 vacation queue system with N-policy. Various performance and energy metrics are obtained and examined numerically. Further, the optimal value of N as well as the maximum number of DRX cycles, are computed to obtain the minimal amount of power consumption. This study concludes the selection guidelines for choosing the optimal values of N and the maximum number of DRX cycles.
Keywords LTE -A networks · DRX mechanism · M[X]/G/1 vacation queueing system · Power saving · Delay
Lightweight deep network for traffic sign classification
Jianming Zhang1,2, Wei Wang1,2, Chaoquan Lu1,2, Jin Wang1,2, Arun Kumar Sangaiah3
(1) School of Computer and Communication Engineering, Changsha, University of Science and Technology, Changsha, Hunan Province, China
(2) Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, Changsha University of Science and Technology, Changsha, China
(3) School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Abstract Deeper neural networks have achieved great results in the field of computer vision and have been successfully applied to tasks such as traffic sign recognition. However, as traffic sign recognition systems are often deployed in resource-constrained environments, it is critical for the network design to be slim and accurate in these instances. Accordingly, in this paper, we propose two novel lightweight networks that can obtain higher recognition precision while preserving less trainable parameters in the models. Knowledge distillation transfers the knowledge in a trained model, called the teacher network, to a smaller model, called the student network. Moreover, to improve the accuracy of traffic sign recognition, we also implement a new module in our teacher network that combines two streams of feature channels with dense connectivity. To enable easy deployment on mobile devices, our student network is a simple end-to-end architecture containing five convolutional layers and a fully connected layer. Furthermore, by referring to the values of batch normalization (BN) scaling factors towards zero to identify insignificant channels, we prune redundant channels from the student network, yielding a compact model with accuracy comparable to that of more complex models. Our teacher network exhibited an accuracy rate of 93.16% when trained and tested on the CIFAR-10 general dataset. Using the knowledge of our teacher network, we train the student network on the GTSRB and BTSC traffic sign datasets. Thus, our student model uses only 0.8 million parameters while still achieving accuracy of 99.61% and 99.13% respectively on both datasets. All experimental results show that our lightweight networks can be useful when deploying deep convolutional neural networks (CNNs) on mobile embedded devices.
Keywords Convolutional neural networks . Traffic sign classification . Knowledge distillation . Network pruning
Bit error probability analysis of IR-UWB ED-OOK system
using cooperative dual-hop DTF strategy
Ranjay Hazra1, Anshul Tyagi2
(1) NIT Silchar, Silchar, Assam, India
(2) IIT Roorkee, Roorkee, India
Abstract The Bit Error Rate (BER) of a single user cooperative Impulse Radio (IR)-Ultrawideband (UWB) communication system employing Energy Detector (ED) receiver with On-Off Keying (OOK) in IEEE 802.15.4a UWB multipath environment is investigated in this paper. Analytical evaluation based on Energy detection principle is performed to derive approximate BER Expressions for various diversity combining cases, namely optimum combining, linear combining and selective combining using cooperative dual-hop Detect and Forward (DTF) relay protocol in presence and absence of Inter-symbol interference (ISI). Numerical results reveal that there is a significant improvement in BER, with increase in number of relay diversity paths and decrease in number of frames Nf . The accuracy and perfection in approximation used in investigation of BER is confirmed with the validation of the analytical BER expressions with that of the simulation results. The analytical and simulation results confirm that among the diversity combining schemes, the performance of optimum combining is better compared with linear combining, which in turn performs better than selective combining.
Keywords Energy Detector (ED) · Bit Error Rate (BER) · Detect and Forward (DTF) · Cooperative · Dual-hop and diversity combining
Secrecy capacity analysis of untrusted relaying energy-harvesting systems with hardware impairments
Van Phu Tuan1, Hyung Yun Kong2
(1) Department of Information & Communication Engineering, Kongju National University, Cheonan, South Korea
(2) Department of Electrical Engineering, University of Ulsan, Ulsan, South Korea
Abstract In this paper, we study the impact of hardware impairments, which can act as one of the factors that cause degradation in the performance of communication systems, on the secrecy capacity of an untrusted relaying wireless energy-harvesting (WEH) system. In the system, the energy-constrained relay is an untrusted node which can overhear the source’s confidential signal while assisting the source-destination communication. The relay operates in the amplify-and-forward (AF) mode and uses the power-splitting (PS) protocol for harvesting energy. The destination sends an artificial noise (AN) signal during the source-relay communication. The AN signal acts as an additional energy source and an interference source at the relay. In our study, we derive an approximation of the average secrecy capacity (ASC) for the high-power-regime approximation in order to evaluate the secrecy performance of the proposed system, which is also the upper bound for the ASC. The analytical results are confirmed via Monte Carlo simulations. The numerical results provide valuable insights into the effect of the various system parameters, such as the power-splitting ratio, the relay’s location, the trade-off between the source’s power and the destination’s power, and the level of hardware impairments, on the secrecy performance.
Keywords Energy harvesting · Power-splitting architecture · Untrusted relay · Amplify-and-forward · Hardware impairments · Physical layer security
Performance analysis of secondary users under heterogeneous licensed spectrum environment in cognitive radio ad hoc networks
Anand Jee1, Shanidul Hoque2, Wasim Arif3
(1) Department of Electrical Engineering, Indian Institute of Technology Delhi, Delhi, India
(2) Department of Electronics and Communication Engineering, Madanapalle Institute of Technology & Science, Madanapalle, India
(3) Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar, India
Abstract Cognitive radio (CR) is a hopeful technology to sort out spectrumscarcity and underutilization problemin ad hoc networks.With the help of cognitive radio technology, unlicensed users can efficiently utilize the unused part of heterogeneous licensed spectrum. In this article, we present a three-dimensional (3D) Markov chain analysis for spectrum management scheme under heterogeneous licensed bands of two different licensed spectrum pools in cognitive radio ad hoc networks. We present the concept of interpool and intrapool spectrum handoff in the proposed model and derive blocking probability, dropping probability, non-completion probability, and throughput to estimate the performance of the secondary users under heterogeneous licensed spectrum environment. The impact of secondary users dynamic along with the primary users’ activity model on the performance measuring metrics in terms of blocking probability, dropping probability, non-completion probability, and throughput for three different cases is also investigated. The proposed model offers significant improvement in the performance of secondary users under heterogeneous licensed spectrum environment in a CR ad hoc network.
Keywords Adhoc network . Cognitive radio . 3DMarkovchain . Heterogeneous spectrumenvironment . Performance evaluation
An ontology supported hybrid approach for recommendation in emergency situations
Sonia Mehla1, Sarika Jain1
(1) Department of Computer Applications, National Institute of Technology, Kurukshetra, Haryana, India
Abstract Large-scale disasters pose significant response challenges for all governmental organizations and the general public. Several difficulties usually occur during the response efforts, making it important for the authorities to take timely key decisions to mitigate and recover from disastrous or emergency situations. We herein present an ontology-supported hybrid reasoning model by integrating case-based reasoning and rule-based reasoning with implementation support for decision-makers to effectively respond in case of emergencies. We also introduce a new hierarchically organized semantic knowledge representation model to represent the case base structure that enhances case-based reasoning to knowledge-intensive case-based reasoning. In addition, we obtain experimental results on the analysis of the proposed approach in terms of the efficiency of the decision support system. Hence, it seems reasonable to merge the advantages of both approaches using a hybrid model of knowledge representation. The model output presents an estimation of the number of resources to be deployed if an emergency occurs. The proposed approaches for both the knowledge representation structure and the inference algorithm have proved to improve the accuracy of recommendation in emergencies. The results show that our hybrid systemapproach is efficient in decision support. The ontology-supported hybrid reasoning approach is also further validated using subjective evaluation.
Keywords Decision support system . Ontology . Rule based reasoning . Case based reasoning . Emergency situations . Hybrid reasoning
FDTD propagation of VLF-LF waves in the presence of ions
in the earth-ionosphere waveguide
(1) Visitor at School of Electrical and Electronic Engineering, The University of Manchester, UK
Abstract The finite-difference time-domain (FDTD) method has been used for a long time to compute the propagation of very low frequency (VLF) and low frequency (LF) radio waves in the Earth-Ionosphere waveguide. In previously published FDTD schemes, only the electronic density of the ionosphere was accounted for, since in usual natural conditions the effect of the ion density can be neglected. In the present paper, the FDTD scheme is extended to the casewhere one or several ion species must be accounted for, which may occur in special natural conditions or in such artificial conditions as after high altitude nuclear bursts. The conditions that must hold for the effect of the ions not to be negligible are discussed, the FDTD scheme with ions is derived, and numerical experiments are provided to show that the effect of the ions may be significant when the ionosphere is disturbed by incident flows of γ or β rays.
Keywords Numerical method . Finite-difference . FDTD . VLF . LF . Propagation . Communication
Moments of the quadrivariate Rayleigh distribution
with applications for diversity receivers
Mustafa Tekinay1, Cory Beard1
(1) University of Missouri – Kansas City, Kansas City, MO, 64110, USA
Abstract Wireless channels exhibit time, frequency, and spatial correlation. Models in literature that study four-branch diversity receivers make assumptions such as independence, constant correlation, exponential correlation, or some other kind between received signals at each antenna. However, these models are not accurate in many scenarios. Addressing this issue, we provide novel results for the moments, moment-generating function, probability density function, and cumulative distribution function of the quadrivariate Rayleigh distribution with an arbitrary correlation model. To the best of our knowledge, our model is the most comprehensive and the only one that can incorporate the 3GPP suggested spatial correlation structure. We use our new results to derive an analytical expression for the moments of the output signal-tonoise ratio of the four-branch equal gain combining receiver and the four-branch maximal ratio combining receiver. We provide original insight about their output signal-to-noise ratio distributions through their higher order moments in different scenarios. Our expressions are valid for all moments.
Keywords Quadrivariate Rayleigh distribution · Multivariate Gaussian distribution · Correlated random variables · Diversity · Moment-generating function · Joint moments
A prototype filter design based on channel
estimation for OQAM/OFDM systems
Yongjin Liu1, Xihong Chen1
(1) Air and Missile Defense College, Air Force Engineering University, Xi’an 710051, China
Abstract A prototype filter design for offset quadrature amplitude–modulation based orthogonal frequency division multiplexing (OQAM/OFDM) systems is proposed in this study. The influence of channel estimation is considered, with the object to minimize stop-band energy. An efficient preamble structure is proposed to improve the channel estimation and save the frequency spectral efficiency. The reciprocal of the signal-to-interference-plus-noise ratio (RSINR) is derived to measure the influence of the prototype for channel estimation. After that, the problem of prototype filter design is formulated as an optimization problem with constraints on the RSINR. To accelerate the convergence and obtain a global optimal solution, the box-based branch and bound algorithm is utilized to solve the optimization problem. Simulation results demonstrate the validity and efficiency of the prototype filter designed in this study.
Keywords Channel estimation . 5G communication . Box-BB
Scalable kernel convex hull online support vector machine
for intelligent network traffic classification
Xiaoqing Gu1, Tongguang Ni1, Yiqing Fan2, Weibo Wang3
(1) School of Information Science and Engineering, Changzhou University, Changzhou, China
(2) Viterbi School of Engineering, University of Southern California, Los Angeles, USA
(3) School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Abstract Online support vector machine (SVM) is an effective learning method in real-time network traffic classification tasks. However, due to its geometric characteristics, the traditional online SVMs are sensitive to noise and class imbalance. In this paper, a scalable kernel convex hull online SVMcalled SKCHO-SVM is proposed to solve this problem. SKCHO-SVM involves two stages: (1) offline leaning stage, in which the noise points are deleted and initial pin-SVM classifier is built; (2) online updating stage, in which the classifier is updated with newly arrived data points, while carrying out the classification task. The noise deleting strategy and pinball loss function ensure SKCHO-SVMinsensitive to noise data flows. Based on the scalable kernel convex hull, a small amount of convex hull vertices are dynamically selected as the training data points in each class, and the obtained scalable kernel convex hull can relieve class imbalance. Theoretical analysis and numerical experiments show that SKCHO-SVM has the distinctive ability of training time and classification performance.
Keywords Online learning . Support vectormachine . Scalable kernel convex hull . Network traffic classification
Correction to: MineCap: super incremental learning for detecting and blocking cryptocurrency mining on software-defined networking
Helio N. Cunha Neto1, Martin Andreoni Lopez2, Natalia C. Fernandes1, Diogo M. F. Mattos1
(1) Midiacom/PPGEET/TET, Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil
(2) Samsung Research Institute, Campinas, SP, Brazil
Correction to: Optical wireless multiple-input multiple-output system based on avalanche photodiode receiver
Hao Du1, Guoning Xu1
(1) Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China