In many urbanized and industrial areas, there exist wireless network infrastructures - usually complex, covered large public buildings (often with adjacent parking lots and green areas). In the case of emergency situations, such infrastructure could be used as a production network (dedicated for transmissions of user data) for ad-hoc created flying monitoring systems composed of one or more drones (equipped with specialized sensors and detectors, as well as high resolution camera), and corresponding air station(s). This paper proves that the existing network architecture is able to play a significant role in the casual assurance of suitable air-to-ground transmission of monitoring data. Transmissions are carried out between two WebRTC applications of IoT brokers, placed at the air station, and at the ground one. The stations are connected through the IEEE 802.11ac (Wi-Fi) local area network. During experiments, two different wireless local area networks were used. The first one was dedicated to transmissions coming from the flying monitoring system. The second one was the private network of ... University, available for the academic community. Results of experiments show that although the dedicated network better fits the needs of the flying monitoring system, the well-dimensioned public network that has a good coverage of the monitored area is able to effectively replace it in an emergency.
Authors: Agnieszka Chodorek (Kielce University of Technology), Robert Chodorek (Department of Telecommunications, The AGH University of Science and Technology), Krzysztof Wajda (AGH University of Science and Technology),
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In the typical distributed applications, the data exchange between the communicating peers proceeds along the transport path established in the connection initialization phase, even if a better one is discovered during the active session. With the recent advancement in the multipath protocol development, e.g., MPTCP, the peers can benefit from a concurrent use of a few channels, thus improving the transmission quality. However, the present approaches to the multipath transfer organization tend to neglect the energy aspects, crucial for resource-constrained Internet of Things (IoT) devices. In this paper, a framework for MPTCP module tuning, targeting the power expenditure, is developed. A new Scheduler and a new Path Manager promoting a conservative energy economy are designed by adopting a formal optimization approach. Moreover, explicit guidelines regarding the TCP variant selection are provided. As confirmed by numerous experiments involving physical devices and real networks, the proposed configuration scheme allows for several percent energy gain with respect to the default one, thus setting a solid framework for green MPTCP-based Industrial IoT communication.
Authors: Michal Morawski (Lodz University of Technology, Lodz, Poland), Przemyslaw Ignaciuk (Lodz University of Technology, Lodz, Poland),
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Since Google unveiled Android OS for smartphones, malware are thriving with 3Vs, i.e. volume, velocity and variety. A recent report indicates that one out of every five business/industry mobile application leaks sensitive personal data. Traditional signature/heuristic based malware detection systems are unable to cope up with current malware challenges and thus threaten the Android ecosystem. Therefore recently researchers have started exploring machine learning and deep learning based malware detection systems. In this paper, we performed a comprehensive feature analysis to identify the significant Android permissions and propose an efficient Android malware detection system using machine learning and deep neural network. We constructed a set of 16 permissions (8% of the total set) derived from variance threshold, auto-encoders, and principal component analysis to build a malware detection engine which consumes less train and test time without significant compromise on the model accuracy. Our experimental results show that the Android malware detection model based on the random forest classifier is most balanced and achieves the highest area under curve score of 97.7%, which is better than the current state-of-art systems. We also observed that deep neural networks attain comparable accuracy to the baseline results but with a massive computational penalty.
Authors: Hemant Rathore (BITS Pilani), Sanjay Sahay (BITS Pilani), Ritvik Rajvanshi (BITS Pilani), Mohit Sewak (BITS Pilani),
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This paper conducts research on the RF energy harvesting relay network, and proposes an improved energy harvesting relay protocol, which allows the energy harvesting source node to retransmit data to improve the system diversity gain, and constructs energy harvesting slot allocation, subcarrier pairing, and power Optimized model of distributed system energy efficiency. A resource allocation algorithm based on optimal energy efficiency is further proposed. The Dinkelbach method is used to transform the nonlinear programming problem into a linear programming problem. Then, the Hungarian algorithm and the sub-gradient method are used to obtain the iterative algorithm based on energy efficiency optimization. Simulation shows that the algorithm reduces the complexity of the algorithm and has good global convergence.
Authors: guangjun liang (Jiangsu Police Institute), jianfang xin (Anhui Polytechnic University), Qun Wang (Nanjing University of Science and Technology), lingling xia (Jiangsu Police Institute), meng li (Jiangsu Police Institute),
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IP network experts and engineers have been working on solutions for decades to promote network QoS. Latency guarantee, as one of the key aspects of network QoS, is attracting increasing attentions with requirements from time-critical applications and the vision of building a fully connected, intelligent world. Meanwhile, Network Calculus is a theory that focuses on performance bound analysis for communication networks, and has been used in avionic networks. Still, because of the extremely large scale and high complexity of IP networks, few works gave theoretically modeling and systematically analyzing for the QoS of IP networks (i.e., latency bound). In this paper, three QoS schemes for IP networks are summarized and the performance on the perspective of efficiency is analyzed. The effect of ingress shaping is also investigated, and results show that a proper ingress shaping could benefit overall network latency performance, and could be adapted to all three QoS schemes. An IP network use case is given with different QoS schemes applied and the performance is evaluated by using Network Calculus.
Authors: Lihao Chen (Huawei Technologies), Jiayi Zhang (Huawei Technologies), Tao Gao (Huawei Technologies), Tongtong Wang (Huawei Technologies),
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With the development of the Internet, the marketing model of the communications industry has transformed from a call-based to a social application-based. Analyzing information transmission of social application helped to develop marketing strategy for different customer needs. The paper proposes and constructs a two-layer communication user spreading model based on the SIR information spreading model. Then we analyze the traditional model of virus spread on the network's application, and get the simulation results of immunization strategy and the communication process of social application information on WeChat, microblog and QQ. Combining the actual data, simulation results show that the spread of the three types of social applications reaches a peak in a short time with the increase of the spread rate. The spread of WeChat application is larger than the other two types of applications on the same spread rate. Based on the acquaintance (target) immune strategy, the three types of applications have faster transmission inhibition than the random immune strategy. The research results of this paper provide an effective theoretical base for setting up individuality service combination of mobile communication enterprise.
Authors: zhenghui Li (Qinghai Normal University), yuzhi xiao (qinghai Normal University), haixiu Luo (Qinghai Normal University), chunyang Tang (Qinghai Normal University),
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Today anti-malware community is facing challenges due to ever-increasing sophistication and volume of malware attacks developed by adversaries. Traditional malware detection mechanisms are not able to cope-up against next-generation malware attacks. Therefore in this paper, we propose effective and efficient Android malware detection models based on machine learning and deep learning integrated with clustering. We performed a comprehensive study of different feature reduction, classification and clustering algorithms over various performance metrics to construct the Android malware detection models. Our experimental results show that malware detection models developed using Random Forest eclipsed deep neural network and other classifiers on the majority of performance metrics. The baseline Random Forest model without any feature reduction achieved the highest AUC of 99.4%. Also, the segregating of vector space using clustering integrated with Random Forest further boosted the AUC to 99.6% in one cluster and direct detection of Android malware in another cluster, thus reducing the curse of dimensionality. Additionally, we found that feature reduction in detection models does improve the model efficiency (training and testing time) many folds without much penalty on effectiveness of detection model.
Authors: Hemant Rathore (BITS Pilani), Sanjay Sahay (BITS Pilani), Shivin Thukral (BITS Pilani), Mohit Sewak (BITS Pilani),
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Future metro networks need to increase the transport capacity and improve the cost- and power-efficiency. These challenges are tackled by the EUH2020 PASSION project exploiting dense photonic integration and cost-efficient optical technologies. Specifically, PASSION investigates a) modular sliceable bandwidth variable transceivers (S-BVTs) built upòn a set of both vertical cavity surface emitting lasers (VCSEL) and Coherent Receivers (CO-Rx); and b) hierarchical switching nodes in a flexigrid network. An SDN controller handles the network programmability where a key functionality is the path computation and resource selection to fulfil the connection requirements. This is conducted by the Routing and Spectrum Assignment (RSA) algorithms. The considered S-BVT transmitter imposes that each S-BVT VCSEL reaches up to 50 Gb/s. Thus, connections requesting higher bandwidth (e.g., 200 Gb/s) are accommodated over several optical flows. In this context, two RSA algorithms called co-routed (RSA-CR) and inversed multiplexed (RSA-IM) optical flows are proposed and compared. The RSA-CR enforces that all the connection’s optical flows are routed over the same spatial path; the RSA-IM relaxes this allowing the optical flows being set up over different spatial routes. The experimental valuation, made upon dynamic traffic, aims at comparing both RSA algorithms performance according to the blocked bandwidth ratio, the average used of S-BVT devices, and the average setup time.
Authors: Ricardo Martinez (CTTC), Ramon Casellas (CTTC), Michela Svaluto Moreolo (CTTC), Josep Maria Fabrega (CTTC), Ricard Vilalta (CTTC), Raul Munoz (CTTC), Laia Nadal (CTTC), Juan Pedro Fernández Palacios (Telefónica I+D, GTCO), Víctor López (Telefónica I+D, GTCO), David Larrabeiti (Universidad Carlos III de Madrid), Gabriel Otero Pérez (Universidad Carlos III de Madrid),
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Several discussions regarding IoT devices and devices have been widely adopted by a notable set of Internet services driven by their capacity to cover several needs (for example, monitoring a manufacturing process, guiding an autonomous car, or tracking a train). On the other hand, Blockchain technology has been considered by several companies to support some critical functionalities, such as security provisioning or data protection. Nowadays, many challenges on both technologies remain yet unsolved, in spite of the unstoppable and ever-growing interest both technologies are attracting. Actually, a substantial push to them both comes from their agnosticism, i.e., many scenarios, particularly those considered as smart, are considered as proper candidates for their deployment, for example smart transportation, smart manufacturing or smart cities, just to name a few. This paper focuses on the latter, proposing a preliminary architecture using both technologies intended to provide security and robustness in Smart Cities. Several Blockchain strategies are analysed in the paper to identify unequivocally every device that belongs to the proposed architecture, also describing the operation of the chosen Blockchain to meet the security requirements. In summary, in this paper, an architecture able to resist certain attacks and proven to be useful to the previous mentioned examples is designed and implemented.
Authors: Martí Martínez (Universitat Politècnica de Catalunya), Eva Marín-Tordera (Universitat Politècnica de Catalunya), Xavi Masip-Bruin (Universitat Politècnica de Catalunya), Sergio Sánchez-López (Universitat Politècnica de Catalunya), Jordi García (Universitat Politècnica de Catalunya),
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Future metro networks will connect many multiaccess edge computing resources (MEC) working in a coordinating fashion to provide users with cloud computing capabilities with very low latency. That highly distributed computing architecture has to be connected by a network that provides high bandwidth and flexibility. Elastic optical networks (EONs) are currently the best option to per- form that task. In a next step of optical network evolution, EONs can increase the bandwidth that they provide by using multicore fibers (MCF). When dynamic optical circuits are established in these networks, the routing, core and spectrum assignment (RCSA) problem must be solved. In this paper, two algorithms are presented in order to solve the RCSA problem considering continuity constraints in both the spectrum and the core (as we consider a cost-effective metro network architecture based on ROADMs without line changes). One of these versions ex- plores the full spectrum of all cores in order to grant the best solution when solv- ing the RCSA problem. The results of a simulation study show that exploring all the cores when solving the RCSA problem can reduce the blocking ratio of those networks and, therefore, increase its performance at the expense of a slight incre- ment of the computing time required to provide a solution.
Authors: Iván Viloria (Universidad de Valladolid), Ramón J. Durán Barroso (Universidad de Valladolid), Ignacio de Miguel (Universidad de Valladolid), Lidia Ruiz Pérez (Universidad de Valladolid), Noemi Merayo (Universidad de Valladolid), Juan Carlos Aguado Manzano (Universidad de Valladolid), Patricia Fernández Reguero (Universidad de Valladolid), Rubén Lorenzo Toledo (Universidad de Valladolid), Evaristo J. Abril Domingo (Universidad de Valladolid),
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A review of recent Last Mile Delivery optimization proposals is presented. The proposals are classified according to the criteria of collaboration, ranging from optimization of a single route to the integration of multiple carriers. An alternative proposal is presented, based also on collaboration, but which does not involve either integration into a single organization or sharing of its resources. Each carrier is represented as a Virtual Organization of Agents (VO). A global optimizer, also a VO, oversees the search for deliveries that can be better delivered by another carrier and new routes are calculated based on a win-win approach. This approach has the advantages of being easily configurable by integrating or removing the VO of each carrier, highly distributable using a cloud infrastructure, easily scalable both for physical areas and computational resources using the cloud infrastructure in case more computational power is needed. It also allows the sharing of little information as possible among carriers, so that they only know which they deliveries are losing or gaining.
Authors: Jose Maestro (Universidad de Salamanca), Sara Rodriguez (Universidad de Salamanca), Roberto Casado (Universidad de Salamanca), Javier Prieto (Universidad de Salamanca), Juan Corchado (Universidad de Salamanca),
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The main characteristic of various emerging communication network paradigms in the dimensioning, control and deployment of future networks is the fact that they are human-centric, entailing closelyknit interactions between telematics and human activities. Considering the effect of user behavior, whose dynamics are difficult to model, new uncertainties are introduced in these systems, bringing about network resource management challenges. Within this context, this study seeks to review different decision-making computational methods in conditions of uncertainty for Internet of Things scenarios such as smart spaces,and industry 4.0, through a systematic literature review. According to our research results, a new paradigm for computationally capturing and modeling human behavior context must be developed with the purpose of improving resource management.
Authors: Germán Santos-Boada (Universitat Politècnica de Catalunya (UPC), Barcelona (Spain)), Néstor Alzate-Mejía (Cooperative University of Colombia, Santiago de Cali, Colombia), José Roberto Amazonas (Escola Politécnica of the University of São Paulo, SP, Brazil),
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The increasing demand of data and real-time analysis has given rise to edge computing, providing benefits such as low latency, efficient bandwidth us- age, fine-grained location tracking, or task offloading. Edge computing based on containers brings additional benefits, facilitating the development and deploy- ment of scalable applications adapting to changing market demands. But in order to enable edge computing in the telco industry, it is important that current stand- ardization efforts are followed by software platforms implementing those stand- ards. This paper proposes an approach to the design and implementation of an edge computing platform based on Kubernetes and Helm providing functional blocks and APIs as defined by ETSI in the Multi-Access Edge Computing (MEC) reference architecture. Although this proposal is still at a work-in-progress state, this paper describes the design and implementation of an open-source proof-of- concept scenario focusing on the lifecycle management of cloud native MEC ap- plications. The resulting prototype shows the feasibility of this approach, that can be adequate to create a lightweight MEC demonstration platform for university laboratories and experimentation.
Authors: Ignacio D. Martinez-Casanueva (Universidad Politecnica de Madrid), Luis Bellido (Universidad Politecnica de Madrid), Carlos M. Lentisco (Universidad Politecnica de Madrid), David Fernandez (Universidad Politecnica de Madrid),
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