Communication Service Networks Research Articles

Digital Battle: A Three-Layer Distributed Simulation Architecture for Heterogeneous Robot System Collaboration

In this paper, we propose a three-layer distributed simulation network architecture, which consists of a distributed virtual simulation network, a perception and control subnetwork, and a cooperative communication service network. The simulation architecture runs on a distributed platform, which can provide unique virtual scenarios and multiple simulation services for the verification of basic perception, control, and planning algorithms of a single-robot system and can verify the distributed collaboration algorithms of heterogeneous multirobot systems. Further, we design simulation experimental scenarios for classic heterogeneous robotic systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). Through the analysis of experimental measurement data, we draw several important conclusions: firstly, the replication time characteristics and update frequency characteristics of entity synchronization in our system indicate that the replication time of entity synchronization in our system is relatively short, and the update frequency can meet the needs of multirobot collaboration and ensure the real-time use and accuracy of the system; secondly, we analyze the bandwidth usage of data frames in the whole session and observe that the server side occupies almost half of the data throughput during the whole session, which indicates that the allocation and utilization of data transmission in our system is reasonable; and finally, we construct a bandwidth estimation surface model to estimate the bandwidth requirements of the current model when scaling the server-side scale and synchronization-state scale, which provides an important reference for better planning and optimizing of the resource allocation and performance of the system. Based on this distributed simulation framework, future research will improve the key technical details, including further refining the coupling object dynamic model update method to support the simulation theory of the coupling relationship between system objects, studying the impact of spatiotemporal consistency of distributed systems on multirobot control and decision making, and in-depth research on the impact of collaborative frameworks combined with multirobot systems for specific tasks.

Robust Beamforming for Downlink Multi-Cell Systems: A Bilevel Optimization Perspective

Utilization of inter-base station cooperation for information processing has shown great potential in enhancing the overall quality of communication services (QoS) in wireless communication networks. Nevertheless, such cooperations require the knowledge of channel state information (CSI) at base stations (BSs), which is assumed to be perfectly known. However, CSI errors are inevitable in practice which necessitates beamforming technique that can achieve robust performance in the presence of channel estimation errors. Existing approaches relax the robust beamforming design problems into semidefinite programming (SDP), which can only achieve a solution that is far from being optimal. To this end, this paper views robust beamforming design problems from a bilevel optimization perspective. In particular, we focus on maximizing the worst-case weighted sum-rate (WSR) in the downlink multi-cell multi-user multiple-input single-output (MISO) system considering bounded CSI errors. We first reformulate this problem into a bilevel optimization problem and then develop an efficient algorithm based on the cutting plane method. A distributed optimization algorithm has also been developed to facilitate the parallel processing in practical settings. Numerical results are provided to confirm the effectiveness of the proposed algorithm in terms of performance and complexity, particularly in the presence of CSI uncertainties.

FedRDR: Federated Reinforcement Distillation-Based Routing Algorithm in UAV-Assisted Networks for Communication Infrastructure Failures

Traditional Internet of Things (IoT) networks have limited coverage and may experience failures due to natural disasters affecting critical IoT devices, making it difficult for them to provide communication services. Therefore, how to establish network communication service more efficiently in the presence of fault points is the problem we solve in this paper. To address this issue, this study constructs a hierarchical multi-domain data transmission architecture for an emergency network with unmanned aerial vehicles (UAVs) employed as core communication devices. This architecture expands the functionality of UAVs as key network devices and provides a theoretical basis for their feasibility as intelligent network controllers and switches. Firstly, the UAV controllers perceive the network status and learn the spatio-temporal characteristics of air-to-ground network links. Secondly, a routing algorithm within the domain based on federated reinforcement distillation (FedRDR) is developed, which enhances the generalization capability of the routing decision model by increasing the training data samples. Simulation experiments are conducted, and the results show that the average communication data size between each domain controller and the server is approximately 45.3 KB when using the FedRDR algorithm. Compared to the transmission of parameters through federated reinforcement learning algorithms, FedRDR reduces the transmitted parameter size by approximately 29%. Therefore, the FedRDR routing algorithm helps to facilitate knowledge transfer, accelerate the training process of intelligent agents within the domain, and reduce communication costs in resource-constrained scenarios for UAV networks and has practical value.

Energy-efficient secure dynamic service migration for edge-based 3-D networks

AbstractIn communication networks, where users are highly mobile, migrating edge servers that are performing services closer to users, i.e., service migration, is essential to maintain the high quality of service (QoS). However, existing dynamic service migration techniques face two distinct challenges: (1) The security and energy consumption of service migration systems need to be optimised urgently; (2) The uncertainty of user movement makes it difficult to develop optimal service migration strategies, especially in future three-dimensional (3-D) communication networks. To address these challenges, we propose a novel energy-efficient secure 3-D dynamic service migration framework for communication networks. We then quantify the cost of service migration based on the proposed framework considering security, energy efficiency and delay and present a solution based on a deep reinforcement learning (DRL) approach to make migration decisions optimally in the 3-D communication network. We also propose a universal formula for measuring the reliability value of intelligent autonomous nodes in order to reduce the energy consumption and delay of the proposed security paradigm and to optimise the service migration decision making. Simulation results demonstrate our proposed migration strategy for 3-D communication network services outperforms the baseline solutions in terms of reducing communication network delay and energy consumption while preserving migration security. Moreover, the results confirm the effectiveness of the proposed reliability value calculation approach applied to improve the QoS in the secured edge networks.

Method of operating assessment of the state of network elements to ensure the quality of services in corporate high­speed multiservice communication networks

The article proposes intelligent methods and algorithms for operational assessment of the state of network elements to ensure indicators of the quality of communication services in corporate multi-service communication networks that function in a mode close to real time. A feature of corporate multi-service networks is the high dynamics of changes in their state. And the task of the automated network management system is to ensure the given quality of communication services. Thus, the relevance of this study is determined by the need to implement network management processes in a mode close to real time, with a given quality. The basis of the method of operational assessment of the state of network elements is the concept of using intelligent agents. In the proposed approach, intelligent agents are created as hierarchical fuzzy situational networks, in which management decisions, in contrast to known methods based on the application of reference situations, are produced on the basis of solving a hierarchical system of optimization tasks based on fuzzy mathematical programming methods. The main paradigm of their functioning is «situation – action». This makes it possible to significantly reduce the dimension of the task to be solved and obtain Pareto-optimal solutions for managing the quality of communication services. The intelligent agent of management solutions can be implemented automatically, provided that the network administrator delegates such capabilities to it. The method of estimating traffic parameters is based on the concept of conditional nonlinear Pareto-optimal filtering. Its essence is to apply a two-stage procedure; at the first stage, a forecast of the values of parameter estimates is made, but in the second, with the receipt of the following observations, their values are adjusted. The average relative error of traffic parameter estimation does not exceed 10%, which is sufficiently operational for managing the quality of communication services.

Research of protocols and technologies data transmissions in IoT networks

Important functions of the concept of the Internet of Things are the facilitation of everyday life, improvement of efficiency and quality of work, energy saving, etc. More and more often, data from "things" are transferred to the public communication network and cloud services. Any objects in the physical world that can be assigned IP addresses and are capable of transmitting data can act as "things" in such a network. Various technologies and protocols are used for data transmission, of which there are currently more than twenty. In the near future, a large number of devices will be connected to the Internet of Things. Most of these devices will run on batteries. At the same time, one of the main characteristics is the duration of equipment operation without human intervention. In order to solve this problem, new networks were created specifically for the Internet of Things. These networks are called LPWANs. At the same time, one of the key issues is the optimal selection of the method of information transfer between nodes in the Internet of Things concept. After conducting an analysis of open sources, it is possible to conclude about the prospects of using the following technologies for these purposes: NB-IoT, Weightless, LoRa, SigFox. The subject of research in the article is long-distance data transmission technologies and protocols used to send information from a sensor to a cloud service in the context of the Internet of Things. The purpose of the study is to review and compare the main technologies and protocols for long-distance data transmission in Internet of Things networks. A comparative analysis of the main characteristics of long-distance data transmission protocols and technologies of the LPWAN network was carried out: NB-IoT, Weightless, LoRa, SigFox. The results of the analysis are presented in the form of a table. Experimental results have shown that the effectiveness of the considered protocols and technologies depends on various conditions of the communication network. In this regard, currently the choice of protocols for devices depending on operating conditions helps to solve the problem of saving resources, both energy consumption and guaranteed delivery. This is especially relevant in connection with the spread of the Internet of Things technology and the increase in the total number of "things".

Implementation of Mobile Ad-Hoc Network Using BATMAN Routing Protocol (Better Approach To Mobile Ad-hoc Network) for Salinity Monitoring in Vaname Shrimp Farms

Salinity is the key parameters in the shrimp culture environment. Conventional method is by visiting each pond plot. But,due to the large number and distance between the plots, this method is less effective. This ineffectiveness can lead to less than optimal yields. Manet is applied to increase the effectiveness of checking salinity using the BATMAN routing protocol. In this study, 2 units of laptops were used that act as Node 1 and Node 4, 2 units of Orange Pi Zero as Node 2, and 3. Each device is connected to a conductivity sensor to measure the salinity. The four devices are configured with an adhoc network using the BATMAN routing protocol. This research was conducted to provide an alternative for monitoring salinity to make it more effective. Based on the results of testing and analysis of network quality, the average delay value is 22.285 ms. The low delay value affects the percentage of packet loss in the four test scenarios with an average percentage of 0.999759613 %. Memory and CPU usage in testing 4 transition scenarios resulted in an average memory usage of 0.225% and CPU usage of 0.725%. The BATMAN routing protocol does not use a lot of memory and CPU usage because it only forwards data packets without the need to process data. From these data, it can be concluded that manet with batman routing protocol can be used as an alternative communication to provide communication network services in areas where there is no fixed network infrastructure.

THE INFLUENCE OF RLAH ON THE BUSINESS OF TELECOM OPERATORS ON THE MARKET OF BOSNIA AND HERZEGOVINA

In the era of general globalization and transition, the accession of Bosnia and Herzegovina to the European Union is considered as a strategic priority. The integration of Bosnia and Herzegovina (hereinafter BiH) into the European Union (hereinafter EU) is a very significant process that requires fundamental changes in society, and therefore the inclusion and full engagement of all social and especially economic subjects in BiH is necessary.Bosnia and Herzegovina has always belonged to the European political, cultural, and economic area. The process of European integration requires a comprehensive adjustment of policies, institutional framework and legal system with the aim of reaching European standards in all areas. The process of legal harmonization and acceptance of European standards implies extensive internal reforms, general consolidation of the system, stronger economic development and more intensive foreign policy activities in areas that affect the dynamics of relations between BiH and the EU. The prospect of membership in the EU is an extremely strong incentive for the continuation of already started reforms in BiH and the initiator of the process that should enable the creation of an economic, legal, organizational and social structure capable of operating in accordance with EU rules. Ensuring non-discriminatory access to telecommunications services and their high quality at affordable prices form one of the bases of the policy of developing BiH society and protecting the interests of BiH citizens. Global measures for the implementation of such a policy are: liberalization of the telecommunications market, encouragement of the development of the telecommunications sector and ensuring effective control measures with the aim of protecting users’ rights and reducing barriers to the entry of new operators.The subject of the research in this paper is the assessment of the impact of the current EU Roaming Regulation on the telecommunications market of BiH, that is, the business income of telecom operators from mobile telephony services, as well as the user experience related to the use of services in roaming. The basic question that arises is: How do companies operating in the field of telecommunications adapt their prices and business conditions to the EU requirements? What are the experiences of applying these provisions in EU countries? Can some measures be taken in the context of maintaining business and how to communicate with the users who are directly affected by the mentioned changes, in a positive context? The aim of the research is to assess the effect of the implementation of the Decision of the Regulatory Agency for Communications of BiH (hereinafter referred to as the Agency) on the prices of roaming services in public mobile communication networks, which stipulates the obligation to determine the maximum prices for roaming services and the termination of regulated roaming calls in public mobile communication networks.

LONG OVERDUE ADDITIONS TO THE LICENSING RULES FOR INTERNET SERVICES THAT MAKE VOICE CALLS TO THE PSTN NETWORK

Появление и активное развитие интернет-сервисов в современных сетях связи предопределено как востребован­ностью таких услуг широким кругом пользователей, так и необходимостью экономного отношения к дорогостоящей телеком­муникационной инфраструктуре. Как и любое новое направление, эти технологические решения опережают их нормативное регулирование. На стадии становления такое естественное утверждение новых прогрессивных технологий дало импульс про­рывным достижениям. Однако в процессе масштабного развития отставание нормативного регулирования начинает создавать серьезные проблемы для самих технологий и для безопасности их пользователей. Отсутствие в современной нормативной базе целого ряда определений или допустимость их неоднозначной трактовки становится все менее приемлемым для эффективной работы отрасли связи. В статье анализируются возможные конкретные законодательные и нормотворческие инициативы и их последствия для поэтапного приведения нормативной базы в соответствие с новыми требованиями. The emergence and active development of Internet services in modern communication networks is predetermined both by the demand for such services by a wide range of users and by the need for an thrifty attitude to expensive telecommunications infrastructure. Like any new direction, these technological solutions are ahead of their regulatory regulation. At the nascent stage such a natural approval of new progressive technologies gave impetus to breakthrough achievements. However, in the process of large-scale development the regulatory backlog begins to create serious problems for the technologies themselves and for the safety of their users. The absence of a number of definitions in the modern regulatory framework, or the permissibility of their ambiguous interpretation, is becoming less and less acceptable for the effective operation of the communications industry. The article analyzes possible specific legislative and rule-making initiatives and their consequences for bringing the regulatory framework in line with the new requirements.

APPLICATION OF E-LEARNING AS A LEARNING MEDIUM FOR INFORMATION TECHNOLOGY

With advances in internet network technology, information and communication services are no longer constrained by time and place constraints. Online learning emphasizes distance learning to provide the best educational process possible. Online learning is a type of information technology advancement that can be used as a teaching aid. In this work, the authors use descriptive research techniques to conduct a more in-depth analysis of the theories and trends in advances in online learning. The University of Illinois at Urbana-Champaign is a pioneer in the development of online education. In a computer-based education system, the University of Illinois has started e-learning by utilizing a computer called PLATO. The e-learning classroom learning model is a significant development in the teaching and learning process because it can reduce variations in teaching strategies and course materials and increase the consistency of learning. To prepare, with the help of technology, when everything shifts to the digital era, both in terms of methods and content, online learning systems are very important.

Knowledge-Driven Location Privacy Preserving Scheme for Location-Based Social Networks

Location privacy-preserving methods for location-based services in mobile communication networks have received great attention. Traditional location privacy-preserving methods mostly focus on the researches of location data analysis in geographical space. However, there is a lack of studies on location privacy preservation by considering the personalized features of users. In this paper, we present a Knowledge-Driven Location Privacy Preserving (KD-LPP) scheme, in order to mine user preferences and provide customized location privacy protection for users. Firstly, the UBPG algorithm is proposed to mine the basic portrait. User familiarity and user curiosity are modelled to generate psychological portrait. Then, the location transfer matrix based on the user portrait is built to transfer the real location to an anonymous location. In order to achieve customized privacy protection, the amount of privacy is modelled to quantize the demand of privacy protection of target user. Finally, experimental evaluation on two real datasets illustrates that our KD-LPP scheme can not only protect user privacy, but also achieve better accuracy of privacy protection.

Application-Aware Flow Forwarding Service for SDN-Based Data Centers

Security and Quality of Service (QoS) in communication networks are critical factors supporting end-to-end dataflows in data centers. On the other hand, it is essential to provide mechanisms that enable different treatments for applications requiring sensitive data transfer. Both applications’ requirements can vary according to their particular needs. To achieve their goals, it is necessary to provide services so that each application can request both the quality of service and security services dynamically and on demand. This article presents QoSS, an API web service to provide both Quality of Service and Security for applications through software-defined networks. We developed a prototype to conduct a case study to provide QoS and security. QoSS finds the optimal end-to-end path according to four optimization rules: bandwidth-aware, delay-aware, security-aware, and application requirements (considering the bandwidth, delay, packet loss, jitter, and security level of network nodes). Simulation results showed that our proposal improved end-to-end application data transfer by an average of 45%. Besides, it supports the dynamic end-to-end path configuration according to the application requirements. QoSS also logs each application’s data transfer events to enable further analysis.

Application of Outlier Detection Model in Korean Language and Culture Communication System Based on Artificial Intelligence.

With the continuous expansion of the Internet in China, network communication models and network services have become more and more complex, and with the increase of data types and diversification of data sources, network operation and maintenance projects have become more and more difficult. Passive statistical testing techniques for outliers are widely used, and many shortcomings have been pointed out, so there is an urgent need for improvement. After the research on the abnormal test of the text, it is determined that each method uses the visualization tool to simulate the data through the classification algorithm of the existing abnormal test and to identify the possibility of the data of each method and the PR diagram. The accuracy is counterintuitive. At present, Hallyu has a greater influence on the Internet, mainly in the fields of fashion and culture in Asian countries. Therefore, Korean language teaching has received widespread attention from the society, and combining cultural education with language teaching is an important way to improve the efficiency of language teaching. In the actual Korean language teaching work, a variety of Korean language materials are essential educational and teaching resources. The simulation results show that a large amount of training can make the DNN generate a better auto-encoder. In addition to strengthening the template for simulation training in deep learning, multiple supervisions of the data can be performed to reduce errors and improve efficiency.

Design and Implementation of Dance Online Teaching System Based on Optimized Load Balancing Algorithm.

With the continuous improvement of the network hardware environment, people turn the demand target to the network application environment and the construction of information resources. How to build a network teaching platform for general undergraduate teaching to ensure the stability of the system and high-quality services during operation especially large-scale concurrent access will inevitably lead to the increase in the business volume of each core part of the network, the number of visits, and data traffic. With the growth of the network, the corresponding processing power and computing intensity also increase rapidly, which causes problems such as overloading of core network equipment, network bottlenecks, and network congestion. Simply pursuing high-performance hardware to solve problems will undoubtedly result in high cost investment; moreover, equipment with excellent performance cannot meet the needs of the current rapidly growing business volume. According to the design goal of the dance online teaching platform, to meet the online teaching load requirements of many people at the same time, the pressure of the web server cluster must be great. Because many people in online at the same time put too much pressure on the web server, this part of the network cannot be processed in time, which leads to the phenomenon that the performance of this part and even the whole network is degraded. In severe cases, it will even cause network communication services to come to a standstill, that is, the so-called deadlock phenomenon. If the protocol software cannot detect congestion and reduce the packet sending rate, the network will be paralyzed due to congestion. This situation will cause the problem of movement delay for online dance teaching, which will seriously affect the quality of teaching. Therefore, the dance online course system should be continuously improved, the quality of online courses should be continuously improved, and the study of the practical application of load balancing technology in the network teaching environment has become an important means to solve the relationship between supply and demand of network teaching. According to the experimental analysis, when the number of Worker' actuators is fixed, the execution time span of MakeSpan increases with the increase of tasks, while the time required by the optimized load balancing algorithm proposed in this paper increases by 1.32 s on average with the increase of tasks, and the time required by heuristic algorithm and bee colony algorithm increases by 3.68 s and 3.45 s on average with the increase of tasks. On the whole, the optimized load balancing algorithm proposed in this paper has obvious advantages.

Development of Microcontroller Based Gas Leakage Detector with Dual SMS Alert

The prevailing treat to lives and property by the usage of gas for cooking, etc, and the rapidly increasing evolution in new technologies worldwide, a novel approach utilizing dual communication network providers is applied to alert users in the event of leakage of Liquefied Petroleum Gas (LPG). In this work, a prototype gas leakage detector, based on dedicated Peripheral Interface Controller (PIC), sensitive MQ-6 gas sensor, GSM/GPRS SIM900 and discrete components is developed and tested. Glo and MTN network service providers were selected for the design. Both indoor and laboratory tests were conducted where the results indicate gas concentration levels of 372 ppm to 255 ppm were measured to display a message on Liquid Crystal Display (LCD) and trigger audio alarm at instances of 2.42 secs and 8.35 secs in locations of 5 cm and 30 cm away from gas source respectively. Finally, the viability test proved satisfactory as it indicates that whenever a particular network fails, the second network was available to receive the SMS message adequately. This could be applied in homes, restaurants, etc where cooking gas is often used. Future enhancements should include the deployment of all available communication network service providers to augment for the limitation of the only two networks in this work.

Prediction of Enterprise Economy by Network Communication Business Based on BP Neural Network in Big Data Security Environment

From the environmental and security status quo faced by big data, although big data is unstructured or more difficult to filter and analyze, it does not mean that big data is necessarily more secure. In order to be invincible in the fierce market competition, an enterprise must conduct an in-depth understanding and investigation of the rapid changes in the market and economic development. The current era is already the Internet era. The arrival of the era of network communications has greatly facilitated people’s lives. However, how to seize the opportunities in the era of network communication and make economic predictions based on actual situations are particularly important for enterprises. Therefore, we are required to make reasonable economic predictions of network communication services in order to seize opportunities and meet challenges. By analyzing the development and application of artificial neural network (NN), this article briefly introduces its development and principles. Based on the reality of a network communication industrial enterprise, it uses data modeling and comparative analysis to establish a logistic regression model, a decision tree model, and a BP NN. The model compares the customer types and data predictions of the enterprise’s data traffic under the three models. From the results of the model analysis, it can be seen that in the analysis of the three models, the ROC curve analysis, the BP NN predicts that the cumulative hit rate in the ROC curve is wider. More users who can handle traffic services will be covered. In the cumulative customer lift analysis, under the first set of data (that is, when the depth is 20), the cumulative depths of the decision tree model, logic analysis model, and BP neural system prediction model are 2.5, 3.4, and 3.6, respectively. The BP neural system prediction model has the highest value of cumulative depth. In the cumulative capture response percentage analysis, the cumulative capture response percentage from low to low is the decision tree model and logic analysis. From BP NN prediction model, we can draw the conclusions. The network system can play a good role in forecasting and help enterprise managers make economic decisions.

Optimized Content Caching and User Association for Edge Computing in Densely Deployed Heterogeneous Networks

Deploying small cell base stations (SBS) under the coverage area of a macro base station (MBS), and caching popular contents at the SBSs in advance, are effective means to provide high-speed and low-latency services in next generation mobile communication networks. In this paper, we investigate the problem of content caching (CC) and user association (UA) for edge computing. A joint CC and UA optimization problem is formulated to minimize the content download latency. We prove that the joint CC and UA optimization problem is NP-hard. Then, we propose a CC and UA algorithm (JCC-UA) to reduce the content download latency. JCC-UA includes a smart content caching policy (SCCP) and dynamic user association (DUA). SCCP utilizes the exponential smoothing method to predict content popularity and cache contents according to prediction results. DUA includes a rapid association (RA) method and a delayed association (DA) method. Simulation results demonstrate that the proposed JCC-UA algorithm can effectively reduce the latency of user content downloading and improve the hit rates of contents cached at the BSs as compared to several baseline schemes.

Joint Resource Allocation and Phase Shift Optimization for RIS-Aided eMBB/URLLC Traffic Multiplexing

This paper studies the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) services in a cellular network that is assisted by a reconfigurable intelligent surface (RIS). The system model consists of one base station (BS) and one RIS that is deployed to enhance the performance of both eMBB and URLLC in terms of the achievable data rate and reliability, respectively. We formulate two optimization problems, a time slot basis eMBB allocation problem and a mini-time slot basis URLLC allocation problem. The eMBB allocation problem aims at maximizing the eMBB sum rate by jointly optimizing the power allocation at the BS and the RIS phase-shift matrix while satisfying the eMBB rate constraint. On the other hand, the URLLC allocation problem is formulated as a multi-objective problem with the goal of maximizing the URLLC admitted packets and minimizing the eMBB rate loss. This is achieved by jointly optimizing the power and frequency allocations along with the RIS phase-shift matrix. In order to avoid the violation in the URLLC latency requirements, we propose a novel framework in which the RIS phase-shift matrix that enhances the URLLC reliability is proactively designed at the beginning of the time slot. For the sake of solving the URLLC allocation problem, two algorithms are proposed, namely, an optimization-based URLLC allocation algorithm and a heuristic algorithm. The simulation results show that the heuristic algorithm has a low time complexity, which makes it practical for real-time and efficient multiplexing between eMBB and URLLC traffic. In addition, using only 60 RIS elements, we observe that the proposed scheme achieves around 99.99% URLLC packets admission rate compared to 95.6% when there is no RIS, while also achieving up to 70% enhancement on the eMBB sum rate.

Low-Complexity Channel Estimation and Multi-User Detection for Uplink Grant-Free NOMA Systems

Grant-free non-orthogonal multiple access (NOMA) scheme is a promising candidate to accommodate massive connectivity with reduced signalling overhead for Internet of Things (IoT) services in massive machine-type communication (mMTC) networks. In this letter, we propose a low-complexity compressed sensing (CS) based sparsity adaptive block gradient pursuit (SA-BGP) algorithm in uplink grant-free NOMA systems. Our proposed SA-BGP algorithm is capable of jointly carrying out channel estimation (CE), user activity detection (UAD) and data detection (DD) without knowing the user sparsity level. By exploiting the inherent sparsity of transmission signal and gradient descend, our proposed method can enjoy a decent detection performance with substantial reduction of computational complexity. Simulation results demonstrate that the proposed method achieves a balanced trade-off between computational complexity and detection performance, rendering it a viable solution for future IoT applications.

Wrongdoing Monitor: A Graph-Based Behavioral Anomaly Detection in Cyber Security

The so-called <i>behavioral anomaly detection</i> (BAD) is expected to solve effectively a variety of security issues by detecting the deviances from normal behavioral patterns of protected agents. We propose a new graph-based behavioral modeling paradigm for BAD problem, named <i>behavioral identification graph</i> (BIG), which has distinct advantages over existing methods by mining deeply the <i>property-level</i> (as an enhancement to the <i>event-level</i>) associations in behavioral data. Under BIG, the behavioral properties and their co-occurrence associations in behavioral data are modeled as the entities and relationships of graph, respectively; furthermore, behavioral properties and events are both vectorized by a devised event-property composite model, and the behavioral patterns of agents are finally represented as a multidimensional spatial distribution of behavioral properties. Consequently, for a behavior, the intensity of its behavioral anomaly can be transformed into the spatial decentrality of its behavioral agent and properties which contain both fine-grained information between behavioral properties and coarse-grained information between behavioral events. To the best of our knowledge, this is the first work to improve behavioral modeling for anomaly detection by integrating <i>inter</i> (event-level) and <i>intra</i> (property-level) associations of behaviors into a unified graph and space. Our method is validated by four representative security issues, i.e., <i>fraud detection</i> in online payment services (by transaction behaviors), <i>intrusion detection</i> in network communication services (by traffic behaviors), <i>insider threat detection</i> in organizational information systems (by system behaviors), and <i>compromise detection</i> in social networking services (by trajectory behaviors).