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Switch Allocation (SA) holds a critical stage in Network-on-Chip (NoC) routers, its performance gets affected adversely due to Head-of-Line (HoL) blocking. In traditionally used Input-Queued Routers (IQR), packets are arranged in a particular order in each Virtual Channel (VC). This implementation is vulnerable to HoL blocking, as the switch allocator can allocate only those packets which are available at the head in a VC. In this paper, Swapped Buffer (SB) Router architecture is proposed to schedule packets in input buffers by using SB registers. The VCs are designed as SBs, this allows the packets stored in SB registers along with the head packet of VC to participate in SA. The concept of the SB register minimizes the conflicts in SA and thus reduces HoL blocking, therefore improves the performance of NoC. This paper proposes a priority mechanism to prioritize the non-head packets as compared to head packets in case of conflict between them. Two methods have been proposed in this paper, to enhance the performance of the NoC router. First, a VC allocation technique is proposed to optimize the order of packets in the input buffer. Next, SB-Router is combined with the Fill VC allocation technique to further enhance the performance of NoC routers. The performance of the proposed router is evaluated and the experimental results indicate that our design achieves latency improvement of 68.75% over (Time-Series) TS-Router for uniform traffic at the injection rate of 0.42 flits/cycle for a 64 node mesh network with moderate power consumption and area usage. The performance improvement in packet latency for traces from Princeton Application Repository for Shared-Memory Computers (PARSEC) has also been evaluated. With the achieved reduction in latency, the proposed method has the potential to serve high-speed operations while mapping different applications on multiple core architectures.

Named data networking (NDN) aims to change the traditional content delivery method and caching by router nodes caching and participating in forwarding. NDN-caching can reduce the expected flood of global data traffic by providing cache storage at intermediate nodes for transmitted content objects, making data broadcasting in an efficient way. In this paper, a novel caching strategy based on entropy weighting method and TOPSIS is proposed for efficient content dissemination to improve NDN’s in-network caching performance. Firstly, the consumer’s request process is modeled by the entropy weighting method and TOPSIS to obtain the best cache node for the cache object according to the real-time status of the node. Secondly, two cache replacement algorithms (composed of an active cache replacement algorithm and a passive cache replacement algorithm) are proposed to reduce the cache redundancy on the delivery path and improve the utilization of data packets in the nodes. Finally, an effective cache mechanism and data packet migration scheme are proposed to further improve the cache performance according to the different types of cache nodes. The performance evaluation shows that the proposed scheme performs better in terms of cache hit rate, latency, and link load compared with some existing strategies.

Network-on-Chip (NoC) is used as the communication network in many applications that use multiple cores or Processing Elements (PEs). Routers play a crucial role as connectors since a faulty router can degrade the NoC’s performance and cause miscommunication between the network’s components. Thus a faulty router may cause the system to fail. To avoid failure in routers in NoCs, a novel self-healing technique is proposed. Self-healing serves to recover hardware faults, and it is defined as the ability of a system to recover from its faults without any external intervention. The proposed self-healing method is to heal faulty routers and their port buffers of faults as they occur. The proposed method uses the neighboring routers of a faulty router for computation. The data packet includes three bits for routing. A neighbor’s active router updates these bits according to the destination of the packet. A self-healing block is added inside each router. The proposed method also covers faulty buffers, and it uses active buffers to store the packet of a faulty one. It has been implemented and tested using VHDL and Altera Arria 10 GX FPGA. It has been found to attain improved reliability and Mean Time to Failure (MTTF) at an area overhead of 27%. It has been tested for complex NoC structure, and the results show it is practical, scalable, stable, and robust.

In the event-driven wireless sensor networks (EWSNs), the event of interests occurs irregularly and at random in the network. Then, sensor nodes near the event sense the event and send out data packets of the event. Next, router nodes (RNs) forward those packets to the sink node (SN) by multi-hop communications. Compromised RNs would become malicious and launch selective forwarding attacks by dropping part of or all the packets from other nodes. On the other hand, a harsh environment makes the channel poor, so the routing nodes under a harsh environment have low packet forwarding rates because they sometimes have to give up forwarding the current packets after many tries to forward them due to poor channel. If the malicious nodes’ forwarding rates become close to those of nodes under a harsh environment, the schemes based on packet forwarding rates for detecting selective forwarding attack may fail because they cannot differentiate the low data packet forwarding rates resulting from the malicious behaviors or harsh environment. To solve this problem, we provide a combined scheme for detecting selective forwarding attack in wireless sensor networks (WSNs) under harsh environments. This scheme employs a data clustering algorithm (DCA) to screen the malicious nodes out by clustering their cumulative forwarding rates (CFRs) and designs a voting decision method to protect the nodes under a harsh environment from being judged as malicious nodes. The simulation results show that our scheme has a low false detection rate (FDR) of 1% and a low missed detection rate (MDR) of 5% respectively with negligible energy consumption in WSNs under a local variable harsh environment.

Smartphones and Internet have become prevalent in our society with various applications in businesses, education, healthcare, gaming, and research. One of the major issues with the Internet today is its lack of security since an eavesdropper can potentially intercept the communication. This has contributed towards an increased number of cyber-crime incidents, resulting in an increase in users’ consciousness about the security and privacy of their communication. One example is the shift towards using private browsers such as Tor. Tor is a well-recognized and widely used privacy browser based on The Onion Router network that provisions anonymity over the insecure Internet. This functionality of Tor has been a major hurdle in cybercrime investigations due to the complex nature of its anonymity. This paper investigates artifacts from the Tor privacy browser on the latest Windows 10 and Android 10 devices to determine potential areas where evidence can be found. We examine the registry, storage, and memory of Windows 10 devices and the memory, storage, logs, and Zram of Android 10 devices for three possible scenarios i.e. before, during, and after use of the Tor browser. Our results do not support the claims made by the Tor Project regarding user privacy and anonymity. We find that it is possible to retrieve significant details about a user’s browsing activities while the Tor browser is in use as well as after it is closed (on both operating systems). This paper also provides an investigative methodology for the acquisition and analysis of Tor browser artifacts from different areas of the targeted operating systems. Therefore, it can serve as a base to expand research in the forensic analysis of other privacy browsers and improve the efficiency of cybercrime investigations efficiency.

Network-on-Chips (NoCs) have been widely used as a scalable communication solution in the design of multiprocessor system-on-chips (MPSoCs). NoCs enable communications between on-chip Intellectual Property (IP) cores and allow processing cores to achieve higher performance by outsourcing their communication tasks. NoC paradigm is based on the idea of resource sharing in which hardware resources, including buffers, communication links, routers, etc., are shared between all IPs of the MPSoC. In fact, the data being routed by each NoC router might not be related to the router’s local core. Such a utilization-centric design approach can raise security issues in NoC-based designs, e.g., integrity and confidentiality of the data being routed in an NoC might be compromised by unauthorized accesses/modifications of intermediate routers. Many papers in the literature have discovered and addressed security holes of NoCs, aiming at improving the security of the NoC paradigm. However, to the best of our knowledge, there is no solid survey study on the security vulnerabilities and countermeasures for NoCs. This paper will review security threats and countermeasures proposed so far for wired NoCs, wireless NoCs, and 3D NoCs. The paper aims at giving the readers an insight into the attacks and weaknesses/strengths of countermeasures.

Network management is facing a great challenge to analyze and identify encrypted network traffic with specific applications and protocols. A significant number of network users applying different encryption techniques to network applications and services to hide the true nature of the network communication. These challenges attract the network community to improve network security and enhance network service quality. Network managers need novel techniques to cope with the failure and shortcomings of the port-based and payload-based classification methods of encrypted network traffic due to emergent security technologies. Mainly, the famous network hopping mechanisms used to make network traffic unknown and anonymous are VPN (virtual private network) and TOR (Onion Router). This paper presents a novel scheme to unveil encrypted network traffic and easily identify the tunneled and anonymous network traffic. The proposed identification scheme uses the highly desirable deep learning techniques to easily and efficiently identify the anonymous network traffic and extract the Voice over IP (VoIP) and Non VoIP ones within encrypted traffic flows. Finally, the captured traffic has been classified into four different categories, i-e., VPN VoIP, VPN Non-VoIP, TOR VoIP, and TOR Non-VoIP. The experimental results show that our identification engine is extremely robust to VPN and TOR network traffic.

Information centric networking (ICN) shifts the focus of existing internet architecture from host-oriented to content-oriented model by enabling in-network caching and content-based forwarding. These ICN features help to increase network performance by decreasing content discovery delay, content server load, and network congestion. To route a content interest inside network such that content can be fetched with minimal time is a challenging task in ICN. The performance of the ICN routing protocol can be significantly improved if the decisions related to content chunk placement and request forwarding are taken in a cooperative fashion. This paper describes a novel strategy for co-operative caching joint request forwarding in ICN, focusing on decreasing content retrieval latency. To do so, the caching strategy leverages the concept of connected dominating set (CDS) for creating a virtual backbone network to eliminate caching redundancy and reduce content discovery delay. It considers content chunk placement and request forwarding tasks as strongly co-related procedures. It exploits the caching information so that the request is forwarded to a content router (CR) with the maximum likelihood of carrying needed data using the betweenness centrality (BC) of CR. The proposed approach also uses the Markov chain-based model to estimate CS hit likelihood and use it as decisional parameter while forwarding the interest packet. This mechanism helps to fetch the content within the shortest possible time duration. The CCJRF-ICN adopts the Dijkstra’s shortest path routing and works in collaboration with the CDS-driven caching joint forwarding mechanism. The simulation study of CCJRF-ICN is done inside ns-3 based ndnSIM-2.0 simulator with performance measures like content store (CS) hit ratio, content discovery delay, mean hop distance, network load, and network overhead. The simulation outcomes demonstrate that CCJRF-ICN outperforms the state-of-the-art strategies for realistic topologies (GEANT, US-26, Euro-28) and shows improvement up to 5-35% against stated performance measures.

The cache allocation of in-network caching is fundamental to the quality of service in heterogeneous information centric network (ICN). The aim of the cache allocation is to efficiently allocate appropriate cache capacity to each router for storing content, avoiding the long-distance transmission cost from clients to servers. Existing works focus on the analysis of network topology. However, this way is computation-expensive for such analysis, at the same time it cannot reach a completely optimal network, due to its used multiple conflicting performance metrics. In this paper, we propose an ant colony inspired cache allocation mechanism (ACCM) for heterogeneous ICN, which is able to deal with the cache budget constraint. Specifically, we first construct an evaluation model of network performance, in terms of hit ratio, energy consumption, time latency, and throughput. Then, based on the evaluation model, we devise an ant colony inspired cache allocation mechanism, where the ICN topology system is mapped into an ant colony system and the cache allocation process is simulated by the ant colony foraging behavior. Our theoretical analysis shows that the proposed mechanism can converge to the best solution. Finally, we conduct simulations on AttMpls and TW Telecom topologies with real datasets in YouTube. Simulation results show the effectiveness and efficiency of the proposed mechanism on the simulation instances in terms of hit ratio, energy consumption, time latency, and throughput.

Internet of Things (IoT) network infrastructure now days growing very significantly, along with the number of smart devices being used in everyday life. The existence of obstacles in the Internet of Things (IoT) network area is the biggest challenge in the IoT routing network. This obstacle in the IoT network can be a wall or the absence of a router in a specific area. The routing development to facing obstacles problems has been done a lot, however, there no routing algorithm that can overcome that obstacle. This research proposed a Physarum Routing Algorithm with Adaptive Power Control (PRA-APC) to solve the problem of IoT obstacles in the network. PRA-APC method provides sufficient power to the last node before the obstacle so it can be able to pass through the obstacle to the final destination node. PRA-APC routing method will compare with other routing algorithms such as Physarum inspired Routing Protocol (P-iRP) and Robust Selection Physarum-inspired Routing Protocol (RS-PRP). The PRA-APC protocol can develop the shortest routing path, 70% better than P-iRP and RS-PRP. The result of the delay more efficient, network lifetime is longer, throughput is much better than other routing algorithm protocols. The PRA-APC routing performance improvement results in efficiency and balance of resources in the network so that it can extend the life span of IoT networks that have limited resources in the local IoT network infrastructure. The new development of the PRA-APC routing protocol can provide solutions to overcome the problem of obstacles in the IoT network.

The Heterogeneous Network-on-Chip (HNoC) integrates CPU cores, Graphic Processing Unit (GPU) cores, last-level-cache and memory controllers. The heterogeneity of this architecture inevitably brings resource contention and energy shortage. In this work, we first study the impact of different capacity of router buffers on communication delay and energy consumption. After comprehensive evaluation with a spectrum of benchmarks with different characteristics, we reveal the implicit tradeoff between performance and energy consumption under different constrains of buffer resource. We further show that intelligently allocating more on-chip network buffer resources to compute-intensive nodes can significantly improve system performance. We introduce a runtime strategy that dynamically allocates network buffers to applications based on application characteristics. Our evaluation shows that our system reduces the communication delay by 55.47% on average, and reduces energy consumption of the system by 21% on average.

Figuring the network’s hidden abnormal behavior can reduce network vulnerability. This paper presents a detailed architecture in which the collected log data of the network can be processed and analyzed. We process and integrate on-campus network information from every router and store the integrated NetFlow log data. Ceph is used as an open-source distributed storage platform that offers high efficiency, high reliability, scalability, and preliminary preprocessing of raw data with Python, removing redundant areas and unification. In the subanalysis, we discover the anomaly event and absolute flow by three times of standard deviation rule. Keras has been used to classify in-time data collected via a cyber-attack and to construct an automatic identifier template through the Recurring Neural Network (RNN) test. The identification accuracy of the optimization model is around 98% in attack detection. Finally, in the MySQL server, the results of the real-time evaluation can be obtained, and the results of the assessment can be displayed via ECharts.

The IPv6-native home-area-network-oriented Thread protocol stack is currently attracting attention from both academic and commercial consumer electronics communities. In a Thread mesh deployment, as with any 6LoWPAN-based solution, a key element is the border router, since integration to the world-wide web depends exclusively on its performance. The typical architecture of a Thread border router involves a low-capable Thread-enabled device that acts as a slave of a more powerful host device owning a second networking interface, in what is known as a network-co-processor (NCP) architecture. To provide an alternative, this work focuses on the design and prototyping of a Thread border router using a non-NCP architecture. The challenges faced in implementing a non-NCP border router are detailed and a benchmark against a state-of-the-art NCP border router is presented. Results show that the non-NCP border router reduces the out-of-mesh latency by a factor of two. Immaturity of the IEEE 802.15.4 subsystem in the Linux kernel was evident during design and further work in such area is likely to improve dramatically the results obtained.

Ensuring reliable data transmission in multicore System on Chip (SoC), which employs Network on Chip (NoC), is a challenging task. This task is well addressed by Error Correcting Codes (ECC) in on-chip as well as off-chip networks. ECC significantly improves reliability of NoC interconnects with area and power overhead. In this paper, we propose a novel Transient Error Correction (TEC) coding scheme for reliable low power data link layer in NoC to attain a high error correction capability with less hardware overhead. Performance of TEC scheme is evaluated with realistic traffic patterns and validated with simulation results. The proposed scheme has less residual errors than the Hamming product code enabling reliable transmission at lower link swing voltage. Further, the scheme reduces the power consumption of NoC interconnects up to 71% as compared to Hamming product code with a marginal increase in codec delay and thus router delay. TEC scheme performs well in high noise environment with no delay penalty associated with retransmission.

Named Data Networking (NDN) recently arises as a promising technology to support connected vehicle (CV) applications due to the match between their characteristics. However, the fast mobility and the vast number of vehicles raise great challenges in designing a scalable and efficient NDN network for CV applications. Therefore, in this paper, we develop an NDN based CV application framework that handles the challenge through innovations in two aspects. First, we propose a hierarchical hyperbolic NDN backbone architecture (H2NDN). H2NDN exploits the location dependency of CV applications to develop a hierarchical router topology and a hierarchical data/interest namespace. As a result, efficient and scalable data retrieval can be achieved by only configuring static forwarding information base (FIB) on NDN routers. To avoid overloading high-level routers, H2NDN integrates hyperbolic routing into the hierarchical architecture through carefully designed hyperbolic planes. Second, on top of the H2NDN architecture, we further model the optimal data caching problem. Based on the modeling, we propose a distributed adaptive caching strategy that can greatly improve the efficiency of the H2NDN backbone in supporting CV applications. Extensive ndnSIM based experiments with real traffic data in a city prove the efficiency and scalability of the proposed NDN application framework.

Named Data Networking (NDN) aims to improve the efficiency of data delivery for the Internet. One of the typical characteristics of NDN is ubiquitous caching, that is to say, each network participant in NDN is capable of caching contents. This caching feature is beneficial for enhancing the data availability but also raises a problem of cache consistency. In this paper, we propose a novel strategy of cache invalidation, called PIOR (Proactive Invalidation with Optional Renewing), to provide strong consistency for NDN. PIOR is based on a lightweight publish/subscribe model, actively publishing the updated contents to the router nodes to guarantee the copy validity. We also conceive customized publish/subscribe rules to relieve the unbearable burden on the server imposed by the excessive publishing traffic. The advantage of PIOR lies in simple deployment and compatibility, since the invalidation process of PIOR is independent of the inherent process of NDN. We conduct extensive simulations over a real topology to evaluate the achievable performance of PIOR. The simulation results show that PIOR is able to achieve a high hit ratio and low server load at the low cost of network management.

Vehicular Adhoc NETworks (VANETs) is a new and emerging technology for wireless communications that has attracted considerable attention in the last years from the academic, scientific, industrial and governmental communities, due to the improvements and the new features that it brings to the Intelligent Transportation Systems (ITSs). In this paper, we present an algorithm that uses VANET technology to determine the total number of vehicles that are stopped at a traffic light at an intersection. To facilitate an efficient counting, we divide the road into fixed-size road regions and through a leader election mechanism, we designate one vehicle in each region as the “Region Leader” that is in charge of computing and propagating the total number of nodes in its region. Additionally, the region leader will act as a router to retransmit counting information from other region leaders that are further away, so it can eventually reach the central processing point where it is processed. We have carried out extensive experiments in various scenarios to validate and analyze the behavior and precision of our new proposed algorithm. Also, we compare our algorithm with another strategy proposed by a research team led by Alok Rajan. Our simulations were done using Veins (Vehicle in Network Simulation), an open-source simulation framework that ties together two simulators: OMNeT++ for the network simulation and SUMO for the microscopic road traffic simulation. Both simulators run in parallel and communicate with each other through a TCP connection using a protocol called TraCI (Traffic Control Interface). Our simulation results show that the algorithm performs an effective counting of vehicles, with a reduced response time, and a small total number of control messages sent by the vehicles to accomplish the counting task, under different conditions of vehicular traffic loads.

Obstacle-avoiding multiterminal net routing approach is proposed. The approach is inspired by deep learning image processing. The key idea is based on training a conditional generative adversarial network (cGAN) to interpret a routing task as a graphical bitmap and consequently map it to an optimal routing solution represented by another bitmap. The system is implemented in Python/Keras, trained on synthetically generated data, evaluated on typical high-resolution benchmarks, and compared with state-of-the-art traditional deterministic and deep learning solutions. The proposed system yields between 10.75x and 83.33x speedup over the traditional router without wirelength overhead due to effective parallelization on GPU hardware.

We consider the problem of estimating the state of computer networks which are delivering video in the presence of other interfering services. Existing methods for measuring jitter, a Quality of Delivery (QoD) measure for video, are based on statically configured IIR filters. They do not attempt to estimate the congestion in the network that caused the jitter to change. As a result, steps taken to improve QoD are frequently taken blindly. We pose the problem of estimating jitter as the problem of estimating a target source in the presence of interfering sources. To evaluate the approach we capture QoD measurements for a target video client from a six router networking test-bed where video is delivered over a substrate which is shared with varying levels of interfering sources which cause congestion. We demonstrate the performance of the new jitter estimator as part of a background congestion level detector. Numerical results based on real data show that considerable gains in congestion state classification are achieved for all congestion levels.

The power router (PR) based on power electronic technology is the core equipment of the energy internet (EI). For the PR, the common direct current (DC) bus structure is drawing more and more attention, in which the DC voltage stability is of vital importance. In the PR with the energy storage system (ESS), the DC/DC converter of ESS has significant effects on the DC bus voltage stability. Droop control is commonly used in the control of DC/DC converters in ESS. However, conventional droop control fails to provide the inertia to meet the demand for voltage stability. Hence, a virtual inertia control strategy with load current feedforward is proposed in this paper to strengthen the voltage stability. Firstly, the small-signal model of ESS is derived to find out the key factors that affect the DC bus voltage stability. Secondly, based on the analysis, an inertial droop control strategy is presented to provide inertia to the DC bus voltage, while a load current feedforward method is proposed to improve the voltage response performance during load transients. The stability analysis is also carried out to guide the controller designing. The validity of the proposed control strategy has been verified by the results from both MATLAB/Simulink and hardware-in-the-loop (HIL) simulation.

Nowadays, the magnetically coupled resonant (MCR) wireless power transfer (WPT) system are mostly the single-source or single-load systems that operate at “one to one” mode. With the increasing number of electrical equipment and types of input sources, the “one to one” mode cannot meet the application requirements. Therefore, the "one-to-many" and "many-to-many" WPT become increasingly important. In this paper, a three-port MCR wireless energy router (Wi E-Router) architecture with dual sources and dual loads is investigated in detail, which allows power transfer among dual sources and dual loads wirelessly. The equivalent circuit model of the system is built to analyze its transfer characteristics. Moreover, an effective power management strategy for a variety of input power cases is proposed. Finally, the theoretical analysis is validated by the experimental results from a 600 W prototype.

Multi-port AC-coupled converter (MAC) is promising to become the next-generation energy router in future Micro-grid and energy Internet to satisfy the upcoming requirement. As the most critical component of MAC, the multi-winding transformer needs a suitable model to achieve power flow analysis and flexible control. This paper analyzes the multi-winding transformer model suitable for MAC application. Three existing transformer modeling methods have been investigated, i.e. self-/mutual-inductance matrix, extended T model, and extended cantilever model. Their equivalent conversions to the expected model have been derived. A four-port multi-winding transformer is designed for the Multi-Active-Bridge converter. The experiment and simulations are performed to compare the advantages and disadvantages of three transformer models.

Energy router (ER), as the core equipment of energy internet (EI), can realize the regulation, conversion, and storage of multiple energy carriers. The conversion efficiency of ERs is important which is affected by load or temperature varying with actual operating environment. But, the efficiencies of conversion devices are assumed to be constant in the conventional ER model, which results in unreasonable operation schemes. Then, the key factors affecting the economic dispatch of the ER is the accuracy of the model. Therefore, an improved energy hub (EH) dynamic model is proposed for representing complex power flows of the physical layer, where conversion efficiency varies with temperature or load rate. Besides, to further improve the flexibility of the model, energy storage and region exchange matrix are added to the proposed model. Finally, the feasibility and effectiveness of the proposed model are verified based on the general algebraic modeling system (GAMS) in a residential area.

Virtual twins are capable of replicating the shape and behavior of physical systems in a digitized environment, achieving better control and monitoring of industrial processes. The virtual machine covers different areas necessary for proper operation, such as design, simulation programming, communication networks, and actuator control. Throughout this document, the process of building a virtual Computer-Numerical-Control router in Unity software, including the numerical simulation of mathematical models for the dynamics of the actuators, is explained. The control of the Cartesian robot is designed and implemented in the CODESYS platform, as well as a trajectory generator and a discrete closed loop control for the movement of each of the motion axes. The virtual router and the controller are configured in a hardware in the loop simulation scheme using the Modbus open source industrial protocol for data communication. The developed system is suitable for mechatronics engineering remote/online education.

The article discusses the state and prospects of the scientific and technical direction of the Internet of Energy or ENERNET. ENERNET is a global energy network concept in which energy resources are monitored and managed using information and telecommunication technologies. The paper discusses a multi-level structure for building energy networks, similar to the multi-level structure used on the Internet. This structure allows for control and effective management of energy resources, including distributed sources and storage. Bringing energy sources closer to energy consumers reduces energy losses and improves energy efficiency. The routing of energy flows in the network is carried out using an energy router (ER), similar to a communication router, which forms a two-way transmission of energy in the form of packets similar to information packets. The heart of the energy router is a solid-state transformer (SST) and energy storage. The work was carried out with the financial support of SibSUTIS within the framework of the state assignment under the grant "Development and research of components of intelligent systems for electronics and energy".

With the drastic growth of the energy internet in recent years, the energy router, an important energy hub, has seen wide application and unprecedented value due to its many functions such as energy transmission and coordination management. However, the energy router's ability to cope with the grid voltage sag is critical to its stable operation. This paper presents an advanced low voltage ride-through (LVRT) control strategy for the energy router when the symmetrical grid voltage sag occurs. The presented LVRT strategy can assist in voltage recovery and active power maintenance. When detecting a voltage sag, the inner loop regulator is directly controlled which contributes to the amelioration of the response speed as the outer loop regulator is disconnected. Voltage sags of different severities require different reactive and active power injections to support the voltage recovery and reduce the impact on the energy router's power delivery. Simulation results confirm the effectiveness of the presented LVRT strategy.

With the world becoming more mobile and dynamic each year, the application of ad-hoc networks has broadened. Ad-hoc networks do not have a predefined infrastructure; each node serves as a router, bringing security challenges. Trust and trustworthiness mechanisms are among the most common methods for ensuring security in an ad-hoc network. In [1], we proposed a method for the evaluation of trust in ad-hoc networks. This paper aims to describe the method formally and analyze its performance. The original paper showed that neural networks could do trust estimation with an average 98% accuracy of the classification and 94% of the regression problem. This paper aims to investigate the capabilities of our method under malicious conditions. The analysis could also provide insight for tuning trust parameters, such as the threshold of trust. Furthermore, this paper presents a mathematical model behind the problem to show that the neural network approach is reasonable.

This paper presents solutions for frequency support in a cluster of microgrids by using DC-link-based energy routers interface. With this interface, the cluster of AC microgrids is interconnected by a DC common link. With such an AC/DC multi-microgrid system, the stability of the system can be improved by supporting the voltage of the common DC-link among microgrids or by sharing the load through proper frequency coordination strategy. The proposed solution takes into account the privacy of the MMG members. First, a chosen topology of the energy router and its controlling strategy are addressed. Next, three different methodologies for frequency supporting are presented. Finally, a simulation model, which is an islanded multi-microgrid system with an energy router interface, is built in MATLAB/Simulink environment to evaluate the efficiency of the proposed method.

IoT will be the future of connectivity, from having your coffee ready before you are, to automated doors, inter-connected vehicles, buildings, and almost everything. It is in fact, getting implemented in every major sector and we are rapidly witnessing rise of new terms like HIoT, IIoT, etc., as the extension of conventional IoT. One such usage of IoT is in the development of monitoring systems. These systems are used to gather sensory data such as motion, temperature, CO 2 levels and provide sufficient data to the admin or data processing center to predict any forthcoming faults and give useful insights. If we talk about the industries and what they have as future for IoT, we cannot forget the refrigeration industry. This industry has seen a rapid rise in the last few years. From storing food & medicines to transportation of fresh produce from one place to another, refrigeration is a crucial part and requires frequent maintenance. This paper presents the design and development of a real-time monitoring system based on the 4-layer architecture of IoT, which will help in condition monitoring of these refrigerators and support the facilitation of condition-based maintenance. It consists of a sensing node, a router (as a gateway) and an Android application to visualize the gathered data. It is being tested for a non- commercial refrigerator however, it has the potential to be implemented in an industrial environment.

The non-volatile metal-oxide resistive random access memory (ReRAM) is an emerging alternative for the current memory technologies. The unique capability of ReRAM to perform analog and digital arithmetic and logic operations has enabled this technology to incorporate both computation and memory capabilities on the same unit. Due to this interesting property, there is a growing trend in recent years to implement emerging data-intensive applications on ReRAM structures. A typical ReRAM-based processing-in-memory architecture may consist tens to hundreds of ReRAM units (mats) that can either store or process data. To support such large-scale ReRAM structure, this paper proposes a scalable network-on-ReRAM architecture. The proposed network employs a novel associative router architecture, designed based on the ReRAM-based content-addressable memories. With the in-memory packet processing capability, this router yields higher throughput and resource utilization levels than a conventional router. This router is technology compatible with ReRAM and as our evaluations show, employing it to build a network-on-ReRAM makes the emerging ReRAM-based processing-in-memory architectures more scalable and performance-efficient.

With the increasing number of applications running on a Network-on-Chip (NoC) based System-on-Chip (SoC), there is a need for designing a reconfigurable NoC platform to achieve acceptable performance for all the applications. This paper proposes a novel architecture for implementing a reconfiguration logic to the NoC platform executing multiple applications. The proposed architecture reconfigures SoC modules to the routers in the NoC with the help of tri-state buffers based on the applications running. The overhead in implementing the reconfiguration circuitry is significantly less, approximately 0.9% of the area and 1% of the total power consumed by the router network. The architectures presented in the paper are developed in Verilog HDL, applied to the NoC router platform and simulated for functional verification. The synthesis results show that the proposed tri-state buffer-based reconfiguration logic has better performance in terms of area, power and speed compared with the multiplexer-based reconfiguration logic.

In this paper, we put forward an energy-efficient configurable asynchronous SNN accelerator for energy-constrained applications, which includes 256 neurons and 131K synapses with 8-bit fixed point weight. To achieve high energy efficiency and on-chip learning ability, we propose a sparse target propagation (S-TP) algorithm and design the accelerator with Click-based bundled-data asynchronous circuits. The SNN accelerator is implemented in 28nm CMOS process, and the post place and router (post-PAR) simulation results indicate that the SNN accelerator achieves on-chip learning with inference power efficiency of 3.97 pJ/SOP and 95.7% classification accuracy on NMNIST test dataset, which outperforms prior neuromorphic on-chip learning systems.

The network protocol BFD (Bidirectional Forwarding Detection) that detects issues between duplet forwarding engines. With minimum overhead, it detects flaws in physical media that doesn't allow for any kind of finding defects, including Ethernet, MPLS label switched channels, tunnels, and virtual circuits. One of the features is to verify the functionalities of static BFD. The work modes in BTS are Asynchronous mode, Demand mode, Echo mode. Currently only Asynchronous mode is supported in WBTS. BFD can be configured in two ways: Single hop and multi hop. Configured and commissioned the BTS & TRS setup in SEM tool and configured BFD in SEM (Site Element Manager) tool. BTS has come ON AIR and CS (Circuit Switch) PS (Packet Switch) calls are processing. Here we are checking the functionality of BFD whether it detects faults properly or not and removing routing connection from router side and check BFD alarm show up or not in SEM. Several calls are successfully placed after functionality check. Complete BFD process setting up and functionality check is automated. Where its check switch and router configuration as precondition and then perform BTS commissioning, checks BTS RNC BFD alarms and also placed call automatically. For switch, router configuration check and Wireshark log collection several key words are designed in Robot framework format so that script can be easily understandable by anyone. Configuring and verifying BIDIRECTIONAL FORWARDING DETECTION functionality in WCDMA Base Transceiver station (WBTS) is done manually and automated the complete process.

The performance of 2.4GHz and 5GHz Wi-Fi router placement in the Communication Technology laboratories area at Universiti Kuala Lumpur British Malaysian Institute is investigated to address the intermittent connectivity problem observed in some areas. Altair WinProp is a wave propagation simulation tool that can simulate the interior of the building and examine wave propagation with a highly accurate result in a short amount of time. Using WinProp ProMan, the omnidirectional antenna patterns are placed at several locations within the focused area, and the propagation of each of the antennas is computed. The layout of the Communication Section laboratory is initially modelled. The specifications of the construction materials are assigned using WinProp WallMan. The router’s performance is evaluated based on the received signal strength. The procedure is repeated using a different frequency. These antennas’ performances are then compared to determine the optimum placement for the WiFi system at the Communication Technology laboratory area. In addition, the simulation results obtained using WinProp ProMan is validated by measuring the received signal strength using InSSIDer in the real environment. Finally, the optimum location for a radio signal to be broadcast from is identified. The results indicate that the wave propagation pattern can cover the entire Labs area in one go, with better signal strength at this position. The number of current access points can be reduced due to this optimisation, resulting in lower equipment costs and lower electricity bills.

The spherical multi-robot system is mainly used for water quality monitoring in large-scale aquaculture. The main research content of this article is how to realize the multi-robot system effectiveness of data transmission. Or, when the detection range is too large, the multi-robot system adopts the centralized control mode, once the instability of the central robot network occurs. If the data can not be fed back to the user, how to ensure the control ability of the entire multi-robot system. Novel network nod monitoring system has the advantages of Ad Hoc network, self - repair and not limited by the distance of router. It has been widely used in various fields. At the same time, cloud platform communication technology has also been widely used in the field of the Internet of Things. Its advantages are multi-purpose function, long transmission distance, strong safety performance, etc. By adopting self - owned cloud platform structure and the novel network nod monitoring system. It improves the flexibility and reliability of the multi-robot system and ensures the efficiency of large-scale data acquisition. In this paper, a Mesh network architecture and a network system based on cloud platform for spherical multi-robot systems are proposed. The experimental results show that it is feasible to construct the whole node monitoring system based on Mesh. With this system, the multi-robot system can accomplish more complex tasks.

Ping is a computer network utility software used to test the reliability of hosts on IP (Internet Protocol). This is used to measure the time sent from the host to the destination computer or central computer. Ping operates by sending the Internet Control Message Protocol (ICMP). Traceroute is used to show the route the packet passes to reach the destination or route diagnostic tool. This process is done by sending the message Internet Control Message Protocol (ICMP) Echo Request_ to the destination with the value of Time to Live or commonly referred to as TTL which is increasing. The route shown is a list of router interfaces found on the path between the host and destination. The purpose of pinging and traceroute is to find out the status of up or down in the network. With traceroute, we can analyze information about the location of the router.

Energy router (ER) is a core equipment in the energy internet. However, due to the limitation of topology architecture, the traditional series architecture region ER (SA-RER) has the disadvantages of limited loading capacity and inability of flexible operation for the reactive power. To this end, this paper intends to build a new type of RER with the series and parallel architecture (SPA-RER), which breaks the double limits of SA-RER's 100% energy transmission and reactive power rigid operation. The power flow flexible operation mechanism of SPA-RER is analyzed, and the calculation methods of power flow in different operation modes are given, thus its operation law is further clarified. After that, a two-degree-of-freedom power flow flexible control strategy (TDF-PFFCS) is proposed, and by controlling the DFs of active and reactive powers, SPA-RER can flexibly match the active powers between the AC grid and the DC bus as well as the reactive powers between the series and parallel converters. As a result, without increasing the system capacity and AC input power distribution, the transmission targets of 200% active power and 120% reactive power can be achieved, which provides novel design ideas and solutions for ERs to achieve high-power energy flexible transmission.

Routing is one of the most time-consuming stages in the FPGA design flow. Parallelization can accelerate the routing process but suffering from load imbalance, further resulting in a low scalability. In this paper, we propose a load balance-centric parallel router in a distributed computing environment. First, we explore regular and irregular region partitioning so that routing tasks are assigned to different cores for static load balance before parallel routing. Second, we explore message propagation and task migration between underloaded and overloaded cores so that load balance can be dynamically maintained at parallel routing runtime. Finally, we demonstrate the effectiveness of the parallel router using large-scale Titan designs. Experimental results show that our parallel router achieves about 17 × speedup on average using 32 cores, compared with VTR 8 router.