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Internet of Things (IoT) has entered a stage of rapid development and increasing deployment. Meanwhile, these low-power devices typically cannot support complex security mechanisms and thus are highly susceptible to malware. This paper proposes ADRIoT, an anomaly detection framework for IoT networks which leverages edge computing to uncover potential threats. An edge is empowered with an anomaly detection module, which consists of a traffic capturer, a traffic preprocessor and a collection of anomaly detectors dedicated to each type of device. Each detector is constructed by an LSTM autoencoder in an unsupervised manner that requires no labelled attack data and is able to handle emerging zero-day attacks. When a device connects to the edge, the edge will fetch the corresponding detector from the cloud and execute it locally. Another problem is the resource constraint of a single edge device like a home router hinders the deployment of such a detection module. To mitigate this problem, we design a multi-edge collaborative mechanism that integrates the resource of multiple edges in a local network to increase the overall load capacity. The evaluation demonstrates that ADRIoT can detect various IoT-based attacks effectively and efficiently, showing that ADRIoT can feasibly help build a more secure IoT environment.

In Named Data Networking, cache pollution, cache poisoning and interest flooding are three popular types of attacks that can drastically degrade the network performance. However, previous methods for mitigating these attacks are not sufficiently effective or efficient. Also, they cannot simultaneously handle the three attacks, or the case that core routers or edge routers are compromised. To handle these problems, we propose an effective and lightweight countermeasure scheme. It consists of token-based router monitoring policy (TRM), hierarchical consensus-based trust management (HCT), and popularity-based probabilistic caching and caching replacement policy (PPC). In TRM, each edge router monitors and evaluates each data requester's probability of launching the cache pollution attack and each data provider's probability of launching the cache poisoning attack, and accordingly assigns, rewards and penalizes tokens to them to control their data request and data provision activities. Thus, the interest flooding attack can also be mitigated by limiting the consumption of tokens. In HCT, each core router manages its directly connected edge routers using TRM, and the core routers trust each other through adopting the concept of consensus in Blockchain. Thus, the edge and core routers executing monitoring and evaluation are trustable. PPC uses probabilistic caching and caching replacement based on the popularity of received content to further mitigate the attacks and reduce caching and data verification overhead. Results from simulation experiments demonstrate that our proposed scheme has better performance, in terms of interest satisfaction ratio and average end-to-end delay than current mechanisms.

IP hijack attacks deflect traffic between endpoints through the attacker network, leading to man-in-the-middle attacks. Current detection solutions are only based on AS-level path analysis, while attacks that include data-plane manipulations may exhibit only geographic anomalies and preserve the AS-level route, or hide the problematic AS in the path. Thus, there is a need to develop data-plane analysis frameworks that examine the actual route packets traverse. We introduce here a deep learning system that examines the geography of traceroute measurements to detect malicious routes. We use multiple geolocation services, with various levels of confidence; each also suffers from location errors. Moreover, identifying a hijacked route is not sufficient since an operator presented with a hijack alert needs an indication of the cause for flagging out the problematic route. Thus, we introduce a novel deep learning layer, called Source-Aware Self-Attention (SASA), which is an extension of the attention mechanism. SASA learns each data source's confidence and combines this score with the attention of each router in the route to point out the most problematic one. We validate our IP hijacking classification method using two router data types: coordinates and country location, and show that SASA outperforms the regular self-attention layer, using the same neural network architecture, and achieves extremely high accuracy.

Packet routing is one of the fundamental problems in computer networks in which a router determines the next-hop of each packet in the queue to get it as quickly as possible to its destination. Reinforcement learning (RL) has been introduced to design autonomous packet routing policies with local information of stochastic packet arrival and service. However, the curse of dimensionality of RL prohibits the more comprehensive representation of dynamic network states, thus limiting its potential benefit. In this article, we propose a novel packet routing framework based on multiagent deep RL (DRL) in which each router possess an independent long short term memory (LSTM) recurrent neural network (RNN) for training and decision making in a fully distributed environment. The LSTM RNN extracts routing features from rich information regarding backlogged packets and past actions, and effectively approximates the value function of Q-learning. We further allow each route to communicate periodically with direct neighbors so that a broader view of network state can be incorporated. The experimental results manifest that our multiagent DRL policy can strike the delicate balance between congestion-aware and shortest routes, and significantly reduce the packet delivery time in general network topologies compared with its counterparts.

The recent spate of cyber attacks towards Internet of Things (IoT) devices in smart homes calls for effective techniques to understand, characterize, and unveil IoT device activities. In this paper, we present a new system, named IoTAthena, to unveil IoT device activities from raw network traffic consisting of timestamped IP packets. IoTAthena characterizes each IoT device activity using an activity signature consisting of an ordered sequence of IP packets with inter-packet time intervals. IoTAthena has two novel polynomial time algorithms, sigMatch and actExtract. For any given signature, sigMatch can capture all matches of the signature in the raw network traffic. Using sigMatch as a subfunction, actExtract can accurately unveil the sequence of various IoT device activities from the raw network traffic. Using the network traffic of heterogeneous IoT devices collected at the router of a real-world smart home testbed and a public IoT dataset, we demonstrate that IoTAthena is able to characterize and generate activity signatures of IoT device activities and accurately unveil the sequence of IoT device activities from raw network traffic.

The routing protocols are considered to be the backbone of the network communication. Each protocol has its outlined algorithmic program that decides the routing choices for the designated router. The Routing Information Protocol comes under category of Distance Vector Routing Protocol and is related to several dimensions, that define the scope of improvement also, in RIP. In this paper, a detailed analysis of RIP has been done, appended with the implementation in Packet Tracer. This analysis is augmented with the insight into the Interior Border Gateway Protocol and concluded with their comparative analysis.

In present days, development in chip technology enables us to incorporate heterogonous cores on one chip. Synchronization and communication between such diverse cores is a major issue. Current Synchronous NOC architecture with buffered router consumes a substantial chip area and Power (clock distribution & I/O buffers). Hence in recent times Buffer-less routers based on Deflective routing are projected as a possible solution, but they suffers from issues like sequential port allocation and slow critical path and also increases the Latency. In this paper we propose 2D 4x4 Asynchronous Mesh NOC architecture with a novel router design using XY routing algorithm. In the proposed router design, we have eliminated the conventional input and output buffers and crossbar switch. We integrated priority encoder and FSM based Arbiter which efficiently solves long critical path issues of conventional Buffer less router by dynamically changing the port priority and hence solves the starvation and Live/Dead lock issue and improves the Area Consumption (i.e., reduced by ≈ 43%). We have used parallel transmission which enables us to improve Speed (by ≈73%) and elimination of I/O buffers reduces the power consumption (≈ 0.56w).

A distributed denial-of-service (DDoS) attack is a cyber-attack in which the attackers from different locations send out a huge number of requests to exhaust the capacity of a server. Current DDoS attack protection services filter out the DDoS attack packets in the middle of the path from the attacker to the servers. Some of the DDoS protection systems filter out them at the victim server. As a result, unnecessary attack traffic congests the network and wastes bandwidth which can be minimized if we block them as early as possible. In this paper, we propose a DDoS attack protection system by using the filter router. The victim needs to wisely select and send filters to a subset of filter routers to minimize attack traffic and blockage of legitimate users (LUs). Many filters can minimize the attack traffic and blockage of LUs easily, but it is costly to the victim. So, we formulate two problems with different settings for selecting filter routers given a constraint on the number of filters. We propose a dynamic programming solution for both problems. Both problems consider the blockage of all attack traffic before it reaches the victim. We conduct extensive simulation to support our solutions.

Scalable Networks-on-Chip (NoCs) have become the standard interconnection mechanisms in large-scale multicore architectures. These NoCs consume a large fraction of the on-chip power budget, where the static portion is becoming dominant as technology scales down to sub-10nm node. Therefore, it is essential to reduce static power so as to achieve power- and energy-efficient computing. Power-Gating as an effective static power saving technique can be used to power off inactive routers for static power saving. However, packet deliveries in irregular power-gated networks suffer from detour or waiting time overhead to either route around or wake up power-gated routers. In this article, we propose Fly-Over ( Flov ) , a voting approach for dynamic router power-gating in a light-weight and distributed manner, which includes Flov router microarchitecture, adaptive power-gating policy, and low-latency dynamic routing algorithms. We evaluate Flov using synthetic workloads as well as real workloads from PARSEC 2.1 benchmark suite. Our full-system evaluations show that Flov reduces the power consumption of NoC by 31 and 20 percent, respectively, on average across several benchmarks, compared to the baseline and the state-of-the-art while maintaining the similar performance.

Refraction networking is a promising censorship circumvention technique in which a participating router along the path to an innocuous destination deflects traffic to a covert site that is otherwise blocked by the censor. However, refraction networking faces major practical challenges due to performance issues and various attacks (e.g., routing-around-the-decoy and fingerprinting). Given that many sites are now hosted in the cloud, data centers offer an advantageous setting to implement refraction networking due to the physical proximity and similarity of hosted sites. We propose REDACT, a novel class of refraction networking solutions where the decoy router is a border router of a multi-tenant data center and the decoy and covert sites are tenants within the same data center. We highlight one specific example REDACT protocol, which leverages TLS session resumption to address the performance and implementation challenges in prior refraction networking protocols. REDACT also offers scope for other designs with different realistic use cases and assumptions.

Information technology, especially the internet, is currently growing very rapidly, due to the increasing number of people who disseminate information through the internet. The development of the number of users of Internet information technology is currently not followed by the addition of appropriate bandwidth, so problems often arise related to the speed of access to get internet services. An easy way to save bandwidth and force authentication on information traffic is to use squid. The use of Squid can be used to increase the need to speed up information retrieval. By using the Squid application, the router can be used as a proxy server for internet web cache. At the time of installing Squid without a proxy, testing was carried out on the https://www.kompas.com url and the results of the first load on a website resulted in a load time of 36 seconds, there was no difference in bandwidth usage and time whether using a proxy server or not, but the second page load on the same site with a faster load time of 30 seconds will save bandwidth. Then the installation of Squid using a proxy was carried out, testing was carried out on the https://www.kompas.com url and the results of the first load on a website resulted in a load time of 34 seconds, there was no difference in bandwidth usage and time, whether using a proxy server or not, but on the second page load on the same site with a faster load time of 16 seconds, it will save bandwidth and be faster by using squid compared to not using squid.

Information-Centric Networking (ICN) provides scalable and efficient content distribution at the Internet scale due to in-network caching and native multicast. To support these features, a content router needs high performance at its data plane, which consists of three forwarding steps: checking the Content Store (CS), then the Pending Interest Table (PIT), and finally the Forwarding Information Base (FIB). In this work, we build an analytical model of the router and identify that CS is the actual bottleneck. Then, we propose a novel mechanism called “NB-Cache” to address CS’s performance issue from a network-wide point of view. In NB-Cache, when packets arrive at a router whose CS is fully loaded, instead of being blocked and waiting for the CS, these packets are forwarded to the next-hop router, whose CS may not be fully loaded. This approach essentially utilizes Content Stores of all the routers along the forwarding path in parallel rather than checking each CS sequentially. NB-Cache follows a design pattern of on-demand load balancing and can be formulated into a non-trivial N-queue bypass model. We use the Markov chain to establish its theoretical base and find an algorithm for automated transition rate matrix generation. Experiments show significant improvement of data plane performance: 70% reduction in round-trip time (RTT) and 130% increase in throughput. NB-Cache decouples the fast packet forwarding from the slower content retrieval thus substantially reducing CS’s heavy dependency on fast but expensive memory.

Congestion control has a vital role in the prosperity of any network. Thus, designing an effective mechanism for congestion control of the NDN is an active research area. In NDN, congestion control and interest forwarding mechanisms are usually considered an integrated plane for the network traffic management. In this paper, we propose to decouple the forwarding and congestion control planes. We offer a novel architecture for the NDN router in which congestion control and forwarding modules cooperate for interest flow management and congestion control. Based on this framework, we introduce a new explicit feedback-based congestion control protocol (3CP) for managing the consumers’ sending rate in an NDN environment that multi-source and multi-path content delivery is intrinsically supported. 3CP employs a new per-packet feedback computation to inform consumers from the available resource of paths toward repositories. Also, it provides feedback to the forwarding mechanism of a router for adjusting the sending rate of interest packets to each interface. By interest flow management, 3CP controls the traffic of data packets in the network. As a significant achievement, 3CP prevents multi-path flows from acquiring more network resources and could manage fair resource allocation to the flows in each path, whereas the consumers obtain the same throughput. The packet-level simulation was conducted by an NDN simulator, and the results confirmed that 3CP outperforms the existing multi-source/multi-path congestion control mechanisms in NDN.

The mobile network operators (MNOs) are looking into economically viable backhaul solutions as alternatives to fiber, specifically the hybrid fiber coaxial networks (HFC). When the latencies from both the wireless and the HFC networks are added together, the result is a noticeable end-to-end system latency, particularly under network congestion. In order to decrease total system latency, we proposed a method to improve upstream user- to-mobile core latency by coordinating the LTE and HFC scheduling in previous papers. In this paper, we implement and optimize the proposed method on a custom LTE and DOCSIS end-to-end system testbed. The testbed uses the OpenAirInterface (OAI) platform for the LTE network, along with Cisco's broadband router cBR-8 that is currently deployed in the HFC networks around the world. Our results show a backhaul latency improvement under all traffic load conditions., IEEE Wireless Communications and Networking Conference (WCNC), 2018. arXiv admin note: text overlap with arXiv:2211.08292

Tunnel is a technique of building a local communication path between two or more routers using a public IP network. The problems faced in tunneling systems are currently lacking guidelines for choosing the right technique according to the network topology used. In the electoral field, it is done based on experience or following SOPs. The brands of devices that support tunneling are very diverse in Indonesia, one of which is Nokia. This study focuses on the tunnel owned by Nokia devices, namely the GRE in order to produce guidelines for using the GRE tunnel. The analysis is carried out with various traffic engineering scenarios including no-load conditions, and various other conditions when there is a network outage. The results showed that the GRE without load runs normally. When the load from the beginning of the GRE gets a throughput of 0.995 Mbps and an average delay of 11.484 ms, when with a sudden load it gets a throughput of 1.059 Mbps and a delay of 11.386 and when a network disturbance is carried out with the ping command it gets 1 RTO. The GRE tunnel follows the LDP protocol path so it is suitable for use in new network implementations because of its simplicity in its configuration which is enough to activate the OSPF metric to balance traffic on each particular router interface

Network on Chip (NoC) is a communication framework for the Multiprocessor System on Chip (MPSoC). It is a router-based communication system. In NoC architecture, nodes of MPSoC are communicating through the network. Different routing algorithms have been developed by researchers, e.g., XY, intermittent XY, DyAD, and DyXY. The main problems in these algorithms are congestion and faults. Congestion and faults cause delay, which degrades the performance of NoC. A congestion-aware algorithm is used for the distribution of traffic over NoC and for the avoidance of congestion. In this paper, a congestion-aware routing algorithm is proposed. The algorithm works by sending congestion information in the data packet. The algorithm is implemented on a 4 × 4 mesh NoC using FPGA. The proposed algorithm decreases latency, increases throughput, and uses less bandwidth in sharing congestion information between routers in comparison to the existing congestion-aware routing algorithms.

Named data networking (NDN) recently arises as a promising networking paradigm to support the Internet of Things (IoT) due to its data-centric architecture. However, NDN integrates application-layer semantics into the packet forwarding plane, which presents new attack faces. In this article, we aim to handle two attacks that exploit such vulnerabilities, namely the blackhole attack and the content poisoning attack. The two attacks are not handled efficiently by existing approaches due to the challenge in minimizing routers that need to be detoured to isolate attackers. Therefore, in this article, we propose a novel method named SmartDetour to tackle the challenge in a distributed manner. SmartDetour contains two components: 1) a proactive reputation updating algorithm and 2) a reputation-based probabilistic forwarding strategy. The former updates the reputation of forwarding candidates based on whether they must be detoured upon packet failures. The latter selects the next-hop router for interest packets probabilistically based on the reputations of forwarding candidates. The two components work together to isolate attackers with minimal detouring needed. Extensive ndnSIM-based simulation shows that SmartDetour can effectively identify and isolate attackers.

The purpose of this research is to build an interconnection network using GPEN (Gigabit Passive Ethernet Network) technology so as to provide convenience for network admin users in managing, controlling, and maintaining each client, making it easy for network technicians when a breakdown occurs, and Providing easy client user authentication in the area (PUSKOM) IAIN Bengkulu. The research method used is research and development research, the research method used to aim at developing, producing products and waiting for the effectiveness of the research method. Developing a wireless-based network, namely a point-to-point radio to a network with GPEN technology (Gigabit Passive Ethernet Network) as a switch and router that supports gigabit ports and to control and monitor bandwidth on each client. Better network quality and efficiency so that activities such as browsing, uploading and downloading are faster.

Hierarchical organization is widely used in high-radix routers to enable efficient scaling to higher switch port count. A general-purpose hierarchical router must be symmetrically designed with the same input buffer depth, resulting in a large amount of unused input buffers due to the different link lengths. Sharing input buffers between different input ports can improve buffer utilization, but the implementation overhead also increases with the number of shared ports. Previous work allowed input buffers to be shared among all router ports, which maximizes the buffer utilization but also introduces higher implementation complexity. Moreover, such design can impair performance when faced with long packets, due to the head-of-line blocking in intermediate buffers. In this work, we explain that sharing unused buffers between a subset of router ports is a more efficient design. Based on this observation, we propose Centralized Input Buffer Design in Hierarchical High-radix Routers (CIB-HIER), a novel centralized input buffer design for hierarchical high-radix routers. CIB-HIER integrates multiple input ports onto a single tile and organizes all unused input buffers in the tile as a centralized input buffer. CIB-HIER only allows the centralized input buffer to be shared between ports on the same tile, without introducing additional intermediate virtual channels or global scheduling circuits. Going beyond the basic design of CIB-HIER, the centralized input buffer can be used to relieve the head-of-line blocking caused by shallow intermediate buffers, by stashing long packets in the centralized input buffer. Experimental results show that CIB-HIER is highly effective and can significantly increase the throughput of high-radix routers.

With technological advancements, a large number of intellectual property (IP) cores can be integrated into a single chip. As a result, communication between these cores is critical. Such communication is achieved using Network on Chip (NoC) technology. NoC is an on-chip packet-switched network with IP cores connected to the network via interfaces, and packets are sent to their destinations via a multi-chip routing path. A router is the essential component of the NoC architecture, it must be designed efficiently to build a competitive NoC architecture. Verilog is used to design the router which supports five parallel connections. It uses store and forward type of flow control, round-robin arbitration, and deterministic XY routing. The building blocks of the router are FIFO, arbiter, and crossbar. The proposed architecture of the five port router is targeted to the Spartan 6 XC6SLX45 FPGA design platform and simulated in Xilinx ISE 14.5 software.

In many conventional Internet-of-Things (IoT) applications, data are transferred directly from the sensor network to the cloud via a gateway for further data processing. However, this typical usage of a gateway is not suitable for every application. For short-range IoT wireless protocols [e.g., Bluetooth low energy (BLE)], multiple gateways are required to achieve broader coverage, which is inconvenient. In this article, an edge-based hybrid network system architecture is presented. The proposed system consists of hybrid routers and an IoT gateway. The router supports two wireless protocols, BLE and long range (LoRa), and is equipped with a solar energy harvester to extend the router’s lifetime. It can extend the coverage of short-range BLE network by utilizing LoRa wireless technology, and support fundamental edge computing tasks such as preliminary data processing. The IoT gateway can support multiple IoT protocols, including LoRa, BLE, and XBee. It can perform more advanced edge computing tasks, such as data filtering, storage, processing, user interface, and cloud connection. Three case studies incorporating a wearable safety monitoring sensor network, a healthcare monitoring application, and a smart hospital application are studied with the proposed edge network system to demonstrate its promising capabilities to support IoT applications. Experimental evaluations indicate that by processing data at the edge, the minimal delay is only 11.5 ms. Furthermore, with the hybrid LoRa network implementation, the BLE network can be extended to 2.4 km.

Purpose. At present, the computer networks of the information and telecommunication system (ITS) of railway transport use the OSPF protocol, which does not allow taking into account several metrics when determining the optimal route. Therefore, there is a need to study the possibility of organizing routing in computer networks of rail transport ITS using a two-colonial ant algorithm. Methodology. According to the Two-ACO software model, created in the Python language based on the two-colonial ant algorithm, the optimal route in a computer network was determined. Two-ACO model inputs: computer network parameters (network adjacency matrix, number of routers); parameters of the ant algorithm (number of iterations; number of ants in the colony; number of elite ants; initial pheromone level; evaporation rate; parameter for adjusting the amount of pheromone deposition). Findings. The results of the Two-ACO model are presented in the form of graphs depicting the optimal paths: the criterion of the total delay on the routers (for the first colony of ants) and the number of hops (for the second colony of ants). Originality. According to the created Two-ACO software model for a computer network of 7 routers and 17 channels, a study of the time for determining the optimal path in a computer network by the number of ordinary and elite ants, evaporation rate and deposited pheromone was conducted. It is determined that it is enough to use the number of ants equal to the number of routers and have 2 elite ants in the colony, with 1000 iterations, evaporation rate from 0.2 to 0.7, and pheromone deposition by ants close to one. Practical value. Created Two-ACO software model using two colonies of ants on the following criteria: the total delay on the routers (for the first colony of ants) and the number of hops that make up the route (for the second colony of ants) allows you to parallel determine the optimal routes in a computer network of railway transport. It is estimated that for a computer network of 15 routers and 17 channels, it is sufficient to have 30 agents (two ants on top), the value of the pheromone deposited by the agents is close to one, and the evaporation rate is 0.4.

Data exchange communication has developed, which leads to centralized communication, and to achieve this communication requires a type of data communication whose data is accommodated on the server and can be accessed by clients, such as at organization. As a company engaged in education, the development of centralized data communication by utilizing the intranet network has been formed. The use of an intranet network allows data communication that is vulnerable to wiretapping. To fix this using a VPN network. L2TP and IPsec VPNs have different performances, especially in the level of security provided. In this study, an analysis of the L2TP and IPsec VPN network performance was carried out on the SMB Server on the Ubuntu server and the Mikrotik router for its VPN configuration. In this study, the L2TP and IPsec VPN was designed by configuring the Mikrotik RB 450G router and the SMB Server configuration using Command Line Interface on Ubuntu 18.04 server. For security analysis, use hacking methods to get VPN Server login data and sniffing methods to get SMB Server login data and SMB data. For performance analysis using parameters of delay, throughput, and packet loss. Wireshark is software for checking by capturing each packet of data from an interface. The research objective to be achieved is to design a VPN technology based on L2TP & IPSec, to be able to determine the resulting performance after implementing a VPN based on L2TP & Ip Sec. The result is that VPN can connect from HO to branch one and branch two or connect from public connection to local connection. The Ubuntu server used is also running well, so it helps the VPN process properly.

Due to limited on-chip caching, data-driven applications with large memory footprint encounter frequent cache misses. Such applications suffer from recurring miss penalty when they re-reference recently evicted cache blocks. To meet the worst-case performance requirements, Network-on-Chip (NoC) routers are provisioned with input port buffers. However, recent studies reveal that these buffers remain underutilised except during network congestion. Trace buffers are Design-for-Debug (DfD) hardware employed in NoC routers for post-silicon debug and validation. Nevertheless, they become non-functional once a design goes into production and remain in the routers left unused. In this article, we exploit the underutilised NoC router buffers and the unused trace buffers to store recently evicted cache blocks. While these blocks are stored in the buffers, future re-reference to these blocks can be replied from the NoC router. Such an opportunistic caching of evicted blocks in NoC routers significantly reduce the miss penalty. Experimental analysis shows that the proposed architectures can achieve up to 21 percent (16 percent on average) reduction in miss penalty and 19 percent (14 percent on average) improvement in overall system performance. While we have a negligible area and leakage power overhead of 2.58 and 3.94 percent, respectively, dynamic power reduces by 6.12 percent due to the improvement in performance.

Content-Centric Networking (CCN) is being established as an emerging Internet architecture that brings efficient data retrieval technology to access the contents with their names. In CCN, the in-network caching capability plays a critical role in the improvement of network performance by reducing the load of content server and increasing the content availability. Thus, the efficiency of the content caching strategy crucially affects the performance of the entire network. Towards this, a novel content caching scheme has been proposed in this article that efficiently utilizes the available caching capacity and improves Quality-of-Service (QoS) during content delivery. To perform optimized caching operations, the proposed scheme considers a dynamic threshold value and takes caching decisions based on two parameters, first is a novel dynamic size popularity window to determine content popularity, and secondly, the distance navigated by the Content message from the preceding on-path router that cached the content copy. For content caching decisions, the dynamic threshold value decreases with an increase in Content message distance from the preceding on-path router (that cached the content) and the content popularity. Using these heuristics, the scheme places the popular contents near the edges of the network. Through extensive simulations, the QoS delivered by the proposed scheme has been examined for different cache sizes on standard Abilene network topology. The results show that the proposed scheme outperforms the existing caching strategies for various performance parameters such as hit-ratio, average network delay, hop count, and average traffic generated in the network. This makes the proposed solution suitable for futuristic Internet architectures with 5G/6G and Industry 4.0 revolutions and their applications where faster content deliveries are required.

Currently healthcare data packets do not get any special priority while routing through the Internet of Things (IoT) networks. These data packets flow through routers using conventional QoS process which does not guarantee that a patient’s critical health data traveling in congested IoT network will actually be routed to doctors office on time. This leaves the remote medical treatment at risk with possible threat to patients’ lives. In this paper, we studied the current healthcare packet routing process in IoT and its performance issues in congested IoT networks, then proposed a sensor driven solution to prioritize healthcare data routing in congested IoT networks. In our proposed system, we add a healthcare data identifier in IP packet header at the sensor level, modify QoS software at the network router level, and provide the highest priority to healthcare data packet routing based on the healthcare data identifier seen at router QoS. A prototype has been built and tested by using TI Launchpads. Test data shows that healthcare packets with an identifier can route to doctors at 80% less latency than healthcare packets routed without an identifier. Additionally, the proposed system saves medical diagnostic cost, and more importantly, reduces the risk of losing human lives. A shorter version of this analysis has also been presented to IEEE conference. The detail analysis in this paper opens up multiple avenues for further research.

This research considers the router allocation problem in situations with sensitive, highest-priority, and severe demand constraints. Examples include bespoke communication, masquerade communication, war, disasters, and various crises (political, social, etc.). Specifically, by introducing a network component called the scheduler. The scheduler is established to provide the intelligencers the highest priority to forwarding their packets based on their preferences at any time. Intelligencers define their preferences to control the data release time, due time, and static window transmission time-slot. Each window represents a reserved time-slot for the intelligencer. A window is an interval when the intelligencer can send data without any contention and can block any other user trying to gain access to the router during this interval. The reserved interval is called a “static urgent window pass”. For each block of the received data, the scheduler solves a scheduling problem with the windows reserved for the router based on the given constraints, which is an NP-hard problem. This work proposes eight heuristics based on dispatching with constraints, iterative randomization method, and subset-sum method to solve the studied problem. These heuristics are utilized by the two proposed algorithms to forward data from the sender to the receiver based on the specified constraints. The first algorithm prioritizes the set of packets to be sent and is called the “priority packet-based algorithm”. The second algorithm is called the “cumulative packet-based algorithm” and is based on the non-priority set of the remaining packets. At any time other than the specified window, the scheduler rearranges and reschedules all the remaining (non-scheduled) packets. Experimental results showed the performance of the proposed heuristics in terms of gap and time. In the performed experiments, the scheduler was capable to pass the router role and gain the control to send the required data based on the specified constraints.

In the era of dark silicon, several components on the chip [i.e., cores, memory, and network on chip (NoC)] need to be powered-off or run in low-power mode. This is mainly due to the increased leakage power consumption at smaller technology nodes. Other than the power consumed by cores and caches, power and performance of the interconnects is a significant factor as the communication network consumes a considerable share of the power budget. In particular, the buffers used at every port of the NoC router consume considerable dynamic as well as static power. To support dark silicon and save energy, a popular approach is to power off the routers and wake them up when needed. However, this affects the packet latency, and we need to observe the traffic through the nodes to decide turning the routers ON–OFF. In this article, we propose to keep the routers always powered ON to maintain constant connectivity and investigate various approaches. One proposal is to frequency scale the routers connected to powered OFF nodes, and the other proposals are to use a combination of SRAM and nonvolatile spin-transfer torque random access memory-based VCs in the routers. By managing which VCs to be active at a given time, we achieve energy savings. The proposals are evaluated by varying the percentage of dark nodes on the chip. The experimental results show that all proposals yield significant energy savings while maintaining connectivity.

Internet-of-Things or IoT technology becomes essential in everyday lives. The risk of security and privacy towards IoT devices, especially smarthomes IoT gateway device, becoming apparent as IoT technology progressed. The need for affordable, secure smarthome gateway device or router that smarthome user prefer. The problem of low-performance smarthome gateways was running security programs on top of smarthome gateway programs. This problem motivates the researcher designing a secure and efficient smarthome gateway using Raspberry Pi hardware as an affordable smarthome gateway device and able to run both smarthome gateways and security programs. In this research, researchers implemented snort as intrusion detection system (IDS), openHab as IoT gateway applications, and well-known encryption algorithms for file encryption in Raspberry PI 3B+ model. The researcher evaluated Snort capability on network attacks and compared each of the well-known encryption algorithm efficiency. From the result, we found Rasefiberry customized snort configuration for Raspberry pi 60 percent of the simulated network attacks. Twofish encryption algorithms were found to have best encryption time, throughput, and power consumption compared to other encryption algorithms in the research. Rasefiberry architecture successfully processes both lightweight security programs and Openhab smarthome gateway programs with a lowperformance computing device such as Raspberry Pi.

Data retrieval in Named Data Networking (NDN) is based on content names irrespective of their hosting location. The NDN architecture introduces original naming, forwarding and caching techniques to improve data delivery efficiency. These distinctive techniques make the TCP congestion control scheme not suitable for the NDN architecture. In particular, the in-network caching and the multi-path forwarding used in the NDN architecture lead to fluctuations in the Round Trip Time (RTT) measurements. This makes the Retransmission TimeOut (RTO) an unreliable congestion indicator. Thus, the congestion problem in Named Data Networks deserves to be reconsidered. In this paper, we present a new congestion control algorithm, called IRNA (Interest Rate Notification and Adjustment), to mitigate the congestion problem in Named Data Networks while maintaining per flow and per consumer fairness property. More specifically, IRNA is a hop-by-hop scheme where each router monitors the occupation level of its outgoing queues to detect in advance potential congestion events. When the queue size is above or below a preset threshold, the router sends explicit notifications to its downstream nodes to specify the appropriate interest rate. Hence, by cooperatively adjusting the Interest transmission rate of each node and for each flow, IRNA succeeded to provide a fair transmission. We evaluated the performance of our solution using ndnSIM simulations. We compared IRNA to state-of-the-art hop-by-hop congestion control solution and we proved that IRNA managed to provide a faster congestion reaction and to achieve per flow and per consumer throughput fairness while maintaining a good bandwidth usage.

With the substantial growth in vehicle population, the road safety problems, such as congestions and accidents, have become serious. To improve driving safety, efficient and rapid road safety data retrieval becomes a significant measure. As a new type of network, the named data networking (NDN) can effectively improve the data retrieval efficiency. Therefore, NDN might help improve the road safety data retrieval efficiency if it is introduced to the vehicular network, namely vehicular NDN. However, in the vehicular network, each vehicle works as a content router and high mobility of vehicles leads to frequent changes in network topology, which makes it hard to maintain forwarding information and achieve aggregation. Moreover, a large number of vehicles are involved in reverse paths, which leads to frequent reverse path disruptions and even data retrieval failures. To reduce the data retrieval latency and cost and improve the success rate, we propose an efficient road safety data retrieval approach that achieves push-based and pull-based data retrieval. In the approach, a forwarding network is constructed to improve the network stability. Based on the forwarding network, only a small number of vehicles are involved in pushing data, and consumers employ aggregation to pull data without depending on forwarding information. Moreover, the disrupted reverse paths can be effectively repaired to guarantee the successful receipt of data. Finally, this method is evaluated, and the experimental results show that it achieves the aforementioned objectives.

Content caching is an effective technique to alleviate the burden on backhaul links and reduce the traffic in cellular networks. In converged networks, broadcasting networks can push non-real-time popular services to different types of terminals during off-peak hours, while cellular networks are deployed to meet personalized needs. However, the storage capacity of terminals are usually limited. In this context, we study on the converged networks to push and cache the popular services in the router nodes close to the terminators. In this scheme, the most popular services are transmitted by the broadcasting base station and cached in the router nodes in a distributed cache network. Then, users can access the cached services in a more energy efficient manner. Due to the limited storage capacity of the router node, we assume that the user can access the cached services within two hops. Then, we formulate the service scheduling problem as a Markov Decision Process, aiming to maximize equivalent throughput (ET). Due to the large state space involved in the distributed cache network, it is quite challenging to obtain a tractable solution by the classical optimization algorithms. To handle this problem, a deep reinforcement learning based framework is proposed to tackle this problem. The simulation results show that the proposed algorithms are very effective; and they outperform the conventional one in term of the ET, especially when the users in the network subject to Poisson point process distribution.

Detailed routing is a dead-or-alive critical element in design automation tooling for advanced node enablement. However, very few works address detailed routing in the recent open literature, particularly in the context of modern industrial designs and a complete, end-to-end flow. The ISPD-2018 Initial Detailed Routing Contest addressed this gap for modern industrial designs, using a realistic design rules set. In this work, we present TritonRoute, a detailed router capable of delivering a DRC-clean routing solution. The key contributions of TritonRoute include an in-memory router database, along with an end-to-end detailed routing scheme that is capable of comprehending connectivity and design rule constraints, with every key detail revealed by a code release under a permissive open-source license. We evaluate our router using the official ISPD-2018 benchmark suite and show that TritonRoute achieves an unprecedented solution quality—improved wirelength and via count, and an extremely low level of design rule violations (DRCs). Compared to the known best detailed routing solutions from all published academic detailed routers, TritonRoute improves wirelength by up to 0.8% (avg. 0.4%), via count by up to 16.1% (avg. 9.3%), and DRCs by up to 100% (avg. 92.0%).

A large number of requests for internet access causes a long response time resulting in an overload problem. This problem occurs in offices that provide public services such as the Soeman HS Regional Library and Archives Office in Riau Province. So that service work is not disrupted due to overload, network optimization is carried out using Load Balancing Techniques. Load Balancing will balance load traffic on two or more connection lines so that traffic can run optimally. The method used is the Peer Connection Classifier (PCC). This method will divide the load based on the source, destination address, and port address. All internet requests from users will go to the router that has been configured with Load Balancing with the PCC method. The router will manage outgoing requests from users through the Internet Service Provider 1 (ISP 1) line or ISP line 2 to be able to enter the internet connection. The test results show equal distribution of outgoing access to ISP 1 and ISP 2 lines so that there is no overload on any ISP lines. This configuration will be applied to the Mikrotik router using the Winbox application.

The Internet is being extensively used in various fields to serve billions of users, which leads to the number of network security issues. Here, Internet Protocol Spoofing is considered the main threat for masquerade of the packet identity. An IP packet, which contains the header with the source IP address, lacks source verification. The invaders to spoof the network address of the packet use this vulnerability. To overcome this, verification of source is performed by marking the packets and tracing back to the source. Existing schemes make use of either packet marking or packet logging for trace back to the source with high computational and storage overhead. This paper proposed a scheme to minimize both the overheads by using a Combined IP Traceback procedure. Packet marking is done efficiently by using the 16-bit ID field of the packet header and packet logging is completed more effectively by using the hash table. The path reconstruction is done using the mark value in the packet, which traces back to the original source border router. The proposed method is empirically validated against the related ones.

Transmission control protocol (TCP) is the widely and dominantly used protocol in today’s internet. A very recent implementation of congestion control algorithm is BBR by Google. Bottleneck bandwidth and round-trip time (BBR) is a congestion control algorithm which is created with the aim of increasing throughput and reducing delay. The congestion control protocols mentioned previously try to determine congestion limits by filling router queues. BBR drains the router queues at the bottleneck by sending exactly at the bottleneck link rate. This is done by the BBR through pacing rate which infers the delivery rate of the receiver and uses this as the estimated bottleneck bandwidth. But when the data rate is high, in the startup phase itself pipe becomes full and leads to some degradation in the Access Point of wireless environments by inducing losses specific to this environment. So the current pacing rate is not suitable for producing higher throughputs. Therefore, in the proposed system named R-BBR, this startup gain should be lower than the current startup gain which eventually would reduce pacing rate to reduce queue pressure in the sink node during the startup phase. The startup phase of BBR is modified to solve the problem of pipe full under high data rate. R-BBR has been evaluated over a wide range of wired as well as wireless networks by varying different factors like startup gain, congestion window, and pacing rate. It is inferred that R-BBR performs better than BBR with significant performance improvement.

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.

Mobile ad hoc network (MANET) is an infrastructure-less, self-motivated, arbitrary, self-configuring, rapidly changing, multi-hop network that is self-possessing wireless bandwidth-conscious links without centrally managed router support. In such a network, wireless media is easy to snoop. It is firm to the surety to access any node, easier to insertion of bad elements or attackers for malicious activities in the network. Therefore, security issues become one of the significant considerations for such kind of networks. The deployment of an effective intrusion detection system is important in order to provide protection against various attacks. In this paper, a Digitally Signed Secure Acknowledgement Method (DSSAM) with the use of the RSA digital signature has been proposed and simulated. Three different parameters are considered, namely secure acknowledgment, node authentication, and packet authentication for study. This article observes the DSSAM performance and compares it with two existing standard methods, namely Watchdog and 2-ACK under standard Dynamic Source Routing (DSR) routing environment. In the end, it is noticed that the rate of detection of malicious behaviour is better in the case of the proposed method. However, associated overheads are high. A trade-off between performance and overhead has been considered.

Neuromorphic (NC) designs have gained significant interest in recent hardware research due to its low-power consumption. Low-power and low-latency router design is one of the most critical component to ensure NC hardware’s scalability and energy efficiency. Various router designs have been proposed to achieve high performance. However, this leads to complex router architectures and thus high area and power consumption. Furthermore, non-uniform traffic patterns of spiking neurons can cause network congestion and unnecessary power consumption. In this brief, we propose a congestion-aware routing algorithm to alleviate the congestion of routers in the middle and reduce network latency. Besides, a globally asynchronous, locally synchronous low-cost router architecture is deployed to relax the global clock tree constraint at chip level. Finally, a novel clock gating circuit is proposed to reduce the dynamic power consumption of routers. Our results show that averagely it reduces the router power consumption by more than 50%. The proposed router achieves ultra-low energy consumption of $2.3\times 10^{-2}$ pJ/bit and a small area of only 0.007 mm2.

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.

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.