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Unmanned aerial vehicles (UAVs) offer solutions to issues like traffic congestion and labor shortages. We developed a distributed UAV management system inspired by virtual circuit and datagram methods in packet-switching networks. By installing houses with wireless terminals, UAVs navigate routes in a multi-hop network, communicating with ground nodes. UAVs are treated as network packets, ground devices are treated as routers, and their connections are treated as links. Activating all nodes as relays increases control message traffic and node load. To optimize connectivity, we minimize relay nodes, connecting non-relay nodes to the nearest relay. This study proposes four relay node selection methods: random selection, two adjacency-based methods, and our innovative approach using Multipoint Relay (MPR) from the Optimized Link State Routing Protocol (OLSR). We evaluated these methods according to their route construction success rates, relay node counts, route lengths, and so on. The MPR-based method proved most effective for UAV route construction. However, fewer relay nodes increase link collisions, and we identify the minimum relay density needed to balance efficiency and conflict reduction. [ABSTRACT FROM AUTHOR]

Addressing the challenges of suboptimal model performance and excessive parameters and operations in the optimization of energy storage power plants utilizing Graph Convolutional Network (GCN), this paper introduces a novel approach – the packet-switched graph convolutional network. Initially, a GCN extreme learning machine is established. Drawing inspiration from this solid foundation, we have innovatively crafted a group exchange graph convolution module. This module leverages group graph convolution techniques to amalgamate unique node feature information, tailored to diverse topology graph matrices based on various groupings. This innovative approach ensures that information flows freely and effectively among distinct groupings. Furthermore, we have designed a cutting-edge timing depth separation convolution module, comprising two innovative components. The first component introduces timing depth separation convolution, revolutionizing the original timing convolution module. The second component, the packet-switching graph convolutional network, revolutionizes the time sequence depth separation convolution process. It achieves this by employing 1 × 1 convolutional layers between different feature fusion packets, enabling seamless information exchange between distinct packets. Experimental results demonstrate the efficacy of the proposed model, with root mean square error (RMSE) metrics and root mean square error (MAE) metrics for single-step prediction reaching 46.08 and 26.22 at 60 min, respectively. In multi-step testing, the proposed model exhibits a 14.71 % reduction in RMSE error at the 15-min scale and a 9.29 % reduction at the 60-min scale compared to the benchmark model. This performance improvement enhances the operational efficiency and reliability of the energy storage plant, particularly under dynamic changes in the time series.

Between MANET nodes as between Wireless Sensor Networks (WSN) nodes, route information is needed for the data packets sent by the sensor nodes to reach the target node. Route information is provided using proactive and reactive routing protocols, considering performance criteria such as efficiency, delay, packet transmission rate, packet drop rate and energy. In proactive routing protocols, route information is created on a table-based basis, while in reactive routing protocols, route information is created on a request basis. Change in speed as a mobility factor affects the performance of routing protocols positively or negatively. In this study, an experiment was carried out in the NS2 simulation environment on how AODV and DSR reactive routing protocols and DSDV proactive routing protocol perform at different selected speeds in efficiency, delay, packet transmission rate and packet drop rate metrics, and it is aimed to determine which one is the best performer. It is seen that the speed unit with the highest performance of the AODV protocol is 10 m/s (36 km/s), while the speed unit with the most performance of the DSDV and DSR protocols is 5 m/s (18 km/s). In addition, speed points between the selected speeds are also important in MANET. Due to this importance, performance measurements at 6, 7, 8 and 9 m/sec speeds are also presented with the same simulation parameters to be used future works, although they are not included in the comparison in the current study. [ABSTRACT FROM AUTHOR]

Currently, data traffic is growing rapidly, and ensuring optimal network performance and effective data flow management have become the most important tasks. In this context, the quality of network service plays a crucial role in achieving these goals. This article suggests an approach to solving the problem of efficient service in ISDN. Namely, optimization of resource distribution between channel switching and packet switching subnets in ISDN to calculate optimal quality of service characteristics. In the process of ISDN design analysis, an optimization problem is compiled, where the evaluation of the packet-switched subnet service is used as an objective function, and the evaluation of the circuit-switched subnet service is used as one of the constraints for this task. To calculate the main characteristics of a packetswitched subnet, the subnet is considered as a service system with a delay. During the study, the methods of optimal movement of the generalized channel boundary between the subnets of channel switching and packet switching were identified, depending on the data parameters and the state of the integrated network, which made it possible to develop an optimal mathematical model of optimal control of the generalized boundary. To calculate the bandwidth for channel switching and packet switching subnets, an algorithm has been compiled to implement the resulting model and a program in C++ has been compiled. The study of the generalized boundary and the dynamic redistribution of bandwidth between subnets represents a new approach to network optimization. The results are based on the use of the classical Erlang formula for systems with service failures and on load distribution plans, which makes it possible to effectively manage the maintenance process in the network. [ABSTRACT FROM AUTHOR]

Philosophers have long recognized the value of metaphor as a tool that opens new avenues of investigation. By seeing brains as having the goal of representation, the computer metaphor in its various guises has helped systems neuroscience approach a wide array of neuronal behaviors at small and large scales. Here I advocate a complementary metaphor, the internet. Adopting this metaphor shifts our focus from computing to communication, and from seeing neuronal signals as localized representational elements to seeing neuronal signals as traveling messages. In doing so, we can take advantage of a comparison with the internet's robust and efficient routing strategies to understand how the brain might meet the challenges of network communication. I lay out nine engineering strategies that help the internet solve routing challenges similar to those faced by brain networks. The internet metaphor helps us by reframing neuronal activity across the brain as, in part, a manifestation of routing, which may, in different parts of the system, resemble the internet more, less, or not at all. I describe suggestive evidence consistent with the brain's use of internet-like routing strategies and conclude that, even if empirical data do not directly implicate internet-like routing, the metaphor is valuable as a reference point for those investigating the difficult problem of network communication in the brain and in particular the problem of routing.

In this two-part article, I trace the history of the Internet. The Internet started in 1969 as an experiment by the Advanced Research Projects Agency (ARPA) of the US Department of Defense to use packet switching on leased telephone lines to connect four mainframe computers. Email was invented in 1971 and it became a "killer application" as it promoted easy interaction among its users. By 1972, fifty computers were connected using leased telephone lines to form what was known as the ARPANET which was successfully demonstrated at an international conference — ICCC 72. ARPANET was followed by Packet Radio Network (PRNET), which connected mobile computers, and Satellite Network (SATNET), which connected computers in Europe with those in the US. A protocol named Transmission Control Protocol/ Internet Protocol (TCP/IP) was invented in 1973 to interconnect ARPANET, PRNET, and SATNET. The success of the TCP/IP protocol in connecting disparate networks paved the way for the development of the Internet. [ABSTRACT FROM AUTHOR]

One of the most critical router’s functions is the IP lookup. For each incoming IP packet, IP lookup determines the output port to which the packet should be forwarded. IPv6 addresses are envisioned to replace IPv4 addresses because the IPv4 address space is exhausted. Therefore, modern IP routers need to support IPv6 lookup. Most of the existing IP lookup algorithms are adjusted for the IPv4 lookup, but not for the IPv6 lookup. Scalability represents the main problem in the existing IP lookup algorithms because the IPv6 address space is much larger than the IPv4 address space due to longer IPv6 addresses. In this paper, we propose a novel IPv6 lookup algorithm that supports very large IPv6 lookup tables and achieves high IP lookup throughput.

Considering the requirements of the space-integrated-ground information network, the technologies of on-board channelized switching and the technologies of on-board packet switching were surveyed.Among, the discussed channelized switching technologies include fl exible digital channelized switching and microwave photonic frequency conversion and switching, while the discussed packet switching technologies mainly include software-defi ned satellite network.Considering the future research directions of space networking and switching, the trends of on-board switching were discussed in terms of system capacity, reliability, effi ciency, and quality of service, which provided a reference for the long-term planning of the space-integrated-ground information network.

Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacities of the servers determine the partition by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are often also required for other tasks such as classification and routing. Previous work showed how to compute the smallest prefix-matching TCAM necessary to implement a given partition exactly. In this paper we solve the more practical case, where at most $n$ prefix-matching TCAM rules are available, restricting the ability to implement exactly the desired partition. We give simple and efficient algorithms to find $n$ rules that generate a partition closest in $L_\infty $ to the desired one. We do the same for a one-sided version of $L_\infty $ which equals to the maximum overload on a server and for a relative version of it. We use our algorithms to evaluate how the expected error changes as a function of the number of rules, the number of servers, and the width of the TCAM. [ABSTRACT FROM AUTHOR]

Many applications such as Industrial Internet of Things (IIoT), tactile Internet, and 5G/6G mobile require Ultra-Low Latency (ULL) in data transmission. The end-to-end latency is required to be on the order of sub-millisecond in these applications. The IEEE 802.1 Time Sensitive Networking (TSN) standards have been developed to provide ULL networking. The IEEE 802.1Qbv Time-Aware Shaper (TAS), which is a typical flow control mechanism of TSN, is a traffic shaper to provide deterministic end-to-end ULL transmission for express traffic. The Gate Control List (GCL) of all TAS enabled nodes must be configured in a coordinated manner to ensure ULL. However, existing configuration schemes cannot be employed in highly dynamic conditions where the distribution of time-sensitive streams frequently changes. It will be a significant problem to deal with such dynamic conditions in the future. Therefore, this paper proposes a real-time adaptive gate scheduling scheme for TAS. The scheduling problem is formulated as a boolean satisfiability problem (SAT), and the employment of an FPGA-based solver is proposed to achieve runtime fast computation. The proposed scheme enables real-time reconfiguration for high flexibility and high bandwidth utilization to deal with the dynamics of network conditions. The feasibility of the proposed scheme is confirmed with computer simulations.

Data center communication networks are characterized by fast and intensive traffic changes, to the extent that a statistical approach to routing has significant drawbacks. This paper proposes the first routing solution that takes into account every data center flow. In order to achieve the required performance, the proposed algorithm operates in the data plane, i.e. in the packet processing pipeline of the programmable packet forwarding chips. Route updates are triggered by the arrival of new flows, and are immediately transferred to the upstream switches in order for them to direct newly arriving flows along the best path. This enables the proposed algorithm to handle fast and intensive traffic changes, such as large-scale flow incast communication patterns which historically presented challenges to the data center routing algorithms. With the explicit knowledge of the current path state, the proposed algorithm can improve routing performance in the data center topologies used today. Additionally, being able to operate with high performance in arbitrary topology, the proposed solution can enable the introduction of new topologies into the data center networks, instead of topologies designed with the goal of supporting equal-cost multipath routing which are dominant in modern data centers.

In large data center, virtual machines are connected dynamically and data are moved between the physical machines and the virtual machines. With this environment, the Network Layer transfers the packets to the Transport Layer. To improve the security and to increase the speed of the packet transmission in the network layer, packet-filtering is carried out by firewalls based on the decision of routers namely Network addresses, Ports or Protocols. Earlier packet filtering techniques are IP data-gram, Queuing and Scheduling. In order to overcome the limitation in security mechanisms in the above filtering techniques, hashing algorithms are used for analyzing the elements in the packets that are stored in the Hash tables. The hashing algorithms are used in Quotient filter, Bloom filter, Cuckoo filter and Adaptive Cuckoo Filter (ACF). AMDS is termed as An Approximate Membership Data Structures were used to store the fingerprints in cuckoo hash tables. In this paper an attempt is made to improve the searching strategy in Cuckoo filter. Spring constant factor and Leivy Flight theorem is introduced in the searching strategy for best solution identification path. A suit of benchmark functions are employed to verify the performance of network with respect to time, speed and the memory space in the packets transmission. The performance of the Enhanced searching strategy gives better result when compared to ACF. [ABSTRACT FROM AUTHOR]

5G cellular IoT has several advantages compared to other access technologies, enabling operators to serve a wider area and more IoT devices. However, in the urban transportation system, a massive number of vehicles exhaust the available resources in the cell, resulting in excessive load in the 5G cellular network. This article proposes a novel reinforcement learning based V2V routing (RLbR) framework, which offloads non‐realtime traffic into the V2V network and significantly relieves the load of 5G cellular network. Meanwhile, we propose a V2V routing algorithm. Specifically, the Q‐values of neighbouring vehicles are firstly calculated according to the cache factor CF and energy factor EF and evaluate the quality of neighbouring vehicles. Then, the position factor PF is calculated, based on which, the vehicle forwards the data packet. In addition, an environment model is designed to accelerate the convergence of Q‐table. The results show that the RLbR framework brings the highest offload rate compared to the other three frameworks, and simultaneously, the proposed algorithm improves the lifetime of the V2V network and performs well in terms of delivery ratio and average delay. [ABSTRACT FROM AUTHOR]

Internet traffic is still exhibiting an exponential growth. This exponential growth will certainly be continued given the Internet of Things (IoT) and Internet of Everything (IoE) predictions regarding the number of devices connected to the Internet in the near future. Also, many popular multicast services such as IPTV, distance learning, content distribution, distributive interactive gaming, collaborative computing and others are rapidly increasing amount of the Internet multicast traffic, thus, significantly contributing to the Internet traffic growth. The routers are typically designed to cope with unicast traffic. Multicast traffic can negatively impact performance of such routers and cause significant degradation of overall network performance. Hence, due to increasing importance and increasing amount of multicast traffic, there is a great need for a scalable switch architecture that efficiently forwards both unicast and multicast traffic. In this paper, we propose a novel scalable, efficient and frugal multicast switch architecture based on load balanced Birkhoff-von Neumann switch with greedy scheduling that achieves stable performance even at very high traffic loads. The proposed switch is compared to other popular multicast switch solutions. Comparison shows that our proposed multicast switch architecture outperforms other solutions in all tested common traffic scenarios at the most critical (highest) traffic loads.

The appeal for more reliable, efficient and resilient power grids has become indispensable with the recent technological development and ever-increasing demand for electrical energy. These goals might be achieved by introducing sensors and actuators in the power grid, with the purpose of enabling a smart control of the power network. All power devices must be connected using a reliable communication network, which should be able to operate even when the power grid fails. Currently, several communication technologies have been applied for supporting this new application scenario. This article aims for reviewing both academic and market use cases for technologies applied to the mission-critical, control networks and Smart Grid applications, such as teleprotection, self-healing, communication with control centers and field devices, among others. More specifically, the key aspects, potential technologies, main protocols and use cases of operating data networks in energy transmission, power distribution and smart grid environments, including circuit and packet switching technologies, are discussed into details. Furthermore, resilience and the main telecommunications technologies used in power grids, as well, the correlation among them, are exploited in practical point of view. The article provides a broad discussion on the best telecommunication options to build the emerging intelligent energy distribution systems, covering control networks, teleprotection, and smart grid applications.

By the introduction of all IP networks with the smart homes, smart phones, car multimedia systems wearable technologies and IP TV’s, the number of internet related devices and the number of applications have increased. This has generated an increased quantity of bandwidth usage in packet switching networks. Therefore, the betterment of the bandwidth usage and the system performance has become more significant. Thus, there is a large number of works in the literature attempting to improve the network performance. For this purpose, generally the modifications of used methods in the network structures are preferred, rather than making major hardware based modifications requiring more financial support. In this work, a novel method called Return Back to threshold (RBT) is proposed to be applied to packet switched networks for a better congestion control.

In this paper, a packet switch architecture for mesh-connected multiprocessors based on the use of a set of in-put FIFO buffers and an output register matrix controlled by a novel distributed timing-based scheduling scheme is proposed. Simple static routing is assumed, with each packet split into a set of independently routed w-bit-wide flits. The device achieves at least 78% throughput for uniformly distributed traffic and an asymptot-ic higher bound of 100%. In contrast to the state-of-the-art VOQ-based switch architectures, the proposed switch is shown to reach its maximum throughput with no internal speedup required and has an order of mag-nitude lower hardware complexity. Compared to existing buffered crossbar non-VOQ switches with typical flit scheduling mechanisms, the proposed device demonstrates slightly higher throughput and substantially short-er delays in some practically important cases.

One of the most critical router's functions is the IP lookup. For each incoming IP packet, IP lookup determines the output port to which the packet should be forwarded. IPv6 addresses are envisioned to replace IPv4 addresses because the IPv4 address space is exhausted. Therefore, modern IP routers need to support IPv6 lookup. Most of the existing IP lookup algorithms are adjusted for the IPv4 lookup, but not for the IPv6 lookup. Scalability represents the main problem in the existing IP lookup algorithms because the IPv6 address space is much larger than the IPv4 address space due to longer IPv6 addresses. In this paper, we propose a novel IPv6 lookup algorithm that supports very large IPv6 lookup tables and achieves high IP lookup throughput. [ABSTRACT FROM AUTHOR]

Computational studies in network neuroscience build models of communication dynamics in the connectome that help us understand the structure-function relationships of the brain. In these models, the dynamics of cortical signal transmission in brain networks are approximated with simple propagation strategies such as random walks and shortest path routing. Furthermore, the signal transmission dynamics in brain networks can be associated with the switching architectures of engineered communication systems (e.g., message switching and packet switching). However, it has been unclear how propagation strategies and switching architectures are related in models of brain network communication. Here, we investigate the effects of the difference between packet switching and message switching (i.e., whether signals are packetized or not) on the transmission completion time of propagation strategies when simulating signal propagation in mammalian brain networks. The results show that packetization in the connectome with hubs increases the time of the random walk strategy and does not change that of the shortest path strategy, but decreases that of more plausible strategies for brain networks that balance between communication speed and information requirements. This finding suggests an advantage of packet-switched communication in the connectome and provides new insights into modeling the communication dynamics in brain networks., Competing Interests: Competing Interests: The authors have declared that no competing interests exist., (© 2024 Massachusetts Institute of Technology.)

Achieving low end-to-end latency with high reliability is one of the key objectives for future mission-critical applications, like the Tactile Internet and real-time interactive Virtual/Augmented Reality (VR/AR). To serve the purpose, cut-through (CT) switching is a promising approach to significantly reduce the transmission delay of store-and-forward switching, via flit-ization of a packet and concurrent forwarding of the flits belonging to the same packet. CT switching, however, has been applied only to well-controlled scenarios like network-on-chip and data center networks, and hence flit scheduling in heterogeneous environments (e.g., the Internet and wide area network) has been given little attention. This paper tries to fill the gap to facilitate the adoption of CT switching in the general-purpose data networks. In particular, we first introduce a packet discarding technique that sheds the packet expected to violate its delay requirement and then propose two flit scheduling algorithms, f EDF (flit-based Earliest Deadline First) and f SPF (flit-based Shortest Processing-time First), aiming at enhancing both reliability and end-to-end latency. Considering packet delivery ratio (PDR) as a reliability metric, we performed extensive simulations to show that the proposed scheduling algorithms can enhance PDR by up to 30.11% (when the delay requirement is 7 ms) and the average end-to-end latency by up to 13.86% (when the delay requirement is 10 ms), against first-in first-out (FIFO) scheduling.

Communication specialists all around the world are facing the same problem: shifting from circuit switching (CS) to packet switching (PS). Communication service providers are favoring “All-over-IP” technologies hoping to boost their profits by providing multimedia services. The main stakeholder in this field of the paradigm shift is the industry itself: packet switching hardware manufacturers are going to earn billions of dollars and thus pay engineers and journalists many millions for the promotion of the new paradigm. However, this drive for profit is tempered by life itself. This article is devoted to the discussion of the telecommunications development strategy. We will provide examples to illustrate the difficulties that complicate the transition from CS to PS and the move to hybrid CS+PS solutions. We are considering three areas: (1) network-on-a-chip (NoC), (2) the telecom strategy: how to build the core of the network, (3) the transition of the U.S. Defense Information System Network from SS7 signaling to IP protocol.

The categorisation of network packets according to multiple parameters such as sender and receiver addresses is called packet classification. Packet classification lies at the core of Software‐Defined Networking (SDN)‐based network applications. Due to the increasing speed of network traffic, there is an urgent need for packet classification at higher speeds. Although it is possible to accelerate packet classification algorithms through hardware implementation, this solution imposes high costs and offers limited development capacity. On the other hand, current software methods to solve this problem are relatively slow. A practical solution to this problem is to parallelise packet classification using multi‐core processors. In this study, the Thread, parallel patterns library (PPL), open multi‐processing (OpenMP), and threading building blocks (TBB) libraries are examined and implemented to parallelise three packet classification algorithms, i.e. tuple space search, tuple pruning search, and hierarchical tree. According to the results, the type of algorithm and rulesets may influence the performance of parallelisation libraries. In general, the TBB‐based method shows the best performance among parallelisation libraries due to using a theft mechanism and can accelerate the classification process up to 8.3 times on a system with a quad‐core processor. [ABSTRACT FROM AUTHOR]

Network flow fingerprinting can be used to de-anonymize communications on anonymity systems such as Tor by linking the ingress and egress segments of anonymized connections. Assume Alice and Bob have access to the input and the output links of an anonymous network, respectively, and they wish to collaboratively reveal the connections between the input and the output links without being detected by Willie who protects the network. Alice generates a codebook where each codeword is a unique fingerprint indicating a sequence of inter-packet delays, and shares it only with Bob. To trace each flow, Alice selects a fingerprint and manipulates the packet timings of the flow to follow the packet timings suggested by the fingerprint, and Bob extracts the fingerprints from it after it passes through the network. We model the network as parallel $M/M/1$ queues where each queue is shared by a flow $f_{i}$ from Alice to Bob and other flows independent of $f_{i}$. Packet timings of the flows are governed by independent Poisson processes. Assuming all input flows have equal packet rates and that Bob observes only flows with fingerprints, we first present two scenarios: 1) Alice fingerprints all the flows and 2) Alice fingerprints a subset of the flows, unknown to Willie. Then, we extend the construction and analysis to the case of arbitrary flow rates and the case where Bob observes flows with and without fingerprints. For each scenario, we derive the number of flows that Alice and Bob can trace by fingerprinting. [ABSTRACT FROM AUTHOR]

One of the most established and well-known standards for packet switched networks are the international standard X.25, The X.25 Recommendation defines the interface requirements between the user equipment (such as a terminal, bridge, router, and computer) and a packet switching network for data exchange X.25 network provides an efficient way to transfer data within one region, the country and even all over the world. The synchronous data transfer with a speed of up to 64 Kbps. The X.25 standards provides automatic error detection and correction, which allows X.25 networks to work effectively even in regions where the quality of communication lines is low. The X.25 interface provides Access to the remote user to the host computer (host). The X.25 standard describes the interface between the data entry equipment - DTE (Data Terminal Equipment) and data network equipment - DCE (Data Circuit terminating Equipment). Bridges, routers, terminals, personal computers (PCs), workstations are an example of equipment that can function as a (DTE). When it is connected to a packet switched network. DTE provides the user part of the usernetwork interface. The equipment to which the DTE is connected is called DCE. DCE provides the network part of the user-network interface. Each DTE has its own DCE. However, several DTE devices can be connected to the same DCE. DTEDTE connection is invalid; communication is only possible between DTE-DCE and DCE-DCE. [ABSTRACT FROM AUTHOR]

We propose and experimentally demonstrate a Software-Defined Network (SDN) enabled Hybrid Polling Algorithm for packet Contention Resolution (HPACR) in optical Data Center Network (DCN) based on Fast Optical Switches (FOS). Fast Semiconductor Optical Amplifier (SOA)-based buffer-less FOS with nanoseconds reconfiguration time are employed for interconnecting Top-Of-the Racks (TORs) switches with distributed flow control. Under the realistic 10 Gb/s server traffic, the network performance of the DCN employing the proposed HPACR algorithm is experimentally assessed. Results show that the HPACR increases 13.6% throughput at the high load of 1.0 and decreases the 75% contention ratio for the load >0.5 with respect to the traditional packet contention resolution methods. Based on the experimental parameters, a simulation platform is built to numerically evaluate the HPACR performance of DCN with 64 TORs connecting 1280 servers. The results show that HPACR improves the system performance by increasing the throughput by 5% compared with existing algorithms, reducing the TOR-to-TOR latency by 18.5%, and decreasing the packet loss by 14.1% at the load of 1. [ABSTRACT FROM AUTHOR]

Summary: Burst traffic is a common traffic pattern in modern IP networks, and it may lead to the unfairness problem and seriously degrade the performance of switches and routers. From the perspective of switching mechanism, the majority of commercial switches adopt the on‐chip shared‐memory switching architecture, and high‐speed packet buffer with efficient queue management is required to deal with the unfairness and congestion problem. In this paper, the performance of a shared‐private buffer management scheme is analyzed in detail. In the proposed scheme, the total memory space is split into shared area and private area. Each output port has a private memory area that cannot be used by other ports. The shared area is completely shared among all output ports. A theoretical queuing model of the proposed scheme is formulated, and closed‐form formulas for multiple performance parameters are derived. Through the numerical studies, we demonstrate that a nearly optimal buffer partition policy can be obtained by setting an equally small amount of private area for each queue. This work is validated by simulations as well as hardware experiments. Software simulations show that the proposed scheme performs better than existing methods, and packet dropping caused by burst traffic can be significantly reduced. Besides, a prototype of the buffer management module is implemented and evaluated in field programmable gate array platform. The evaluation shows that the proposed scheme can ensure the efficiency and fairness while keeping a high throughput in real workload. [ABSTRACT FROM AUTHOR]

With the advent of new technologies, such as software-defined networks (SDN) and fog computing, and the development of communication technology and the vehicular industry, there has been a remarkable growth in intelligent transportation systems (ITS) in recent years. As a main component of ITS, vehicular ad hoc networks (VANETs) suffer from a host of problems, including architectural inflexibility, wireless communication instability, limited range of communications, and frequent topological changes due to the rapid mobility of vehicles. One of the challenges in vehicular ad hoc networks is the lack of efficient and reliable communication between vehicles. Also, given the huge amounts of data production and big data, the communication capabilities of vehicles can be utilized to effectively transmit and communicate data, thus reducing excessive bandwidth usage in internet networks and their infrastructure. The current paper's aim is to present a method for improving the transmission of data packets in inter-vehicle communications. In this regard, software-defined networks and fog-based computing offer substantial benefits. The proposed routing method includes the switching of data packet transmission through the VANET infrastructure and internet transmission. SDN- and Fog computing-based Switchable Routing (SFSR) provides the best path for the inter-vehicle transmission of data packets. When data packet transmission via VANETs is not possible, transmission may be performed via internet. The results of the simulation indicate improved performance of SFSR in terms of the packet delivery ratio, packet loss ratio, end-to-end delay, routing overhead, and routing failure rate. [ABSTRACT FROM AUTHOR]

Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacity of each server or path implies the distribution by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power hungry and are often also required for other tasks such as classification and routing. For splitting a universe of $2^{W}$ addresses into $k$ pieces of particular sizes, we give a simple algorithm that computes an optimal representation in $O(Wk)$ time. Furthermore, we prove that a recently published load balancer, called Niagara, which runs in $O(Wk\log k)$ time is in fact optimal. That is, both our algorithm and Niagara produce the smallest possible TCAM that splits the traffic exactly to the required pieces, where the only previously known algorithm for computing optimal exact representation has running time exponential in $k$. Finally, we use these optimal algorithms to experimentally study the number of TCAM rules required to split traffic in typical scenarios. [ABSTRACT FROM AUTHOR]

Internet traffic continues to grow relentlessly, driven largely by increasingly high resolution video content. Although studies have shown that the majority of packets processed by Internet routers are pass-through traffic, they nonetheless have to be queued and routed at every hop in current networks, which unnecessarily adds substantial delays and processing costs. Such pass-through traffic can be better circuit-switched through the underlying optical transport network by means of pre-established circuits, which is possible in a unified packet and circuit switched network. In this paper, we propose a novel convex optimization framework based on a new destination-based multicommodity flow formulation for the allocation of circuits in such unified networks. In particular, we consider two deployment settings, one based on real-time traffic monitoring, and the other relying upon history-based traffic predictions. In both cases, we formulate global network optimization objectives as concave functions that capture the fair sharing of network capacity among competing traffic flows. The convexity of our problem formulations ensures globally optimal solutions. [ABSTRACT FROM AUTHOR]

We experimentally and theoretically investigate the wavelength switching dynamics of an injection-seeded Er doped fiber ring laser. The fiber ring laser is seeded by an external cavity laser diode that is amplitude modulated with a long period 50% duty cycle wave form so that the return to steady state can be investigated. It is found that the laser suffers from severe large-amplitude relaxation oscillations and slow decay times that limit the available wavelength switching speed. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distributed computing power on the grid to apply a hybrid local search to each individual in the population and reach a near optimal solution in a reduced number of generations. Ant colony systems and simulated annealing are used to apply a combination of iterative and cooperative local searches, respectively. This algorithm is implemented using a master–slave scheme, where the master process distributes the population on the slave process and coordinates the communication on the computational grid elements. The experimental results point out that the proposed scheme obtains the upper bound in a broad set of test instances. Also, an efficiency analysis of the proposed algorithm indicates its competitive use of the computational resources of the grid.