Biblio

With the development of IoT and 5G networks, the demand for the next-generation intelligent transportation system has been growing at a rapid pace. Dynamic mapping has been considered one of the key technologies to reduce traffic accidents and congestion in the intelligent transportation system. However, as the number of vehicles keeps growing, a huge volume of mapping traffic may overload the central cloud, leading to serious performance degradation. In this paper, we propose and prototype a CUPS (control and user plane separation)-based edge computing architecture for the dynamic mapping and quantify its benefits by prototyping. There are a couple of merits of our proposal: (i) we can mitigate the overhead of the networks and central cloud because we only need to abstract and send global dynamic mapping information from the edge servers to the central cloud; (ii) we can reduce the response latency since the dynamic mapping traffic can be isolated from other data traffic by being generated and distributed from a local edge server that is deployed closer to the vehicles than the central server in cloud. The capabilities of our system have been quantified. The experimental results have shown our system achieves throughput improvement by more than four times, and response latency reduction by 67.8% compared to the conventional central cloud-based approach. Although these results are still obtained from the preliminary evaluations using our prototype system, we believe that our proposed architecture gives insight into how we utilize CUPS and edge computing to enable efficient dynamic mapping applications.

Software Defined Networking (SDN) provides opportunities for flexible and dynamic traffic engineering. However, in current SDN systems, routing strategies are based on traditional mechanisms which lack in real-time modification and less efficient resource utilization. To overcome these limitations, deep learning is used in this paper to improve the routing computation in SDN. This paper proposes Convolutional Deep Reinforcement Learning (CoDRL) model which is based on deep reinforcement learning agent for routing optimization in SDN to minimize the mean network delay and packet loss rate. The CoDRL model consists of Deep Deterministic Policy Gradients (DDPG) deep agent coupled with Convolution layer. The proposed model tends to automatically adapts the dynamic packet routing using network data obtained through the SDN controller, and provides the routing configuration that attempts to reduce network congestion and minimize the mean network delay. Hence, the proposed deep agent exhibits good convergence towards providing routing configurations that improves the network performance.

The major challenge of Real Time Protocol is to balance efficiency and fairness over limited bandwidth. MPTCP has proved to be effective for multimedia and real time networks. Ideally, an MPTCP sender should couple the subflows sharing the bottleneck link to provide TCP friendliness. However, existing shared bottleneck detection scheme either utilize end-to-end delay without consideration of multiple bottleneck scenario, or identify subflows on switch at the expense of operation overhead. In this paper, we propose a lightweight yet accurate approach, EMPTCP, to detect shared bottleneck. EMPTCP uses the widely deployed ECN scheme to capture the real congestion state of shared bottleneck, while at the same time can be transparently utilized by various enhanced MPTCP protocols. Through theory analysis, simulation test and real network experiment, we show that EMPTCP achieves higher than 90% accuracy in shared bottleneck detection, thus improving the network efficiency and fairness.

In this paper, we propose a robust Nash strategy for a class of uncertain Markov jump delay stochastic systems (UMJDSSs) via static output feedback (SOF). After establishing the extended bounded real lemma for UMJDSS, the conditions for the existence of a robust Nash strategy set are determined by means of cross coupled stochastic matrix inequalities (CCSMIs). In order to solve the SOF problem, an heuristic algorithm is developed based on the algebraic equations and the linear matrix inequalities (LMIs). In particular, it is shown that robust convergence is guaranteed under a new convergence condition. Finally, a practical numerical example based on the congestion control for active queue management is provided to demonstrate the reliability and usefulness of the proposed design scheme.

Optical burst switching (OBS) is a candidate switching paradigm for future backbone all-optical networks. However, data burst contention can be a major problem especially as the number of lightpath connections as well as the overall network radius increases. Furthermore, the absence of or limited buffering provision in core nodes, coupled with the standard one-way resources signaling aggravate contention occurrences resulting in some of the contending bursts being discarded as a consequence. Contention avoidance as well as resolution measures can be applied in such networks in order to resolve any contention issues. In that way, the offered quality of service (QoS) as well as the network performance will remain consistent and reliable. In particular, to maintain the cost effectiveness of OBS deployment, restricted intermediate buffering can be implemented to buffer contending bursts that have already traversed much of the network on their way to the intended destination. Hence in this paper we propose and analyze a restricted intermediate Node Buffering-based routing and wavelength assignment scheme (RI-RWA) scheme to address contention occurrences as well as prevent deletion of contending bursts. The scheme primarily prioritizes the selection of primary as well as deflection paths for establishing lightpath connections paths as a function of individual wavelength contention performances. It further facilitates and allows partial intermediate buffering provisioning for any data bursts that encounter contention after having already propagated more than half the network's diameter. We evaluate the scheme's performance by simulation and obtained results show that the scheme indeed does improve on key network performance metrics such as fairness, load balancing as well as throughput.

Coupling regular topologies with optimized routing algorithms is key in pushing the performance of interconnection networks of HPC systems. In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under massive topology degradation caused by equipment failure. It applies a modulo-based computation of forwarding tables among switches closer to the destination, using only knowledge of subtrees for pre-modulo division. Dmodc allows complete re-routing of topologies with tens of thousands of nodes in less than a second, which greatly helps centralized fabric management react to faults with high-quality routing tables and no impact to running applications in current and future very large-scale HPC clusters. We compare Dmodc against routing algorithms available in the InfiniBand control software (OpenSM) first for routing execution time to show feasibility at scale, and then for congestion risk under degradation to demonstrate robustness. The latter comparison is done using static analysis of routing tables under random permutation (RP), shift permutation (SP) and all-to-all (A2A) traffic patterns. Results for Dmodc show A2A and RP congestion risks similar under heavy degradation as the most stable algorithms compared, and near-optimal SP congestion risk up to 1% of random degradation.

In multi-tenant datacenters, the hardware may be homogeneous but the traffic often is not. For instance, customers who pay an equal amount of money can get an unequal share of the bottleneck capacity when they do not open the same number of TCP connections. To address this problem, several recent proposals try to manipulate the traffic that TCP sends from the VMs. VCC and AC/DC are two new mechanisms that let the hypervisor control traffic by influencing the TCP receiver window (rwnd). This avoids changing the guest OS, but has limitations (it is not possible to make TCP increase its rate faster than it normally would). Seawall, on the other hand, completely rewrites TCP's congestion control, achieving fairness but requiring significant changes to both the hypervisor and the guest OS. There seems to be a need for a middle ground: a method to control TCP's sending rate without requiring a complete redesign of its congestion control. We introduce a minimally-invasive solution that is flexible enough to cater for needs ranging from weighted fairness in multi-tenant datacenters to potentially offering Internet-wide benefits from reduced interflow competition.

Selecting the best path in multi-path heterogeneous networks is challenging. Multi-path TCP uses by default a scheduler that selects the path with the minimum round trip time (minRTT). A well-known problem is head-of-line blocking at the receiver when packets arrive out of order on different paths. We shed light on another issue that occurs if scheduling have to deal with deep queues in the network. First, we highlight the relevance by a real-world experiment in cellular networks that often deploy deep queues. Second, we elaborate on the issues with minRTT scheduling and deep queues in a simplified network to illustrate the root causes; namely the interaction of the minRTT scheduler and loss-based congestion control that causes extensive bufferbloat at network elements and distorts RTT measurement. This results in extraordinary large buffer sizes for full utilization. Finally, we discuss mitigation techniques and show how alternative congestion control algorithms mitigate the effect.

With the development of modern High-Speed Railway (HSR) and mobile communication systems, network operators have a strong demand to provide high-quality on-board Internet services for HSR passengers. Multi-path TCP (MPTCP) provides a potential solution to aggregate available network bandwidth, greatly overcoming throughout degradation and severe jitter using single transmission path during the high-speed train moving. However, the choose of MPTCP algorithms, i.e., Coupled or Uncoupled, has a great impact on the performance. In this paper, we investigate this interesting issue in the practical datasets along multiple HSR lines. Particularly, we collect the first-hand network datasets and analyze the characteristics and category of traffic flows. Based on this statistics, we measure and analyze the transmission performance for both mice flows and elephant ones with different MPTCP congestion control algorithms in HSR scenarios. The simulation results show that, by comparing with the coupled MPTCP algorithms, i.e., Fully Coupled and LIA, the uncoupled EWTCP algorithm provides more stable throughput and balances congestion window distribution, more suitable for the HSR scenario for elephant flows. This work provides significant reference for the development of on-board devices in HSR network systems.

Naval Battlefield Network communications rely on wireless network technologies to transmit data between different naval entities, such as ships and shore nodes. Existing naval battle networks heavily depend on the satellite communication system using single-path TCP for reliable, non-interactive data. While satisfactory for traditional use cases, this communication model may be inadequate for outlier cases, such as those arising from satellite failure and wireless signal outage. To promote network stability and assurance in such scenarios, the addition of unmanned aerial vehicles to function as relay points can complement network connectivity and alleviate potential strains in adverse conditions. The inherent mobility of aerial vehicles coupled with existing source node movements, however, leads to frequent network handovers with non-negligible overhead and communication interruption, particularly in the present single-path model. In this paper, we propose a solution based on multi-path TCP and software-defined networking, which, when applied to mobile wireless heterogeneous networks, reduces the network handover delay and improves the total throughput for transmissions among various naval entities at sea and littoral. In case of single link failure, the presence of a connectable relay point maintains TCP connectivity and reduces the risk of service interruption. To validate feasibility and to evaluate performance of our solution, we constructed a Mininet- WiFi emulation testbed. Compared against single-path TCP communication methods, execution of the testbed when configured to use multi-path TCP and UAV relays yields demonstrably more stable network handovers with relatively low overhead, greater reliability of network connectivity, and higher overall end-to-end throughput. Because the SDN global controller dynamically adjusts allocations per user, the solution effectively eliminates link congestion and promotes more efficient bandwidth utilization.

Opportunistic spectrum access is one of the emerging techniques for maximizing throughput in congested bands and is enabled by predicting idle slots in spectrum. We propose a kernel-based reinforcement learning approach coupled with a novel budget-constrained sparsification technique that efficiently captures the environment to find the best channel access actions. This approach allows learning and planning over the intrinsic state-action space and extends well to large state spaces. We apply our methods to evaluate coexistence of a reinforcement learning-based radio with a multi-channel adversarial radio and a single-channel carrier-sense multiple-access with collision avoidance (CSMA-CA) radio. Numerical experiments show the performance gains over carrier-sense systems.

The idea to use multiple paths to transport TCP traffic seems very attractive due to its potential benefits it may offer for both redundancy and better utilization of available resources by load balancing. Fixed and mobile network providers employ frequently load-balancers that use multiple paths on either per-flow or per-destination level, but very seldom on per-packet level. Despite of the benefits of packet-level load balancing mechanisms (e.g., low computational complexity and high bandwidth utilization) network providers can't use them mainly because of TCP packet reorderings that harm TCP performance. Emerging network architectures also support multiple paths, but they face with the same obstacle in balancing their load to multiple paths. Indeed, packet level load balancing research is paralyzed by the reordering vulnerability of TCP.A couple of TCP variants exist that deal with TCP packet reordering problem, but due to lack of end-to-end transparency they were not widely deployed and adopted. In this paper, we revisit TCP's packet reorderings problem and present a transparent and light-weight algorithm, Out-of-Order Robustness for TCP with Transparent Acknowledgment (ACK) Intervention (ORTA), to deal with out-of-order deliveries.ORTA works as a transparent thin layer below TCP and hides harmful side-effects of packet-level load balancing. ORTA monitors all TCP flow packets and uses ACK traffic shaping, without any modifications to either TCP sender or receiver sides. Since it is transparent to TCP end-points, it can be easily deployed on TCP sender end-hosts (EHs), gateway (GW) routers, or access points (APs). ORTA opens a door for network providers to use per-packet load balancing.The proposed ORTA algorithm is implemented and tested in NS-2. The results show that ORTA can prevent TCP performance decrease when per-packet load balancing is used.

In this paper, according to the electricity business process including collecting and transmitting power information and sending control instructions, a coupling model of control-communication flow is built which is composed of three main matrices: control-communication, communication-communication, communication-control incidence matrices. Furthermore, the effective path change between two communication nodes is analyzed and a calculation method of connectivity probability for information network is proposed when considering a breakdown in communication links. Then, based on Bayesian conditional probability theory, the effect of the communication interruption on the energy Internet is analyzed and the metric matrix of controllability is given under communication congestion. Several cases are given in the final of paper to verify the effectiveness of the proposed method for calculating controllability matrix by considering different link interruption scenarios. This probability index can be regarded as a quantitative measure of the controllability of the power service based on the communication transmission instructions, which can be used in the power business decision-making in order to improve the control reliability of the energy Internet.

Congestion diffusion resulting from the coupling by resource competing is a kind of typical failure propagation in network systems. The existing models of failure propagation mainly focused on the coupling by direct physical connection between nodes, the most efficiency path, or dependence group, while the coupling by resource competing is ignored. In this paper, a model of network congestion diffusion with resource competing is proposed. With the analysis of the similarities to resource competing in biomolecular network, the model describing the dynamic changing process of biomolecule concentration based on titration mechanism provides reference for our model. Then the innovation on titration mechanism is proposed to describe the dynamic changing process of link load in networks, and a novel congestion model is proposed. By this model, the global congestion can be evaluated. Simulations show that network congestion with resource competing can be obtained from our model.

In recent years, integration of Passive Optical Net-work(PON) and WiMAX (Worldwide Interoperability Microwave Access Network) network is attracting huge interest among many researchers. The continuous demand for large bandwidths with wider coverage area are the key drivers to this technology. This integration has led to high speed and cost efficient solution for internet accessibility. This paper investigates the issues related to traffic grooming, routing and resource allocation in the hybrid networks. The Elastic Optical Network forms Backbone and is integrated with WiMAX. In this novel approach, traffic grooming is carried out using light trail technique to minimize the bandwidth blocking ratio and also reduce the network resource consumption. The simulation is performed on different network topologies, where in the traffic is routed through three modes namely the pure Wireless Network, the Wireless-Optical/Optical-Wireless Network, the pure Optical Network keeping the network congestion in mind. The results confirm reduction in bandwidth blocking ratio in all the given networks coupled with minimum network resource utilization.

We have proposed the Media Access Control method based on the Synchronization Phenomena of coupled oscillators (SP-MAC) to improve a total throughput of wireless terminals connected to a Access Point. SP-MAC can avoid the collision of data frames that occur by applying Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) based on IEEE 802.11 in Wireless local area networks (WLAN). Furthermore, a new throughput guarantee control method based on SP-MAC has been proposed. This method enable each terminal not only to avoid the collision of frames but also to obtain the requested throughput by adjusting the parameters of SP-MAC. In this paper, we propose a new throughput control method that realizes the fairness among groups of terminals that use the different TCP versions, by taking the advantage of our method that is able to change acquired throughput by adjusting parameters. Moreover, we confirm the effectiveness of the proposed method by the simulation evaluation.

We present ctrlTCP, a method to combine the congestion controls of multiple TCP connections. In contrast to the previous methods such as the Congestion Manager, ctrlTCP can couple all TCP flows that leave one sender, traverse a common bottleneck (e.g., a home user's thin uplink) and arrive at different destinations. Using ns-2 simulations and an implementation in the FreeBSD kernel, we show that our mechanism reduces queuing delay, packet loss, and short flow completion times while enabling precise allocation of the share of the available bandwidth between the connections according to the needs of the applications.

Communication between two Internet hosts using parallel connections may result in unwanted interference between the connections. In this dissertation, we propose a sender-side solution to address this problem by letting the congestion controllers of the different connections collaborate, correctly taking congestion control logic into account. Real-life experiments and simulations show that our solution works for a wide variety of congestion control mechanisms, provides great flexibility when allocating application traffic to the connections, and results in lower queuing delay and less packet loss.

In wireless sensor networks (WSNs), congestion control is a very essential region of concern. When the packets that are coming get increased than the actual capacity of network or nodes results into congestion in the network. Congestion in network can cause reduction in throughput, increase in network delay, and increase in packet loss and sensor energy waste. For that reason, new complex methods are mandatory to tackle with congestion. So it is necessary to become aware of congestion and manage the congested resources in wireless sensor networks for enhancing the network performance. Diverse methodologies for congestion recognition and prevention have been presented in the previous couple of years. To handle some of the problems, this paper exhibits a new technique for controlling the congestion. An efficient and reliable routing protocol (ERRP) based on bio inspired algorithms is introduced in this paper for solving congestion problem. In the proposed work, a way is calculated to send the packets on the new pathway. The proposed work has used three approaches for finding the path which results into a congestion free path. Our analysis and simulation results shows that our approach provides better performance as compared to previous approaches in terms of throughput, packet loss, delay etc.

This demo dramatically illustrates how replacing 'Classic' TCP congestion control (Reno, Cubic, etc.) with a 'Scalable' alternative like Data Centre TCP (DCTCP) keeps queuing delay ultra-low; not just for a select few light applications like voice or gaming, but even when a variety of interactive applications all heavily load the same (emulated) Internet access. DCTCP has so far been confined to data centres because it is too aggressive–-it starves Classic TCP flows. To allow DCTCP to be exploited on the public Internet, we developed DualQ Coupled Active Queue Management (AQM), which allows the two TCP types to safely co-exist. Visitors can test all these claims. As well as running Web-based apps, they can pan and zoom a panoramic video of a football stadium on a touch-screen, and experience how their personalized HD scene seems to stick to their finger, even though it is encoded on the fly on servers accessed via an emulated delay, representing 'the cloud'. A pair of VR goggles can be used at the same time, making a similar point. The demo provides a dashboard so that visitors can not only experience the interactivity of each application live, but they can also quantify it via a wide range of performance stats, updated live. It also includes controls so visitors can configure different TCP variants, AQMs, network parameters and background loads and immediately test the effect.

With the world population becoming increasingly urban and the multiplication of mega cities, urban leaders have responded with plans calling for so called smart cities relying on instantaneous access to information using mobile devices for an intelligent management of resources. Coupled with the advent of the smartphone as the main platform for accessing the Internet, this has created the conditions for the looming wireless bandwidth crunch. This paper presents a content delivery infrastructure relying on off-the-shelf technology and the public transportation network (PTN) aimed at relieving the wireless bandwidth crunch in urban centers. Our solution proposes installing WiFi access points on selected public bus stations and buses and using the latter as data mules, creating a delay tolerant network capable of carrying content users can access while using the public transportation. Building such an infrastructure poses several challenges, including congestion points in major hubs and the cost of additional hardware necessary for secure communications. To address these challenges we propose a 3-Tier architecture that guarantees end-to-end delivery and minimizes hardware cost. Trace-based simulations from three major European cities of Paris, Helsinki and Toulouse demonstrate the viability of our design choices. In particular, the 3-Tier architecture is shown to guarantee end-to-end connectivity and reduce the deployment cost by several times while delivering at least as many packets as a baseline architecture.

Congestion Control (CC) algorithms are essential to quickly restore the network performance back to stable whenever congestion occurs. A majority of the existing CC algorithms are implemented at the transport layer, mostly coupled with TCP. Over the past three decades, CC algorithms have incrementally evolved, resulting in many extensions of TCP. A thorough evaluation of a new TCP extension is a huge task. Hence, the Internet Congestion Control Research Group (ICCRG) has proposed a common TCP evaluation suite that helps researchers to gain an initial insight into the working of their proposed TCP extension. This paper presents an implementation of the TCP evaluation suite in ns-3, that automates the simulation setup, topology creation, traffic generation, execution, and results collection. We also describe the internals of our implementation and demonstrate its usage for evaluating the performance of five TCP extensions available in ns-3, by automatically setting up the following simulation scenarios: (i) single and multiple bottleneck topologies, (ii) varying bottleneck bandwidth, (iii) varying bottleneck RTT and (iv) varying the number of long flows.

When multiple TCP connections are used between the same host pair, they often share a common bottleneck – especially when they are encapsulated together, e.g. in VPN scenarios. Then, all connections after the first should not have to guess the right initial value for the congestion window, but rather get the appropriate value from other connections. This allows short flows to complete much faster – but it can also lead to large bursts that cause problems on their own. Prior work used timer-based pacing methods to alleviate this problem; we introduce a new algorithm that ``paces'' packets by instead correctly maintaining the ACK clock, and show its positive impact in combination with a previously presented congestion coupling algorithm.