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Wireless Local-Area Networks (WLANs), as a popular internet access solution, are widely used in numerous places, including enterprises, campuses, and public venues. As the number of devices increases, large-scale deployments will cause the problem of dense wireless networks, including a lot of energy consumption. Thus, the optimization of energy-efficient wireless AP devices has become a focal point of attention. To reduce energy consumption, we have proposed the active access-point (AP) configuration algorithm for WLANs using APs with a dual interface. This uses the greedy algorithm combined with the local search optimization method to find the minimum number of activated APs while satisfying the minimum throughput constraint. However, the previous algorithm basically satisfies only the average throughput among the multiple hosts associated with one AP, wherein some hosts may not reach the required one. In this paper, to overcome this limitation, we propose an enhanced active AP configuration algorithm by incorporating the throughput request satisfaction method that controls the actual throughput at the target value (target throughput) for every host by applying traffic shaping. The target throughput is calculated from the single and concurrent communicating throughput of each host based on channel occupancy time. The minimum throughput constraint will be iteratively adjusted to obtain the required target throughput and achieve the fair throughput allocation. For evaluations, we conducted simulations using the WIMNET simulator and experiments using the testbed system with a Raspberry Pi 4B for APs in four topology cases with five APs and ten hosts. The results show that the proposed method always achieved the required minimum throughput in simulations as well as in experiments, while minimizing the number of active APs. Thus, the validity and effectiveness of our proposal were confirmed. [ABSTRACT FROM AUTHOR]

With the wide applications of the Internet of Things (IoT) in smart home systems, IEEE 802.11n Wireless Local Area Networks (WLANs) have become a frequently chosen communication technology due to their adaptability and affordability. In a high-density network of devices such as the smart home scenerio, a host often meets interferences from other devices and unequal Received Signal Strength (RSS) from Access Points (APs). This results in throughput unfairness/insufficiency problems between hosts communicating concurrently in WLAN. Previously, we have studied the throughput request satisfaction method to address this problem. It calculates the target throughput from measured single and concurrent throughputs of hosts and controls the actual throughput at this target one by applying traffic shaping at the AP. However, the insufficiency problem of maximizing the throughput is not solved due to interferences from other hosts. In this paper, we present an extension of the throughput request satisfaction method to maximize the throughput of a high-priority host under concurrent communications. It recalculates the target throughput to increase the actual throughput as much as possible while the other hosts satisfy the least throughput. For evaluations, we conduct experiments using the test-bed system with Raspberry Pi as the AP devices in several topologies in indoor environments. The results confirm the effectiveness of our proposal. [ABSTRACT FROM AUTHOR]

Wireless Local-Area Networks (WLANs), as a popular internet access solution, are widely used in numerous places, including enterprises, campuses, and public venues. As the number of devices increases, large-scale deployments will cause the problem of dense wireless networks, including a lot of energy consumption. Thus, the optimization of energy-efficient wireless AP devices has become a focal point of attention. To reduce energy consumption, we have proposed the active access-point (AP) configuration algorithm for WLANs using APs with a dual interface. This uses the greedy algorithm combined with the local search optimization method to find the minimum number of activated APs while satisfying the minimum throughput constraint. However, the previous algorithm basically satisfies only the average throughput among the multiple hosts associated with one AP, wherein some hosts may not reach the required one. In this paper, to overcome this limitation, we propose an enhanced active AP configuration algorithm by incorporating the throughput request satisfaction method that controls the actual throughput at the target value (target throughput) for every host by applying traffic shaping. The target throughput is calculated from the single and concurrent communicating throughput of each host based on channel occupancy time. The minimum throughput constraint will be iteratively adjusted to obtain the required target throughput and achieve the fair throughput allocation. For evaluations, we conducted simulations using the WIMNET simulator and experiments using the testbed system with a Raspberry Pi 4B for APs in four topology cases with five APs and ten hosts. The results show that the proposed method always achieved the required minimum throughput in simulations as well as in experiments, while minimizing the number of active APs. Thus, the validity and effectiveness of our proposal were confirmed.

Despite encryption, the packet size is still visible, enabling observers to infer private information in the Internet of Things (IoT) environment (e.g., IoT device identification). Packet padding obfuscates packet-length characteristics with a high data overhead because it relies on adding noise to the data. This paper proposes a more data-efficient approach that randomizes packet sizes without adding noise. We achieve this by splitting large TCP segments into random-sized chunks; hence, the packet length distribution is obfuscated without adding noise data. Our client–server implementation using TCP sockets demonstrates the feasibility of our approach at the application level. We realize our packet size control by adjusting two local socket-programming parameters. First, we enable the TCP_NODELAY option to send out each packet with our specified length. Second, we downsize the sending buffer to prevent the sender from pushing out more data than can be received, which could disable our control of the packet sizes. We simulate our defense on a network trace of four IoT devices and show a reduction in device classification accuracy from 98% to 63%, close to random guessing. Meanwhile, the real-world data transmission experiments show that the added latency is reasonable, less than 21%, while the added packet header overhead is only about 5%. [ABSTRACT FROM AUTHOR]

With the wide applications of the Internet of Things (IoT) in smart home systems, IEEE 802.11n Wireless Local Area Networks (WLANs) have become a frequently chosen communication technology due to their adaptability and affordability. In a high-density network of devices such as the smart home scenerio, a host often meets interferences from other devices and unequal Received Signal Strength (RSS) from Access Points (APs). This results in throughput unfairness/insufficiency problems between hosts communicating concurrently in WLAN. Previously, we have studied the throughput request satisfaction method to address this problem. It calculates the target throughput from measured single and concurrent throughputs of hosts and controls the actual throughput at this target one by applying traffic shaping at the AP. However, the insufficiency problem of maximizing the throughput is not solved due to interferences from other hosts. In this paper, we present an extension of the throughput request satisfaction method to maximize the throughput of a high-priority host under concurrent communications. It recalculates the target throughput to increase the actual throughput as much as possible while the other hosts satisfy the least throughput. For evaluations, we conduct experiments using the test-bed system with Raspberry Pi as the AP devices in several topologies in indoor environments. The results confirm the effectiveness of our proposal.

With the advancement of space technology and satellite communications, low-Earth-orbit (LEO) satellite networks have experienced rapid development in the past decade. In the vision of 6G, LEO satellite networks play an important role in future 6G networks. On the other hand, a variety of applications, including many delay-sensitive applications, are continuously emerging. Due to the highly dynamic nature of LEO satellite networks, supporting time-deterministic services in such networks is challenging. However, we can provide latency guarantees for most delay-sensitive applications through data plane traffic shaping and control plane routing optimization. This paper addresses the routing optimization problem for time-sensitive (TS) flows in software-defined low-Earth-orbit (LEO) satellite networks. We model the problem as an integer linear programming (ILP) model aiming to minimize path handovers and maximum link utilization while meeting TS flow latency constraints. Since this problem is NP-hard, we design an efficient longest continuous path (LCP) approximation algorithm. LCP selects the longest valid path in each topology snapshot that satisfies delay constraints. An auxiliary graph then determines the routing sequence with minimized handovers. We implement an LEO satellite network testbed with Open vSwitch (OVS) and an open-network operating system (ONOS) controller to evaluate LCP. The results show that LCP reduces the number of path handovers by up to 31.7% and keeps the maximum link utilization lowest for more than 75% of the time compared to benchmark algorithms. In summary, LCP achieves excellent path handover optimization and load balancing performance under TS flow latency constraints. [ABSTRACT FROM AUTHOR]

Beyond 5th generation (5G) and 6th generation (6G) mobile systems require not only low latency but also low jitter for deterministic services such as remote operation. Since remote operation requires high-definition video streaming in the uplink, the uplink transmission performance will become more important. However, current new radio (NR) mobile systems cause jitter in the uplink traffic of the mobile backhaul (MBH) network because of the radio transmission schemes such as downlink/uplink separation of time division duplexing (TDD) and medium access control (MAC) service data unit (SDU) concatenation to compose transport blocks. Thus, we propose MBH uplink jitter reduction techniques with optical-wireless cooperative control. Our proposed techniques execute traffic shaping at a router in the MBH network to reduce uplink jitter. The shaping rate that reduces jitter while minimizing latency increase is calculated with mobile scheduling information forwarded from a next generation node B (gNB) via an extended cooperative transport interface (eCTI). The eCTI provides an interface between gNBs and network equipment to achieve optical-wireless cooperative control. In this paper, we experimentally validate our proposed jitter reduction techniques through a combination of simulations for radio transmission and experiments with a shaper prototype we developed. The results regarding end-to-end (E2E) jitter performance indicate that the proposed techniques reduce the maximum jitter by 88%, from 1.1 ms to $137 ~\mu \text{s}$ .

In the era of the Internet of Everything, the burst of traffic will bring many problems. Traffic shaping, as a common means to limit burst traffic rate, achieves “peak and valley reduction” to smooth the output rate, avoid network congestion, guarantee the quality of service (QoS) and improve the overall network transmission efficiency. This paper first explains the basic concept of traffic shaping, the related algorithms in traffic shaping, and compares the differences between traffic shaping and traffic policing. It then describes the research on traffic shaping in software-defined networks and the results from the combination of the two. This is followed by an introduction to relatively new technology for industry, time-sensitive networks, and an exploration of the functions of various types of traffic shapers in time-sensitive networks. This is followed by a description of case studies of traffic shaping in IoT scenarios and an overview of these traffic shaping schemes, summarizing the usefulness of the shaping schemes. Finally, the future of traffic shaping is explored.

The importance of generating internet traffic as one of the basic considerations in bandwidth allocation policies between faculties is increasing due to the number of students who complain about connection services on campus. This study proposes internet traffic generation based on the statistical - engineering method. The population is calculated based on class capacity in each faculty, as the main alibi of student attendance on campus where traffic arrivals are generated based on the arrival model through information on possible scheduling variations. Although internet services have different characteristics, they are physically determined by the bitrate and idle mode in the traffic time series. The results show recommendations in three application bitrate categories, namely 200kbps, 400kbps, and 800kbps Traffic Shaping.

To improve the experience of real-time interactive applications based on video and audio, there is a growing demand to realize deterministic networks that can transmit these media with low latency. In recent years, various deterministic network technologies have been studied such as Time Sensitive Networking (TSN). Time slot allocation type schemes such as Time-Aware Shaper (TAS) offer guaranteed delayed determinism and zero-jitter, but suffer from low network accommodation efficiency. Shaper-based techniques such as Asynchronous Traffic Shaping (ATS) provide high network accommodation efficiency and delay determinism inside the network. However, if the input traffic from the sender is bursty, End-to-End delay increases due to the shaping delay caused by the shapers at the edges of the network. In this paper, we propose Delay-Based Shaper (DBS), which dynamically controls the bandwidth while shaping the bursts so that the upper bound of the shaping delay is protected. In addition, we also propose a Dynamic Token Bucket Algorithm (DTBA) that extends the conventional token bucket algorithm to implement DBS. We show that DBS can both shape bursts and comply with the upper bound of shaping delay by comparing the behavior when bursts are input via a conventional shaper. We also demonstrate good End-to-End delay determinism and high network accommodation efficiency by applying DBS to the edge of the network.

Nowadays, the IEEE 802.11 wireless local area network (WLAN) has been widely used for Internet access services around the world. Then, the unfairness or insufficiency in meeting the throughput request can appear among concurrently communicating hosts with the same access point (AP), which should be solved by sacrificing advantageous hosts. Previously, we studied the fairness control method by adopting packet transmission delay at the AP. However, it suffers from slow convergence and may not satisfy different throughput requests among hosts. In this paper, we propose a throughput request satisfaction method for providing fair or different throughput requests when multiple hosts are concurrently communicating with a single AP. To meet the throughput request, the method (1) measures the single and concurrent throughput for each host, (2) calculates the channel occupying time from them, (3) derives the target throughput to achieve the given throughput request, and (4) controls the traffic by applying traffic shaping at the AP. For evaluations, we implemented the proposal in the WLAN testbed system with one Raspberry Pi AP and up to five hosts, and conducted extensive experiments in five scenarios with different throughput requests. The results confirmed the effectiveness of our proposal. [ABSTRACT FROM AUTHOR]

An aggregating switch (SW) network offers cost-effective accommodation to Internet-of-Things (IoT) traffic by aggregating the traffic. In such a network, it is crucial to eliminate the discarded traffic caused by the simultaneous transmission of massive IoT devices, namely microburst. Traffic shaping is a technique of storing traffic in one SW to mitigate microbursts. Conventional traffic shaping is limited because only one SW performs shaping with a limited queue length. Thus, we propose cooperated traffic shaping using multiple SWs to accommodate more traffic. We formulated equations to derive the minimum queue length with shaping rates which gradually decrease in geometric progression. To acquire the queue length using general SWs without short-cycle monitoring, we propose a scheme for estimating the instantaneous input rate and data size of microburst traffic required for our equations. If the calculated queue length cannot be prepared in the current path, we propose reallocating the path to another one with more SWs. We experimentally demonstrated the proposed coordinated traffic shaping technique by implementing it in commercial SWs with 125 emulated IoT devices. The results showed that the difference between the experimental and numerical results was below 4.2%, and the queue length can be reduced by 40% when there are three SWs. In addition, a path with two SWs was successfully reallocated to one with three SWs.

A mobile ad hoc network (MANET) has several intrinsic features that create unique queuing dynamics, and thus congestion control inside a MANET must be achieved under time-critical conditions. Meanwhile, the Named Data Networking (NDN) architecture ensures traffic optimization and has attracted renewed attention as part of the future internet. The synergy between NDN and MANETs can be exploited in order to improve the performance of dynamic content routing and congestion control mechanisms. This overview identifies the key concepts involved in congestion control for NDN-based MANETs. It also proposes some criteria for categorising existing congestion control solutions for NDN-based MANETs and discusses the advantages and disadvantages of each category. Future challenges regarding congestion control for NDN-based MANETs are also highlighted. [ABSTRACT FROM AUTHOR]

Nowadays, the IEEE 802.11 wireless local area network (WLAN) has been widely used for Internet access services around the world. Then, the unfairness or insufficiency in meeting the throughput request can appear among concurrently communicating hosts with the same access point (AP), which should be solved by sacrificing advantageous hosts. Previously, we studied the fairness control method by adopting packet transmission delay at the AP. However, it suffers from slow convergence and may not satisfy different throughput requests among hosts. In this paper, we propose a throughput request satisfaction method for providing fair or different throughput requests when multiple hosts are concurrently communicating with a single AP. To meet the throughput request, the method (1) measures the single and concurrent throughput for each host, (2) calculates the channel occupying time from them, (3) derives the target throughput to achieve the given throughput request, and (4) controls the traffic by applying traffic shaping at the AP. For evaluations, we implemented the proposal in the WLAN testbed system with one Raspberry Pi AP and up to five hosts, and conducted extensive experiments in five scenarios with different throughput requests. The results confirmed the effectiveness of our proposal.

Energy efficiency is a critical problem for wireless sensor networks. In past decades, network coding has been proved as a promising technology to reduce the number of transmissions, save energy, and improve network throughput, especially suitable for the wireless network that motivates the emergence of network coding aware routings. However, existing network coding aware routings have the failure decoding problem, because of defective network coding conditions. On the other hand, existing network coding aware routings usually consider the ideal traffic scheduling and neglect nodes' energy and load which are important to wireless sensor networks. Therefore, it is not appropriate to directly apply existing network coding aware routings in wireless sensor networks. Regarding the problems above problems, this paper proposes traffic-shaped network coding aware routing (TSCAR) for wireless sensor networks. In the TSCAR, a universal network coding condition is presented to solve the false decoding problem. And traffic shaping mechanism is proposed to shape the traffic of different flows to create more coding actions when coding opportunities exist. In addition, network calculus is used to analyze the delay of the TSCAR. Besides, a coding, load, and energy aware routing metrics are proposed to evaluate the discovered paths. Extensive simulation results demonstrate that the TSCAR increases the number of coding opportunities and the proportion of coded packets, improves network throughput, and extends the network lifetime of wireless sensor networks.

Modern hard real-time systems evolved from isolated single-core architectures to complex multi-core architectures which are often connected in a distributed manner. With the increasing influence of interconnections in hard real-time systems, the access behavior to shared resources of single tasks or cores becomes a crucial factor for the system's overall worst-case timing properties. Traffic shaping is a powerful technique to decrease contention in a network and deliver guarantees on network streams. In this paper we present a novel approach to automatically integrate a traffic shaping behavior into the code of a program for different traffic shaping profiles while being as least invasive as possible. As this approach is solely depending on modifying programs on a code-level, it does not rely on any additional hardware or operating system-based functions. We show how different traffic shaping profiles can be implemented into programs using a greedy heuristic and an evolutionary algorithm, as well as their influences on the modified programs. It is demonstrated that the presented approaches can be used to decrease worst-case execution times inmulti-core systems and lower buffer requirements in distributed systems. [ABSTRACT FROM AUTHOR]

Various server-based services such as big data, IoT and artificial intelligence have been made online. As a result, the demand for IDC to support stable server operation is increasing. IDC is a server-based facility with a stable line and power supply facility that manages 20 to 30 servers in an efficiently separated rack-level subnetwork. Here, we need a way to efficiently manage servers security, firewall, and traffic on a rack-by-rack basis. Including traffic shaping capabilities that control routers, firewalls, IPS, and line speeds, as well as VPN technology, a recent interest. If three or five kinds of commercial equipment are adopted to support this, it may be a great burden to the management cost as well as the introduction cost. Therefore, in this paper, we propose a method to implement the five functions in one rack-unit small integrated security router. In particular, IDC intends to integrate traffic shaping and IPS, which are essential technologies, and to propose the utility accordingly. [ABSTRACT FROM AUTHOR]

Adaptive video streaming can provide adequate Quality of Experience by dynamically adjusting video rates in responding to fluctuating service conditions. However, adaptive video streaming shows dismal performances in wireless networks where several players share a wireless bottleneck link. This paper proposes a novel video rate selection scheme called XMAS for efficient video streaming in wireless networks. XMAS consists of two components: an available bandwidth estimation part and a video rate selection part. To redress the problem of inaccurate bandwidth estimation due to peculiar on-off transmission patterns of mobile video streaming, we devised a novel client-based traffic shaping scheme that effectively throttles server's packet transmission. Equipped with accurate bandwidth estimates, XMAS determines target transmission rates considering playback buffer levels. We implemented XMAS on Linux and performed rigorous experiments to analyze its behavior and performance. Our performance results showed that XMAS achieves up to 20% increase in average video rates while reducing rebuffer rates significantly. [ABSTRACT FROM AUTHOR]

Next-generation wireless architectures are expected to enable slices of shared wireless infrastructure, which are customized to specific mobile operators/services. Given infrastructure costs and the stochastic nature of mobile services’ spatial loads, it is highly desirable to achieve efficient statistical multiplexing among such slices. We study a simple dynamic resource sharing policy, which allocates a “share” of a pool of (distributed) resources to each slice-share constrained proportionally fair (SCPF). We give a characterization of SCPF’s performance gains over static slicing and general processor sharing. We show that higher gains are obtained when a slice’s spatial load is more “imbalanced” than, and/or “orthogonal” to, the aggregate network load, and that the overall gain across slices is positive. We then address the associated dimensioning problem. Under SCPF, traditional network dimensioning translates to a coupled share dimensioning problem, which characterizes the existence of a feasible share allocation, given slices’ expected loads and performance requirements. We provide a solution to robust share dimensioning for SCPF-based network slicing. Slices may wish to unilaterally manage their users’ performance via admission control, which maximizes their carried loads subject to performance requirements. We show that this can be modeled as a “traffic shaping” game with an achievable Nash equilibrium. Under high loads, the equilibrium is explicitly characterized, as are the gains in the carried load under SCPF versus static slicing. Detailed simulations of a wireless infrastructure supporting multiple slices with heterogeneous mobile loads show the fidelity of our models and the range of validity of our high-load equilibrium analysis. [ABSTRACT FROM AUTHOR]

With the emergence of 5G networks and the stringent Quality of Service (QoS) requirements of Mission-Critical Applications (MCAs), co-existing networks are expected to deliver higher-speed connections, enhanced reliability, and lower latency. IEEE 802.11 networks, which co-exist with 5G, continue to be the access choice for indoor networks. However, traditional IEEE 802.11 networks lack sufficient reliability and they have non-deterministic latency. To dynamically control resources in IEEE 802.11 networks, in this paper we propose a delay-aware approach for Medium Access Control (MAC) management via airtime-based network slicing and traffic shaping, as well as user association while using Multi-Criteria Decision Analysis (MCDA). To fulfill the QoS requirements, we use Software-Defined Networking (SDN) for airtime-based network slicing and seamless handovers at the Software-Defined Radio Access Network (SD-RAN), while traffic shaping is done at the Stations (STAs). In addition to throughput, channel utilization, and signal strength, our approach monitors the queueing delay at the Access Points (APs) and uses it for centralized network management. We evaluate our approach in a testbed composed of APs controlled by SD-RAN and SDN controllers, with STAs under different workload combinations. Our results show that, in addition to load balancing flows across APs, our approach avoids the ping-pong effect while enhancing the QoS delivery at runtime. Under varying traffic demands, our approach maintains the queueing delay requirements of 5 ms for most of the experiment run, hence drawing closer to MCA requirements.

Al momento de implementar una red de telecomunicaciones, no sólo se necesita elegir el protocolo adecuado según el tipo de daos y la velocidad de transmisión que ha de manejar, sino que también se debe tomar en cuenta qué mecanismos de control de tráfico llevará a cabo la red. De hecho, este aspecto es crucial a la hora de aplicar la calidad de servicio que se ofrecerá a los usuarios de la misma.

Today, the great challenge in broad band networks, such as ATM, is to support applications that need guaranteed QoS. Efficient resource allocation for connections that need guaranteed QoS is only possible if the application can provide a precise and reliable traffic descriptor that the network can understand. This work presents a methodology to obtain the parameters of the traffic descriptor of an ATM application from an initial sample of the flow. Based on real-time measurements of the flow, we suggest periodic renegotiations of the parameters, every time they vary above or below their predefined limits. We apply this method to a VBR MPEG video flow and demonstrate its performance. Observed results are discussed and some future uses of the methodology are suggested.

With the development of mobile applications, the massive background data transfers may seriously burden the user equipment and reduce the lifetime of battery. In order to reduce the energy consumption of this background traffic, a new energy-efficient approach based on traffic shaping, that uses some static network parameters such as inactivity timer, buffer threshold, was proposed. The simulation results show that the approach can save 32％to 63％Cof the total energy consumption.

HTTP adaptive streaming (HAS) is a widely used video streaming technology that suffers from a degradation of user’s Quality of Experience (QoE) and network’s Quality of Service (QoS) when many HAS players are sharing the same bottleneck link and competing for bandwidth. The two major factors of this degradation are: the large OFF period of HAS, which causes false bandwidth estimations, and the TCP congestion control, which is not suitable for HAS given that it does not consider the different video encoding bitrates of HAS. This paper proposes a HAS-based TCP congestion control, TcpHas, that minimizes the impact of the two aforementioned issues. It does this using traffic shaping on the server. Simulations indicate that TcpHas improves both QoE, mainly by reducing instability and convergence speed, and QoS, mainly by reducing queuing delay and packet drop rate. [ABSTRACT FROM AUTHOR]

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today’s cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control, including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters, which have been receiving increasing attention recently and pose interesting and novel research problems. To measure the performance of datacenter networks, different performance metrics have been used, such as flow completion times, deadline miss rate, throughput, and fairness. Depending on the application and user requirements, some metrics may need more attention. While investigating different traffic control techniques, we point out the tradeoffs involved in terms of costs, complexity, and performance. We find that a combination of different traffic control techniques may be necessary at particular entities and layers in the network to improve the variety of performance metrics. We also find that despite significant research efforts, there are still open problems that demand further attention from the research community. [ABSTRACT FROM AUTHOR]

HTTP Adaptive Streaming (HAS) is a streaming video technique widely used over the Internet. However, it has many drawbacks that degrade its user Quality of Experience (QoE). Our investigation involves several HAS clients competing for bandwidth inside the same home network. Studies have shown that managing the bandwidth between HAS clients using traffic-shaping methods improves the QoE. Additionally, the TCP congestion control algorithm in the HAS server may also impact the QoE, because every congestion control variant has its own method to control the congestion window size. Based on previous work, we describe two traffic-shaping methods, the Hierarchical Token Bucket shaping Method (HTBM) and the Receive Window Tuning Method (RWTM), as well as four popular congestion control variants: NewReno, Vegas, Illinois, and Cubic. In this paper, our objective is to provide a detailed comparative evaluation of combining these four congestion control variants with these two shaping methods. The main result indicates that Illinois with RWTM offers the best QoE without causing congestion. Results were validated through experimentation and objective QoE analytical criteria. [ABSTRACT FROM AUTHOR]

Convolutional Neural Networks (CNNs) have become the default choice for processing visual information, and the design complexity of CNNs has been steadily increasing to improve accuracy. To cope with the massive amount of computation needed for such complex CNNs, the latest solutions utilize blocking of an image over the available dimensions (e.g., horizontal, vertical, channel, and kernel) and batching of multiple input images to improve data reuse in the memory hierarchy. While there has been a large collection of works on maximizing data reuse, only a few studies have focused on the memory bottleneck problem caused by limited bandwidth. Bandwidth bottleneck can easily occur in CNN acceleration as CNN layers have different sizes with varying computation needs and as batching is typically performed over each layer of CNN for an ideal data reuse. In this case, the data transfer demand for a layer can be relatively low or high compared to the computation requirement of the layer, and therefore temporal fluctuations in memory access can be induced eventually causing bandwidth problems. In this paper, we first show that there exists a high degree of fluctuation in memory access to computation ratio depending on CNN layers and functions in the layer being processed by the compute units (cores), where the compute units are tightly synchronized to maximize data reuse. Then we propose a strategy of partitioning the compute units where the cores within each partition process a batch of input data in a synchronous manner to maximize data reuse but different partitions run asynchronously. Because the partitions stay asynchronous and typically process different CNN layers at any given moment, the memory access traffic sizes of the partitions become statistically shuffled. Thus, the partitioning of compute units and asynchronous use of them make the total memory access traffic size be smoothened over time, and the degree of partitioning determines a tradeoff between data reuse efficiency and memory bandwidth utilization efficiency. We call this smoothing statistical memory traffic shaping, and we show that it can lead to 8.0 percent of performance gain on a commercial 64-core processor when running ResNet-50. [ABSTRACT FROM PUBLISHER]

The vehicular ad-hoc network (VANET) is the network of vehicles, which is designed to enable the multi-service architecture across the vehicular networks. The VANETs are the network of the moving nodes on adequately higher speeds, which create the great challenge to gain and through the data from and to the vehicular nodes on the move. The VANETs are used to predict the traffic jams, hurdles or blockades produced due to tree falling, avalanche, flash flood, etc. The minimized delay oriented vehicular networks must be designed over the high speed transmission podium along with efficient data transmissions with optimized number of topology, hello and update packets. In this paper, the major improvements have been proposed in the hazard routing protocols (HRPs) specifically designed for the vehicular networks. The optimized number of hello packets, minimized topology packets and dedicated routing models are involved in the design of the proposed efficient data handling model. This model has undergone the variety of versatile performance evaluation experiments, which proves the improved performance of the proposed model. The maximum delay in the simulation model has been recorded nearly at 0.064 microseconds, which is considerably lower than the existing model. Also the proposed model has been designed to lower the data loss rate by 0.4%, which also proves the robustness of proposed model in comparison to existing model. [ABSTRACT FROM AUTHOR]

Chemical algorithms are statistical control algorithms described and represented as chemical reaction networks. They are analytically tractable, they reinforce a deterministic state-to-dynamics relation, they have configurable stability properties, and they are directly implemented in state space using a high-level visual representation. These properties make them attractive solutions for traffic shaping and generally the control of dynamics in computer networks. In this paper, we present a framework for deploying chemical algorithms on field programmable gate arrays. Besides substantial computational acceleration, we introduce a low-overhead approach for hardware-level programmability and re-configurability of these algorithms at runtime, and without service interruption. We believe that this is a promising approach for expanding the control-plane programmability of software defined networks (SDN), to enable programmable network dynamics. To this end, the simple high-level abstractions of chemical algorithms offer an ideal northbound interface to the hardware, aligned with other programming primitives of SDN (e.g., flow rules). [ABSTRACT FROM AUTHOR]

Faked deauthentication and disassociation frames introduce serious denial of service (DoS) attacks on wireless local area networks (WLANs), and these attacks include deauthentication flooding (DeauthF) and disassociation flooding (DisassF). IEEE 802.11w standard was introduced to extend 802.11i functionalities for preventing DeauthF and DisassF, and so far there has been no detailed theoretical and experimental study on the performance of 802.11w for resolving these attacks. We implemented a prototype at the lab to perform detailed study on the performance of 802.11w for preventing rogue AP based DoS attacks, and the study shows that the current IEEE 802.11w standard cannot resolve DeauthF and DisassF at high attacking rates. Then, based on 802.11 wireless station (STA) modules, a STA-based queuing model is developed to derive a mathematical model for explaining 802.11w performance variations under DeauthF and DisassF attacks. Furthermore, using frame sequence checking and frame queuing, we propose a traffic shaping (TS) scheme to enhance the current IEEE 802.11w standard, and experimental results show that the proposed approach of 802.11w-TS is effective in preventing low-rate and high-rate DeauthF and DisassF attacks under various attacking scenarios. [ABSTRACT FROM AUTHOR]