In this paper, we present a generic plug-and-play controller that ensures fair and efficient operation of IEEE 802.11 infrastructure wireless local area networks with multiple co-channel access points, without any change to hardware firmware of the network devices. Our controller addresses performance issues of TCP transfers in multi-AP WLANs, by overlaying a coarse time-slicing scheduler on top of a cascaded fair queuing scheduler. The time slices and queue weights, used in our controller, are obtained from the solution of a constrained utility optimization formulation. A study of the impact of coarse time-slicing on TCP is also presented in this paper. We present an improved algorithm for adaptation of the service rate of the fair queuing scheduler and provide experimental results to illustrate its efficacy. We also present the changes that need to be incorporated to the proposed approach, to handle short-lived and interactive TCP flows. Finally, we report the results of experiments performed on a real testbed, demonstrating the efficacy of our controller.
In @cite_2 , introduce MIDAS, a management framework that addresses under-served links by throttling traffic to the interfering links. Based on the notion of Activity Share'' that they introduce, the authors propose a method to assess the potential throughput gain that the under-served link can experience, when hindering transmissions are rate-limited. MIDAS limits the rate at which traffic is sent to the interfering links, so that the under-served link's activity share improves. While MIDAS improves the air time'' of under-served links, there are no flow-level system objectives that drive the target activity share. Such flow-level system objectives are indispensable in networks with Quality-of-Service (QoS) guarantees.
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In this paper, a concurrent transmission scheduling algorithm is proposed to enhance the resource utilization efficiency for multi-Gbps millimeter-wave (mmWave) networks. Specifically, we exploit spatial-time division multiple access (STDMA) to improve the system throughput by allowing both non-interfering and interfering links to transmit concurrently, considering the high propagation loss at mmWave band and the utilization of directional antenna. Concurrent transmission scheduling in mmWave networks is formulated as an optimization model to maximize the number of flows scheduled in the network such that the quality of service (QoS) requirement of each flow is satisfied. We further decompose the optimization problem and propose a flip-based heuristic scheduling algorithm with low computational complexity to solve the problem. Extensive simulations demonstrate that the proposed algorithm can significantly improve the network performance in terms of network throughput and the number of supported flows. We consider the following queuing system which arises as a model of a wireless link shared by multiple users. There is a finite number N of input flows served by a server. The system operates in discrete time t = 0,1,2,…. Each input flow can be described as an irreducible countable Markov chain; waiting customers of each flow are placed in a queue. The sequence of server states m(t), t = 0,1,2,…, is a Markov chain with finite number of states M. When the server is in state m, it can serve mim customers of flow i (in one time slot).The scheduling discipline is a rule that in each time slot chooses the flow to serve based on the server state and the state of the queues. Our main result is that a simple online scheduling discipline, Modified Largest Weighted Delay First, along with its generalizations, is throughput optimal; namely, it ensures that the queues are stable as long as the vector of average arrival rates is within the system maximum stability region. A regional central manager is employed to set aside, for the regional (or back-bone) network that it manages, for each flow class, communications capacity resources for a specific future time horizon. In the context of such a traffic management operation, a longer temporal scale is involved in controlling the admission and distribution of flows across the network. For management scal-ability purposes, flows are aggregated into flow classes. Furthermore, we consider a network operation under which multiple simultaneously activated routes are employed, across possibly distinct segments, to distribute traffic between identified source-destination pairs. We aim to ensure that the utility assigned to each class is as high as feasibly possible while striving to raise the utility gained by all classes in a maxmin fair manner. In doing so, we incorporate the communications capacity constraints that are imposed by the underlying hybrid of directional and or multiple-access wireline and wireless communications media employed across the network system. We develop and present in this paper an optimal algorithm for solving such a traffic management problem. It yields multi-utility-based max-min fair distributions of flow rates, per each class, across the specified multitude of simultaneously activated multi-segment routes. To guarantee that admitted flows are granted their desired capacity resources (and targeted corresponding utility levels), the selection of optimal flow distributions across the network routes is combined with the use of a flow admission control scheme that serves to optimally limit the aggregate rate of flows admitted for each flow class. As illustrative examples, we demonstrate the effectiveness of our solution in comparing its performance with that obtained under the use of a traffic regulation scheme that is not overlaid with a traffic management mechanism that serves to set aside resources for the support of flow classes. We also illustrate the use of our optimal algorithm for determining the optimal placement of unmanned aerial vehicle platforms that serve to supplement a terrestrial transport segment with a space-based one. Several works have established links between congestion control in communication networks and feedback control theory. In this paper, following this paradigm, the design of an AQM (active queue management) ensuring the stability of the congestion phenomenon at a router is proposed. To this end, a modified fluid flow model of TCP (transmission control protocol) that takes into account all delays of the topology is introduced. Then, appropriate tools from control theory are used to address the stability issue and to cope with the time-varying nature of the multiple delays. More precisely, the design of the AQM is formulated as a structured state feedback for multiple time delay systems through the quadratic separation framework. The objective of this mechanism is to ensure the regulation of the queue size of the congested router as well as flow rates to a prescribed level. Furthermore, the proposed methodology allows to set arbitrarily the QoS (quality of service) of the communications following through the controlled router. Finally, a numerical example and some simulations support the exposed theory. The deployment of micro-datacenters for network function virtualization (NFV) by Internet Service Providers creates opportunities for flow processing along the traffic path. On-path processing requires the discovery of the middleboxes that will be traversed by each flow and the assignment of network functions (NFs) to middleboxes, while preserving the order of the NFs as specified in the service chain. NF location dependencies may require flow processing establishment across multiple NF Providers (NFPs). This entails additional challenges for middlebox discovery and selection, stemming from the NFPs' restrictions in information disclosure and interoperability. To address these issues, we present MIDAS, an architecture for the coordination of middlebox discovery and selection across multiple NFPs. MIDAS relies on a centralized middlebox controller in each NFP to provide interoperability among NFPs for flow processing setup. MIDAS establishes on-path processing via middlebox signaling, controller chaining, and Multi-Party Computation (MPC) based middlebox selection. We particularly employ MPC to preserve the confidentiality of middlebox utilization across the NFPs. We study the feasibility of MIDAS using a prototype implementation and further present simulation results to assess the efficiency of our middlebox selection approach. In most network models for quality of service support, the communication links interconnecting the switches and gateways are assumed to have fixed bandwidth and zero error rate. This assumption of steadiness, especially in a heterogeneous internet-working environment, might be invalid owing to subnetwork multiple-access mechanism, link-level flow error control, and user mobility. Techniques are presented in this paper to characterize and analyze work-conserving communication nodes with varying output rate. In the deterministic approach, the notion of "fluctuation constraint," analogous to the "burstiness constraint" for traffic characterization, is introduced to characterize the node. In the statistical approach, the variable-rate output is modelled as an "exponentially bounded fluctuation" process in a way similar to the "exponentially bounded burstiness" method for traffic modelling. Based on these concepts, deterministic and statistical bounds on queue size and packet delay in isolated variable-rate communication server-nodes are derived, including cases of single-input and multiple-input under first-come-first-serve queueing. Queue size bounds are shown to be useful for buffer requirement and packet loss probability estimation at individual nodes. Our formulations also facilitate the computation of end-to-end performance bounds across a feedforward network of variable-rate server-nodes. Several numerical examples of interest are given in the discussion. Efficient dynamic resource provisioning algorithms are necessary to the development and automation of Quality of Service (QoS) networks. The main goal of these algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources. This paper proposes a novel game theoretical model that solves the joint problem of non-cooperative QoS routing and dynamic capacity allocation in a parallel links network. Two categories of players are introduced: (1) the capacity players that dimension the link capacities to provide QoS guarantees to users, minimizing, at the same time, the links' congestion, and (2) network users, which are characterized by elastic traffic demands and split their traffic over multiple links, maximizing their objective function. This game is modeled as a multi-leader-follower game, where capacity players are leaders and network users are followers. We derive optimal routing and capacity settings using a round robin greedy algorithm, discussing numerical examples that provide insights into the model's solution. Device-to-device (D2D) communication has been recently proposed to mitigate the burden of base stations by leveraging the underutilized cellular spectrum resources, where high overall network throughput and D2D access rate are critical for its service performance and availability. In this paper, we study the resource allocation problem to push the limit of D2D communication underlaying cellular networks by allowing multiple D2D links to share resource with multiple cellular links. We propose FRESH, a f ull re source sh aring scheme where each subchannel can be shared by a cellular link and an arbitrary number of D2D links. In particular, FRESH first divides the communication links into so-called full resource sharing sets such that, within each set, all D2D link members are able to reuse the whole allocated resources. Thereafter, it allocates a sum of spectrum resources to each obtained full resource sharing set. As compared with state-of-the-art schemes, FRESH provides fine-grained resource allocation, resulting in throughput improvements of up to one order of magnitude, and D2D access rate improvements of up to 5 times with a moderate node density (e.g., on the order of 1 user per 400 square meters). Elastic Optical Networks (EONs) have the potential to improve the fiber spectrum utilization by allocating spectrum resources to multiple traffic requests proportionally to the amount of carried traffic. However, achieving high spectrum utilization in this elastic scenario is hindered by the resulting spectrum fragmentation. A number of studies have addressed and made attempts to mitigate spectrum fragmentation. Most of these studies are based on simulation techniques and target the overall blocking probability experienced by the offered traffic requests due to the lack of available spectrum resources. Some studies have also shown that blocking probability in EON can be uneven, i.e., high-rate circuit requests are more likely to be blocked when compared to low-rate requests due to the shortage of contiguously available spectrum resources. The contribution of this paper is to extend an existing Markov Chain (MC) model previously proposed by the authors to quantify blocking probability in a two-service elastic fiber link. The model extension accounts for a self-limited and partial sharing of the fiber spectrum to accommodate the two types of service. The MC model is used to quantify both the blocking probability and its fairness across the two types of service, documenting how the EON uneven blocking behavior can be significantly mitigated by performing partial (as opposed to full) sharing of the fiber spectrum. We address resource sharing of the cellular network and a device-to-device (D2D) underlay communication assuming that the cellular network has control over the transmit power and the radio resources of D2D links. We show that by proper power control, the interference between two services can be coordinated to benefit the overall performance. In addition, we consider a scenario with prioritized cellular communication and an upper limit on the maximum transmission rate of all links. We derive the optimum power allocation for the considered resource sharing modes. The results show that cellular service can be effectively guaranteed while having a comparable sum rate with a none power control case in most of the cell area. Information about the topology and link-level characteristics of a network is critical for many applications including network diagnostics and management. However, this information is not always directly accessible; subnetworks may not cooperate in releasing information and widespread local measurement can be prohibitively expensive. Network tomographic techniques obviate the need for network cooperation, but the majority assume probing from a single source, which imposes scalability limitations because sampling traffic is concentrated on network links close to the source. We describe a multiple source, end-to-end sampling architecture that uses coordinated transmission of carefully engineered multipacket probes to jointly infer logical topology and estimate link-level performance characteristics. We commence by demonstrating that the general multiple source, multiple destination tomography problem can be formally reduced to the two source, two destination case, allowing the immediate generalization of any sampling techniques developed for the simpler, smaller scenario. We then describe a method for testing whether links are shared in the topologies perceived by individual sources, and describe how to fuse the measurements in the shared case to generate more accurate estimates of the link-level performance statistics Link bundling is a way to increase routing scalability whenever a pair of label switching routers in MPLS are connected by multiple parallel links. However, link bundling can be inefficient as a label switched path (LSP) has to be associated with a particular link. In this paper, we show that the efficiency of link bundling can be significantly improved if traffic can be effectively distributed across the parallel links. We propose an IP switch architecture that is capable of distributing flows both inside the switch and among the parallel links based on operations that are relatively simple to implement. The switch requires no speedup, guarantees in-sequence packet delivery for a given flow, avoids complex coordination algorithms, and can achieve LSP throughput higher than the line rate. By means of simulation using IP traces, we investigate the performance of the proposed switch, and show that the switch achieves good load-balancing performance. We describe extensions to the basic architecture which allows for very large bundle size, handles incremental upgrade strategy, improves reliability, and accommodates nonIP traffic. This paper investigates the optimal rate allocation problem with end-to-end delay constraints in multi-hop wireless networks. We introduce Virtual Link Capacity Margin (VLCM), which is the gap between the schedulable link capacity and the maximum allowable flow rate over a link, for link delay control. We formulate the problem as a utility maximization framework with two sets of constraints: 1) capacity and schedulability constraints and 2) end-to-end delay constraints. By dual decomposition of the original optimization problem, we present a control algorithm that jointly tunes the flow rates and VLCMs, through a double-price scheme derived with regard to the constraints: the link congestion price reflecting the traffic load of a link, and the flow delay price reflecting the margin between the average packet delay and the delay requirement of a flow. We prove that the algorithm converges to a global optimum where the aggregate network utility defined over the flow rate set is maximized, while the delay constraints are satisfied. A key feature of our algorithm is it does not rely on a specific traffic model. The algorithm is implemented distributedly via joint wireless link scheduling and congestion control. Simulation results show that our algorithm outperforms heuristic rate allocation algorithms while satisfying the end-to-end delay constraints. Narrowband Internet of Things (NB-IoT) is a new narrow-band radio technology introduced in the Third Generation Partnership Project release 13 to the 5th generation evolution for providing low-power wide-area IoT. In NB-IoT systems, repeating transmission data or control signals has been considered as a promising approach for enhancing coverage. Considering the new feature of repetition, link adaptation for NB-IoT systems needs to be performed in 2-D, i.e., the modulation and coding scheme (MCS) and the repetition number. Therefore, existing link adaptation schemes without consideration of the repetition number are no longer applicable. In this paper, a novel uplink link adaptation scheme with the repetition number determination is proposed, which is composed of the inner loop link adaptation and the outer loop link adaptation, to guarantee transmission reliability and improve throughput of NB-IoT systems. In particular, the inner loop link adaptation is designed to cope with block error ratio variation by periodically adjusting the repetition number. The outer loop link adaptation coordinates the MCS level selection and the repetition number determination. Besides, key technologies of uplink scheduling, such as power control and transmission gap, are analyzed, and a simple single-tone scheduling scheme is proposed. Link-level simulations are performed to validate the performance of the proposed uplink link adaptation scheme. The results show that our proposed uplink link adaptation scheme for NB-IoT systems outperforms the repetition-dominated method and the straightforward method, particularly for good channel conditions and larger packet sizes. Specifically, it can save more than 14 of the active time and resource consumption compared with the repetition-dominated method and save more than 46 of the active time and resource consumption compared with the straightforward method. Millimeter wave (mmWave) communication has been a promising technology of future fifth generation (5G) cellular networks. Due to the tremendous propagation loss of mmWave communication, device-to-device (D2D) communications are widely used over directional mmWave networks to improve the network throughput. In this paper, a new time resource sharing scheme is proposed based on Stackelberg game for interference D2D links to further enhance the network throughput. The D2D links causing interference can access to the time resource by paying higher price, while the D2D links causing no interference can also be scheduled in the scheme. Concurrent transmission scheduling between D2D links causing interference is formulated as a non-cooperative game, which achieves a distributed transmission power control solution among the interference D2D links. Moreover, the price strategy can be adjusted by setting the interference threshold such that the transmission quality can be guaranteed. The simulation results show that the proposed scheme can achieve significant network throughput gain compared with traditional concurrent transmission scheme. Aggregation of resources is a means to improve performance and efficiency in statistically shared systems in general, and communication networks in particular. One approach to this is traffic dispersion, which means that the traffic from a source is spread over multiple paths and transmitted in parallel through the network. Traffic dispersion may help in utilizing network resources to their full potential, while providing quality-of-service guarantees. It is a topic gaining interest, and much work has been done in the field. The results are, however, difficult to find, since the technique appears under many different labels. This article is therefore an attempt to gather and report on the work done on traffic dispersion in communication networks. It looks at a specific instance of this general method. The processes are communication processes, and the resource is the link capacity in a packet switched network. Networks that support multiple services through "link-sharing" must address the fundamental conflicting requirement between isolation among service classes to satisfy each class' quality of service requirements, and statistical sharing of resources for efficient network utilization. While a number of service disciplines have been devised which provide mechanisms to both isolate flows and fairly share excess capacity, admission control algorithms are needed which exploit the effects of inter-class resource sharing. In this paper, we develop a framework of using statistical service envelopes to study inter-class statistical resource sharing. We show how this service envelope enables a class to over-book resources beyond its deterministically guaranteed capacity by statistically characterizing the excess service available due to fluctuating demands of other service classes. We apply our techniques to several multi-class schedulers, including generalized processor sharing, and design new admission control algorithms for multi-class link-sharing environments. We quantify the utilization gains of our approach with a set of experiments using long traces of compressed video. We discuss the relevance of fairness as a design objective for congestion control mechanisms in the Internet. Specifically, we consider a backbone network shared by a dynamic number of short-lived flows, and study the impact of bandwidth sharing on network performance. In particular, we prove that for a broad class of fair bandwidth allocations, the total number of flows in progress remains finite if the load of every link is less than one. We also show that provided the bandwidth allocation is "sufficiently" fair, performance is optimal in the sense that the throughput of the flows is mainly determined by their access rate. Neither property is guaranteed with unfair bandwidth allocations, when priority is given to one class of flow with respect to another. This suggests current proposals for a differentiated services Internet may lead to suboptimal utilization of network resources. In this paper we propose a general utility-oriented adaptive quality of service (QoS) model for wireless networks and establish a framework for formulating the bandwidth allocation problem for users with time-varying links. For slow link variations, it is inadequate to only employ low-level adaptive mechanisms at the symbol or packet level, such as error correction coding or swapping packet transmission opportunities. To improve bandwidth utilization and satisfy users' QoS requirements, high-level adaptive mechanisms working at larger time scale are needed. We propose an adaptive bandwidth allocation scheme, which is capable of providing QoS guarantees, ensuring long-term fairness, and achieving high bandwidth utilization. A finite-state Markov channel model (FSMC) is used to model wireless links. Internet service provider faces a daunting challenge in provisioning network efficiently. We introduce a proactive multipath routing scheme that tries to route traffic according to its built-in properties. Based on mathematical analysis, our approach disperses incoming traffic flows onto multiple paths according to path qualities. Long-lived flows are detected and migrated to the shortest path if their QoS could be guaranteed there. Suggesting nondisjoint path set, four types of dispersion policies are analyzed, and flow classification policy which relates flow trigger with link state update period is investigated. Simulation experiments show that our approach outperforms traditional single path routing significantly.