Efficient Network Utilization Research Articles

Studying the spatiotemporal variations of the ecological network and carbon utilization efficiency in Southeast Tibet based on complex network theory

Studying the spatiotemporal variations of the ecological network and carbon utilization efficiency in Southeast Tibet based on complex network theory

Intelligent wireless resource management in industrial camera systems: Reinforcement Learning-based AI-extension for efficient network utilization

Intelligent wireless resource management in industrial camera systems: Reinforcement Learning-based AI-extension for efficient network utilization

Enhancement of failure independent path protection preconfigured cycles for electric power communication networks

Enhancement of failure independent path protection preconfigured cycles for electric power communication networks

An adaptive space-step simulation approach for steam heating network considering condensate loss

Steam heating plays an irreplaceable role in industrial productions and occupies a specific proportion of the total heating load. High-precision and efficient simulation is of substantial significance to the economical operation, safety and reliability and energy utilization efficiency of the steam heating network. Widely applicable and adequately accurate simulation approach for the steam heating network is in necessity. A novel adaptive space-step simulation approach for steam heating network considering the condensate loss is developed in this paper. The model equations are precisely derived from the primitive differential equations based on the trapezoidal formula and reorganized into the matrix form for computation acceleration. Meanwhile, a quasi-linear fitting method is proposed to simplify the calculation of steam enthalpy. To solve the model, the computation process is decoupled as hydraulic calculation and thermal calculation, and the converge is achieved through alternating iterative algorithm. The condensate check is introduced after the thermal calculation, in which the condensate loss can be calculated. To acquire the expected simulation precision, an adaptive space-step determination method is developed, in which minimum number of nodes are automatically added to divide long pipes into shorter segments. Finally, case study is conducted on single pipeline cases and a 20-node network. Results show that the proposed approach is applicable to networks containing superheated and saturated steam simultaneously. The error can be controlled to the initially set precision of 0.1 kPa and 0.1 °C through space-step adaption, and nodes are mostly added near the transition point from superheated steam to saturated steam for precision need. • Precise modeling is carried out considering the changes of steam parameters along the pipe. • A quasi-linear fitting method is proposed to simplify the steam enthalpy calculation. • The model is applicable for both superheated and saturated steam, and can calculate condensate loss. • A space-step adaption method is proposed. Nodes are automatically added to divide long pipes into shorter sections. • An alternating iterative algorithm is proposed based on decoupling of matrix-formed hydraulic and thermal equations.

Fast and scalable routing protocols for data center networks

Data center networks may comprise tens or hundreds of thousands of nodes, and, naturally, suffer from frequent software and hardware failures as well as link congestions. Packets are routed along the shortest paths with sufficient resources to facilitate efficient network utilization and minimize delays. In such dynamic networks, links frequently fail or get congested, making the recalculation of the shortest paths a computationally intensive problem. Various routing protocols were proposed to overcome this problem by focusing on network utilization rather than speed. Surprisingly, the design of fast shortest-path algorithms for data centers was largely neglected, though they are universal components of routing protocols. Moreover, parallelization techniques were mostly deployed for random network topologies, and not for regular topologies that are often found in data centers. The aim of this paper is to improve scalability and reduce the time required for the shortest-path calculation in data center networks by parallelization on general-purpose hardware. We propose a novel algorithm that parallelizes edge relaxations as a faster and more scalable solution for popular data center topologies.

Reconfiguration of Uganda's bulk network to accommodate a wholesale electricity market

Countries that have restructured their electricity markets to wholesale markets have had significant benefits, including reduced generation costs, lower transmission losses and better consumer prices. In these markets, generators are dispatched in such a way that the financial benefits of both generator owners (producer surplus) and consumers (consumer surplus) are maximized. Retailers and large-scale consumers transact directly with power producers in a spot market or through contracts at wholesale level. Uganda's current single-buyer market (in which generation companies sell their power to a single entity that in turn transmits and sells it to distribution companies) was introduced in 2001 after the transition from a vertically integrated monopoly model. The market is expected to evolve into a wholesale market as the next restructuring step. This paper investigates the performance of the Uganda bulk network in a wholesale electricity market environment as modelled in Power World simulator. It considers different operation scenarios and possible infrastructure enhancements required for improved performance. Results showed that in the wholesale market model, transmission energy losses fell from an average of 4.3% to 3.8% compared to the single-buyer model due to more efficient network utilization. The economic analysis showed that off-peak and peak prices in the wholesale market system were 68.6% and 13.5% lower than in the current market respectively. However, old high loss transmission lines contributed to higher energy prices at receiving nodes. Transmission congestion, whose cost is embedded in a Location Marginal Price, caused sharp increases in the market's prices; this was addressed by using the network reconfiguration technique.

Influence of distribution tariff structures and peer effects on the adoption of distributed energy resources

• The theory of planned behavior was formalized into an agent-based model. • The model considers the interplay of DERs adoption and distribution tariff evolution. • Non-economic factors limits the rate of adoption in the short-term. • Distribution tariff structures can influence DERs adoption patterns. • DSOs should take a whole system approach to manage the electricity system. The emergence of prosumers calls for a revision of distribution network tariff design to ensure efficient network utilization and optimal customer response. This article aims to investigate the influence of different distribution tariff structures and peer effects on both residential consumers’ distributed energy resources adoption and the allocation of electricity distribution costs. We developed an agent-based model to analyze the interaction between distribution tariffs and the adoption of distributed energy resources. The model takes into account the influence of both economic (e.g., payback period and income level) and non-economic (e.g., peer effects) factors on technology adoption. The model endogenously considers the interplay between the technology adoption and the evolution of distribution tariffs and takes into account the interaction among consumers by incorporating peer effects. We found that under our test case assumptions, the presence of non-economic factors in the decision making, such as peer effects, is the rate-limiting step of the adoption process in the short-term. Hence, creating mechanisms that encourage interpersonal communication among residential consumers may help more risk-averse consumers redefine their attitudes about the benefits and costs of adopting distributed energy resources. We also found that a utility death spiral is more likely to occur with an annual net-volumetric distribution tariff. The increase in distribution cost was ten percentage points higher than that obtained with an annual maximum offtake capacity tariff. Given the complexities of an electricity system where the consumer is at the center, we recommend that regulators and distribution system operators adopt a whole system approach to managing the electricity system.

Experimental study of flue gas condensing heat recovery synergized with low NOx emission system

To improve overall thermal efficiency while simultaneously reducing the NOx emissions of gas boilers, a novel flue gas condensation heat recovery and low NOx emission system that integrates a direct contact heat exchange unit with a combustion air humidification unit is proposed. A well-designed experimental system was established and a test bench was set up to study the effects of variable multi-factor operating conditions on the waste heat recovery and NOx emission properties. The synergistic enhancement principle between the flue gas waste heat recovery process and low nitrogen emission is described in detail. The dew point temperature of the flue gas is improved significantly by humidifying the combustion air, which contributes to both low nitrogen emission and full waste heat recovery. The experimental results show that when the combustion air humidity ratio increased from the zero-humidification condition to 49.0 g/kgdry air, the dew point temperature of the flue gas increased by 6.4 °C. At a spray water flow rate of 0.83 m3/h and with a heat supply network return water temperature of 45 °C, the flue gas waste heat recovery efficiency and the waste heat utilization efficiency of the heat supply network increased by up to 12.2% and 6.9%, respectively, and the average NOx emissions decreased to 50.0 mg/m3. In the NE mode, with a spray water flow rate of 1.03 m3/h, the combustion air humidity ratio is increased to 101.2 g/kgdry air, the NOx emission reduction procedure is more effective and can be reduced to 23.3 mg/m3. The experimental system offers advantages in terms of energy savings, environmental protection, and economic benefits, and also outperforms other competing systems with respect to these issues.

Evaluation of Network Blocking Probability and Network Utilization Efficiency on Proposed Elastic Optical Network using RSA Algorithms

AbstractElastic optical networks (EONs) are new generation optical networks that provide flexible bandwidth and spectrum assignment characteristics to accommodate diverse demand range over traditional dense wavelength division multiplexing (DWDM)-based networks. While overcoming spectrum contiguity and continuity constraints, Routing and Spectrum Assignment (RSA) is a challenging task in EONs. In this article, we have proposed an EON network model. Using existing RSA techniques we have analyzed the performance of the proposed model on the basis of Network Blocking Probability (NBP) and Network Utilization Efficiency (NUE) under variable load conditions. It has been found to be working optimally even at a load of 200 Erlangs.

A Review of the Control Plane Scalability Approaches in Software Defined Networking

Recent advances in information and communications cloud-based services hold the potential to overcome the scalability and complex maintenance limitations of traditional networks. Software Defined Networking (SDN) surfaced as a promising paradigm to mitigate such limitations while offering flexible networks management. Particularly, SDN separates the control plane from the data plane to achieve abstraction of lower-level functionality, hence, allowing more efficient network management and utilization. However, SDN suffers from various performance and scalability problems leading to significant research efforts on maximizing the scalability of the control plane. This paper aims at reviewing different SDN controller scalability, topology-based and mechanism-based approaches, as well as discussing and analyzing how they attempt to solve the scalability challenge. Furthermore, this paper elaborates on the promising research trends and challenges. Our insights are also discussed to stimulate further research efforts addressing the control plane scalability in SDN.

Fault detection of nonlinear stochastic systems via a dynamic event-triggered strategy

Abstract This paper studies the fault detection problem of nonlinear stochastic systems with randomly occurring nonlinearity and missing measurements via a dynamic event-triggered strategy. Firstly, the dynamic event-based data transmission strategy is provided to increase network utilization efficiency, while the data transmission threshold is changed with an adaptive function. This design idea can reduce network transmission pressure more effectively than the traditional one with fixed threshold. Secondly, two independent Bernoulli stochastic sequences are provided to describe the randomly occurring nonlinearity and measured-data packet dropout phenomenon, respectively. By considering time-varying delays, dynamic event-triggered strategy, randomly occurring nonlinearity and packet dropout simultaneously, a unified dynamic model for fault detection is established to generate mean-square asymptotical stability and desirable detection performance. Three examples are finally provided to generate the practicability of proposed technique.

Bridging the Transition from IEEE 802.11ac to IEEE 802.11ax: Survival of EDCA in a Coexistence Environment

TGax aims at developing the IEEE 802.11ax protocol to provide enhanced throughput and power efficiency in dense WiFi deployment environments. The new specification shifts the focus from EDCA access to point coordination access, which aims at improving network utilization and power efficiency. Furthermore, it introduces, for the first time, the concept of RU allocation and orthogonal frequency division multiple access (OFDMA) techniques. The new specification addresses the spectral inefficiency in existing transmission by including schedule-based multi-user multiple-input, multiple- output (MU-MIMO) and multi-user OFDMA (MU-OFDMA) techniques to facilitate multi-user uplink transmission for high efficiency (HE) devices. However, complete adoption of the HE protocol is likely to take place over a period of time to offset the deployment cost. To ensure the coexistence of non-HE devices during the transition period, EDCA based single user transmission will remain the basic access technique and a focal point of spectral inefficiency for non-HE devices in the uplink direction. Motivated by our work on the performance of IEE 802.11ac, we propose an EDCA based uplink transmission technique for non-HE devices that allows multi-user transmission to improve spectral efficiency in coexistent WLAN networks.

Oblivious Routing in IP Networks

To optimize the flow of traffic in IP networks, operators do traffic engineering (TE), i.e., tune routing-protocol parameters in response to traffic demands. TE in IP networks typically involves configuring static link weights and splitting traffic between the resulting shortest-paths via the equal-cost-multipath (ECMP) mechanism. Unfortunately, ECMP is a notoriously cumbersome and indirect means for optimizing traffic flow, often leading to poor network performance. Also, obtaining accurate knowledge of traffic demands as the input to TE is a non-trivial task that may require additional monitoring infrastructure, and traffic conditions can be highly variable, further complicating TE. We leverage recently proposed schemes for increasing ECMP’s expressiveness via carefully disseminated bogus information (lies) to design COYOTE, a readily deployable TE scheme for robust and efficient network utilization. COYOTE leverages new algorithmic ideas to configure (static) traffic splitting ratios that are optimized with respect to all (even adversarial) traffic scenarios within the operator’s “uncertainty bounds”. Our experimental analyses show that COYOTE significantly outperforms today’s prevalent TE schemes in a manner that is robust to traffic uncertainty and variation. We discuss experiments with a prototype implementation of COYOTE.

Optimal Flow Rate Control for SDN-Based Naval Systems

It is essential for a naval ship system (NSS) to transmit important information with very low delay for successful network-centric warfare under given time constraints. From this perspective, quality of service (QoS) control and low delay transmission are the most important components to improve efficient network utilization in NSSs. In general networks, conventional network algorithms have been optimized to manage network devices such as gateway, switch, bridge, hub, and router in a distributed manner for ease of plug-in and play operation, but which may not be optimal for the NSS. This is because, unlike the general network environment, the NSS is equipped with various nodes, which need to be operated through a centralized hierarchical network structure in accordance with their priorities. Thereby, it is difficult to apply new network algorithms to the NSS due to the closed network environment. To overcome this limitation, we propose a novel NSS employing software defined network (SDN) technology. A novel algorithm called real-time transmission via flow rate control (RTF) is proposed for the SDN-based NSS to optimize the specific environment of NSS. In the proposed algorithm, the optimal flow rates of nodes and network devices are obtained via dual decomposition in conjunction with requirements of delay and QoS. The proposed algorithm obtains the optimal solution iteratively while measuring the performance with traffic models based on real data measured in NSS. Through simulation using Floodlight, we demonstrate that RTF significantly contributes to improving throughput in real-time transmission compared with conventional algorithms. The proposed algorithm improves the average throughput by up to 11.8% while guaranteeing real-time transmission.

Scheduling algorithms for time-constrained big-file transfers in the Internet of Vehicles

In order to transfer large files and provide high-quality services in the IoV (Internet of Vehicles), intelligent routing and scheduling are indispensable for fast transfers and efficient network utilization, particularly when multi-path routing is allowed in the wired-transfer. Thus, a network administrator must select a set of feasible paths over which the transfer can be conducted. We consider a TBTS (Time-constrained Big-file Transfer Scheduling) problem in this paper. We prove that TBTS problem is NP-hard and that the TBTS problem can be solved by addressing a corresponding maximum ow over time problem with multi-path routing technique. We then propose both a heuristic algorithm (TBTS-H) and an exact algorithm (TBTS-A) to solve the TBTS problem. Although both of the proposed approaches can solve the TBTS problem, the heuristic runs more efficiently by trading accuracy for delay, while the exact algorithm can achieve high accuracy for delay, at the cost of increased running-time. The corresponding simulation results illustrate this trade-off. Additionally, we conduct some comparisons between our proposed approaches and a traditional single-path routing scheme.

The Research of Internet of Things in Operation and Maintenance for Distribution Grid

This paper takes state monitoring, operation and maintenance as business application scenarios, and then introduces the application of the Internet of things technology in equipment condition monitoring, equipment assets management, operation and maintenance of distribution network. The system realizes the accurate acquisition of running status and environmental information of the distribution network equipment through the installation of RFID, the bar code / QR Code and a variety of sensor devices. The practice shows that the application of the Internet of things technology in the distribution network operation and maintenance can effectively solve the problems of insufficient condition-based maintenance method and equipment on-line monitoring and other issues, and enhance the distribution network equipment management and utilization efficiency significantly. Meanwhile, it further enriches the internet of things’ application scenarios in the grid, and effectively supports the construction of smart grid.

MemEFS: A network-aware elastic in-memory runtime distributed file system

Scientific domains such as astronomy or bioinformatics produce increasingly large amounts of data that need to be analyzed. Such analyses are modeled as scientific workflows — applications composed of many individual tasks that exhibit data dependencies. Typically, these applications suffer from significant variability in the interplay between achieved parallelism and data footprint. To efficiently tackle the data deluge, cost effective solutions need to be deployed by extending private computing infrastructures with public cloud resources. To achieve this, two key features for such systems need to be addressed: elasticity and network adaptability. The former improves compute resource utilization efficiency, while the latter improves network utilization efficiency, since public clouds suffer from significant bandwidth variability. This paper extends our previous work on MemEFS, an in-memory elastic distributed file system by adding network adaptability. Our results show that MemEFS’ elasticity increases the resource utilization efficiency by up to 65%. Regarding the network adaptation policy, MemEFS achieves up to 50% speedup compared to its network-agnostic counterpart.

Towards Promoting Backup-Sharing in Survivable Virtual Network Design

In a virtualized infrastructure where multiple virtual networks (or tenants) are running atop the same physical network (e.g., a data center network), a single facility node (e.g., a server) failure can bring down multiple virtual machines, disconnecting their corresponding services and leading to millions of dollars in penalty cost. To overcome losses, tenants or virtual networks can be augmented with a dedicated set of backup nodes and links provisioned with enough backup resources to assume any single facility node failure. This approach is commonly referred to as Survivable Virtual Network (SVN) design. The achievable reliability guarantee of the resultant SVN could come at the expense of lowering the substrate network utilization efficiency, and subsequently its admissibility, since the provisioned backup resources are reserved and remain idle until failures occur. Backup-sharing can replace the dedicated survivability scheme to circumvent the inconvenience of idle resources and reduce the footprints of backup resources. Indeed the problem of SVN design with backup-sharing has recurred multiple times in the literature. In most of the existing work, designing an SVN is bounded to a fixed number of backup nodes; further backup-sharing is only explored and optimized during the embedding phase. This renders the existing redesign techniques agnostic to the backup resource sharing in the substrate network, and highly dependent on the efficiency of the adopted mapping approach. In this paper, we diverge from this dogmatic approach, and introduce ProRed, a novel prognostic redesign technique that promotes the backup resource sharing at the virtual network level, prior to the embedding phase. Our numerical results prove that this redesign technique achieves lower-cost mapping solutions and greatly enhances the achievable backup sharing, boosting the overall network's admissibility.

Efficient Cellular Load Balancing Through Mobility-Enriched Vehicular Communications

Supporting effective load balancing is paramount for increasing network utilization efficiency and improving the perceivable user experience in emerging and future cellular networks. At the same time, it is becoming increasingly alarming that current communication practices lead to excessive energy wastes both at the infrastructure side and at the terminals. To address both these issues, this paper discusses an innovative communication approach enabled by the implementation of device-to-device (d2d) communication over cellular networks. The technique capitalizes on the delay tolerance of a significant portion of Internet applications and the inherent mobility of the nodes to achieve significant performance gains. For delay-tolerant messages, a mobile node can postpone message transmission—in a store–carry and forward manner—for a later time to allow the terminal to achieve communication over a shorter range or to postpone communication to when the terminal enters a cooler cell, before engaging in communication. Based on this framework, a theoretical model is introduced to study the generalized multihop d2d forwarding scheme where mobile nodes are allowed to buffer messages and carry them while in transit. Thus, a multiobjective optimization problem is introduced where both the communication cost and the varying load levels of multiple cells are to be minimized. We show that the mathematical programming model that arises can be efficiently solved in time. Furthermore, extensive numerical investigations reveal that the proposed scheme is an effective approach for both energy-efficient communication and offering significant gains in terms of load balancing in multicell topologies.

Supporting consumer services in a deterministic industrial internet core network

A convergence is occurring in the networking world. Industrial networks currently provide deterministic services in robotic factories and aircraft, while the best effort Internet of Things provides best effort services for consumers. We argue that a convergence should occur, and that a future converged Industrial Internet of Things (IIoT) should support both best effort and deterministic services, with very low latency and jitter. This article presents the design of a deterministic IIoT core network consisting of many simple deterministic packet switches configured by an SDN control plane. The use of deterministic communications can reduce router buffer sizes by a factor of ≥ 1000, and can reduce end-to-end latencies to the speed of light in fiber. A speed-of-light deterministic core network can have a profound impact on virtually all consumer services such as multimedia distribution, e-Commerce, and cloud computing or gaming systems. Highly aggregated video streams can be delivered over a deterministic virtual network with very high link utilization (≤ 100 percent), very low packet jitter (≤ 10 μs), and zero congestion. In addition to improving consumer services, a converged deterministic IIoT core network can save billions of dollars per year as a result of significantly improved network utilization and energy efficiency.