Idle Bandwidth Research Articles

Enhancing the Efficiency of Resilient Multipath-Routed Elastic Optical Networks: A Novel Approach for Coexisting Protected and Unprotected Services with Idle Slot Reuse.

In this paper, we investigate a scenario in which protected and unprotected services coexist in an elastic optical network under dynamic traffic. In the investigated scenario, unprotected services can reuse the reserved idle bandwidth to provide protection to the protected services. Under this scenario, we propose a new heuristic algorithm that enables such reuse as well as define and introduce a new assignment problem in elastic optical networks, named a Transmission Spectrum Assignment (T-SA) problem. In this paper, we consider a scenario in which services may be routed using the multipath routing approach. Additionally, protection using bandwidth squeezing is also considered. We assess our proposal through simulations on three different network topologies and compare our proposal against the classical protection approach, in which bandwidth reuse is not allowed. For the simulated range of network loads, the maximum (minimum) blocking probability reduction obtained by our proposal is approximately 48% (10%) in the European topology, 46% (7%) in the NSFNET topology, and 32% (6%) in the German topology.

Utilizing User Bandwidth Resources in Information-Centric Networking through Blockchain-Based Incentive Mechanism

Idle bandwidth resources are inefficiently distributed among different users. Currently, the utilization of user bandwidth resources mostly relies on traditional IP networks, implementing relevant techniques at the application layer, which creates scalability issues and brings additional system overheads. Information-Centric Networking (ICN), based on the idea of separating identifiers and locators, offers the potential to aggregate idle bandwidth resources from a network layer perspective. This paper proposes a method for utilizing user bandwidth resources in ICN; specifically, we treat the use of user bandwidth resources as a service and assign service IDs (identifiers), and when network congestion (the network nodes are overloaded) occurs, the traffic can be routed to the user side for forwarding through the ID/NA (Network Address) cooperative routing mechanism of ICN, thereby improving the scalability of ICN transmission and the utilization of underlying network resources. To enhance the willingness of users to contribute idle bandwidth resources, we establish a secure and trustworthy bandwidth trading market using blockchain technology. We also design an incentive mechanism based on the Proof-of-Network-Contribution (PoNC) consensus algorithm; users can “mine” by forwarding packets. The experimental results show that utilizing idle bandwidth can significantly improve the scalability of ICN transmission under experimental conditions, bringing a maximum throughput improvement of 19.4% and reducing the packet loss rate. Compared with existing methods, using ICN technology to aggregate idle bandwidth for network transmission will have a more stable and lower latency, and it brings a maximum utilization improvement of 13.7%.

Predictive edge caching through deep mining of sequential patterns in user content retrievals

Edge caching plays an increasingly important role in boosting user content retrieval performance while reducing redundant network traffic. The effectiveness of caching ultimately hinges on the accuracy of predicting content popularity in the near future. However, at the network edge, content popularity can be extremely dynamic due to diverse user content retrieval behaviors and the low-degree of user multiplexing. It is challenging for the traditional reactive caching systems to keep up with the dynamic content popularity patterns. In this paper, we propose a novel Predictive Edge Caching (PEC) system that predicts the future content popularity using fine-grained learning models that mine sequential patterns in user content retrieval behaviors, and opportunistically prefetches contents predicted to be popular in the near future using idle network bandwidth. Through extensive experiments driven by real content retrieval traces, we demonstrate that PEC can adapt to highly dynamic content popularity at network edge, and significantly improve cache hit ratio and reduce user content retrieval latency over the state-of-art caching policies. More broadly, our study demonstrates that edge caching performance can be boosted by deep mining of user content retrieval behaviors.

Integrated QoS management technique for internet protocol storage area networks

The increasing number of Information Technology Users around the world has led to tremendous increase in the amount of data that requires storage. Traditional implementations of storage area networks are not able to meet the increasing demand for storage capacity as well as a reduction in the operational and capital expenditures. In response to this challenge, new storage area network architectures based on Ethernet (IP) have evolved. IP storage network is a network of storage devices where the underlying technology is based on IP protocol. The creation Internet protocol storage SANS is enabled by the use of iSCSI protocol which makes it possible for SCSI commands to be transmitted over IP network. Meanwhile, storage QoS has become of great importance with the need of assuring a suitable storage service to the clients who share the same pool of IP storage. With the coexistence of storage traffic with other types of traffic in the same IP network, it is important to offer storage traffic QoS guarantees to prevent performance degradation for storage users. Regrettably, the storage device itself does not provide any capability of guaranteeing storage QoS. The research process involved four stages: This first stage involved systematics review of literature to determine techniques for providing QoS in IP networks and then categorized based on performance isolation, bandwidth management and burst handling. However most of the techniques reviewed were found to implement QoS techniques in the storage devices themselves which means the same algorithm run on different devices. In addition, the reviewed techniques did not put into consideration the network statistics when assigning resources. The second stage involved the optimization of QoS techniques for performance isolation, bandwidth management and burst handling for users in IP SANs. Third phase involved the integration of performance isolation, bandwidth management and burst handling techniques for QoS in IP SANs. The fourth stage involved the validation of the integration of the QoS techniques of performance isolation, bandwidth management and validation of the integrated technique based on the response time, throughput and jitter QoS metrics. To optimize the performance isolation, the study formulates an optimization problem to find optimal performance isolation schedule and use it to bind resources to class of users. The study optimized the process of matching packets to rules by sorting rules based on priority, splitting rules and use of a linear tree rue structure. Experimental results generated proves that the proposed performance isolation technique show significant reduction in response time and increase in throughput.To optimize bandwidth management also formulate an optimization problem to find out the optimal bandwidth allocation for optimal burst handling using network statistics. The research put forward HPDDRR a hierarchical priority based scheduling technique that used a quantum generated based network statistics and priority of users. Experiments results proves that HPDDRR is able to allocated bandwidth proportionate to the user’s priority and when there is idle bandwidth is shared based on priority. The results further show that users that generate burst within their allowed limits do not miss deadlines.

Effective Utilization of An Unused Bandwidth in IEEE 802.16 Network

A large percentage of available bandwidth in IEEE 802.16 networks can be utilised by using previous unused bandwidth. This is a common problem that occurs inside IEEE 802.16 networks, and it manifests itself when a subscriber station in an IEEE 802.16 network's Quality of Service (QOS) assured services is unable to predict how much data is being held back as unused bandwidth. As a direct consequence of this fact, the ongoing research has proposed simulating the process by which the remainder of the reserved bandwidth that is not being used will be recycled in order to enhance the Quality of Service and preserve the existing bandwidth reservation. Therefore, it was conceived that bandwidth might be reserved in the subscriber station separately from the bandwidth that is used for the downlink and the uplink of data transmission. This would prevent wasting the bandwidth. Through the utilization of an appropriate scheduling strategy associated with Round Robin, a simulation of an allocation of unoccupied bandwidth was carried out. The simulation findings reveal that an optimised bandwidth can ensure that the model can recycle 50–60 percent of the average amount of idle bandwidth. This is achieved through the allocation of unused bandwidth scheduling techniques. The findings of this research have demonstrated that it is possible to estimate the amount of data that is set aside as unused bandwidth and reuse it.

An approach of data analysis to improve scheduling efficiency in optical burst switched networks

SummaryScheduling at the core node plays an important role in the transmission performance of optical burst switched (OBS) networks. There are two approaches of scheduling for an incoming burst: with void filling and without void filling, where the scheduling with void filling is more efficient thanks to the ability to exploit the idle bandwidth between scheduled bursts. However, the scheduling success depends on factors such as arrival time, burst length, last available unused time (LAUT), void start time, void end time, and so forth. This paper proposes a scheduling data analysis approach to find the factors that influence scheduling efficiency, thereby suggesting an FDL‐based solution to reduce data loss. The results of analysis and simulation show that the derived factors including the last overlap and the near‐last overlap have the most significant influence on the scheduling success rate and the FDL‐based solution is best suited for loss reduction.

Spectrum Pricing in Cognitive Radio Networks: An Analysis

The wireless technology is applied in developing various applications in different trust areas. Due to this there is a huge demand for the spectrum band. The available spectrum can be shared among the primary users and the secondary users. The spectrum is utilized by the secondary user on rental basis. In this competitive world, the primary users provide a good quality for services to the end users for retaining the spectrum band. The pricing is one of the vital components in Cognitive Radio Networks (CRN) for owning/renting the spectrum. The spectrum is utilized by the secondary users when the spectrum is in idle state. This research work focuses on the spectrum pricing for the secondary users based on the price paid by the primary user. The primary users generate revenue, the same price is utilized for maintenance or annual fees which is to be paid to the governance of telecommunication department. The pricing and trading issues is one of the research areas for allocating the spectrum to the primary users. This research work focuses on providing spectrum to the secondary users with the minimal price for utilization during the specified time. The work highlights the open fact that there is a huge scarcity of the spectrum and the price are high, and not affordable to the individuals. Hence primary users lease/rent out the idle bandwidth for the secondary user. To utilize the spectrum for a dedicated period of time the secondary user has to pay the usage charges to the primary user. In this research work, various methods are presented for determining the price for the secondary users. The pricing components are analyzed by adapting the one-way Anova which compares the values among the groups. The results indicates that all the group means are not same and they are independent variables.

Data prefetching and file synchronizing for performance optimization in Hadoop-based hybrid cloud

Driven by the technical factors such as system reliability, bandwidth constraints, data confidentiality and security, as well as the economic factors such as initial capital expenditure and re-occurring operating expenditure, today's cloud computing tends to adopt hybrid cloud model. However, because hybrid clouds scale both numerically and geographically, the network delay becomes the main constraint in remote file system access. To hide network latency and reduce job completion time in Hadoop-based hybrid cloud data access, a scheduling-aware data prefetching scheme to enhance non-local map task's data locality in Hadoop-based centralized hybrid cloud (CHCDLOS-Prefetch) and a file synchronizing method to decrease job execution delay in Hadoop-based distributed hybrid cloud (DHCDLO-Sync) are proposed. In the former, input data for non-local map tasks are fetched ahead of time to target compute nodes by making use of idle network bandwidth. In the latter, considered from job level scheduling, data files with high popularity are proactively synchronized beforehand among sub-clouds to strength intra sub-cloud data locality in distributed hybrid cloud. Extensive experimental results illustrate that compared to the Capacity, the Fair and the DARE algorithms, our proposed algorithms improve hybrid cloud performance more significantly in data locality and job completion time.

Resource Allocation in Heterogeneous Cognitive Radio Network With Non-Orthogonal Multiple Access

In this paper, we study resource allocation problems for a two-tier cognitive heterogeneous network in interweave spectrum sharing mode. Secondary users (SUs) in small cells (SCs) opportunistically access the licensed spectrum resources. Non-orthogonal multiple access (NOMA) is used to boost the number of accessible SUs sharing the limited and dynamic licensed spectrum holes. Practically, there exists a tradeoff: an SC can increase its instantaneous sum throughput by accessing more idle bandwidth, which creates higher liability due to the dynamics of licensed spectrum and contention among the multiple SCs. Aiming to maximize the sum throughput of second-tier SCs network, we formulate a mixed integer non-linear programming problem with the constraints of the available idle bandwidth, the successive interference cancellation complexity, the transmission power budget, and the minimum data requirements. To efficiently solve this problem, we decompose the original optimization problem into bandwidth resource allocation subproblem, SUs clustering subproblem, and power allocation subproblem. Based on the scale of SCs network and the activities of licensed spectrum, we introduce an optimal bandwidth configuration to maximize the average sum throughput of SCs. By analyzing the derivation of the achievable rate expression of a NOMA-enabled SU, we develop a novel SUs clustering algorithm which can improve the throughput of a cluster by grouping SUs with more distinctive channel conditions. With the results of SUs clustering, we propose power allocation within a NOMA cluster by using Karush-Kuhn-Tucker optimality conditions. Furthermore, we perform power allocation across NOMA clusters by using the difference of convex programming. The simulation results validate the performance of the proposed resource allocation algorithms.

Data locality optimization based on data migration and hotspots prediction in geo-distributed cloud environment

With the explosive growth of data-intensive mobile, social, commercial and industrial applications, geo-distributed cloud becomes the main trend of cloud computing due to its advantages of higher flexible scalability, stronger stability, lower latency, and more diverse services. Due to the limited network bandwidth, communication across geographic data centers typically suffers from wide-area latencies, which significantly deteriorates system performance. Data locality is an effective way to solve this problem. In order to provide flexible cloud computing services for data-intensive applications, combining with the advantage of geo-distributed cloud computing paradigm, this paper proposed a data locality optimization method based on data migration (DLO-Migrate) and a data locality optimization algorithm based on hotspots prediction (DLO-Predict) to reduce data access delay in geo-distributed cloud environment. In DLO-Migrate method, tasks are assigned according to node locality, and access data of non-node-locality tasks are migrated in advance by using the idle network bandwidth. In DLO-Predict algorithm, from cloud-level data locality perspective, hot files are predicted and synchronized periodically among data centers of the geo-distributed cloud during information interaction. Extensive experimental results show that, compared with baseline algorithms, our proposed algorithms can improve data locality of geo-distributed cloud and reduce job completion time substantially.

Watt-level widely tunable femtosecond mid-infrared KTiOAsO4 optical parametric oscillator pumped by a 1.03 μm Yb:KGW laser.

A high-power, high-repetition-rate, broadband tunable femtosecond optical parametric oscillator (OPO) is constructed based on KTiOAsO4 crystal, pumped by a 75.5MHz mode-locked Yb:KGW laser. With 7W pump power, the OPO generates as much as 2.32W of signal power at 1.55μm and 1.31W of idler power at 3.05μm, corresponding to a total conversion efficiency of 51.8%. Operating at 151MHz repetition rate, the wavelength of the signal covers 1.41-1.71μm with a tunable idler range of 2.61-3.84μm. The idler bandwidth is more than 180nm over the entire mid-infrared range. By compensating intracavity dispersion, the signal pulse has a nearly Fourier transform-limited duration of 129fs at 1.52μm.

Tunable few-cycle pulses from a dual-chirped optical parametric amplifier pumped by broadband laser

We propose a dual-chirped optical parametric amplification (DC-OPA) scheme pumped by a broadband laser pulse. The pump pulse is spectrally broadened in a multi-plate system before amplifying the chirped seed in a BBO crystal. The system performance and phase-matching mechanism with different pump bandwidths are investigated thoroughly. It is found that the broadened pump bandwidth benefits the system most effectively when the pump and seed pulses are oppositely chirped. The idler bandwidth is nearly tripled in the broadband pumped system, supporting a transform-limited (TL) duration of 8.4fs (∼1.3cycles), meanwhile the energy bandwidth product of the idler is 72.6% higher. Furthermore, the idler wavelength is tunable between 1700nm and 2050nm, with sub-1.5-cycle TL duration and over 14% conversion efficiency. The proposed scheme provides a suitable approach for the generation of few-cycle pulses varying from near-infrared to mid-infrared regions.

A refunding strategy: opportunistic user association with congestion-based pricing in macro-femto hybrid network

Femtocell technology addresses the severe problems of poor network capacity and indoor coverage. Meanwhile, the emergence of high-capacity air interfaces and dense deployment of small cells result in increasingly high backhaul cost in cellular wireless networks. Purchasing on leased lines can guarantee the service provision during busy hours, however, purchased capacity goes to waste in off-peak time. Hybrid mode is the most promising one among all femtocell access modes which allows macro users to associate with adjacent femtocells with idle bandwidth resources. Femto holder (FH) is egoistic and unwilling to share bandwidth with transferred users from macrocells without any compensation, thus the successful implementation of hybrid access becomes a challenging problem. In this paper, we present an economic refunding framework to motivate hybrid access in femtocells. Macro users can opportunistically associate with adjacent femtocells with excess backhaul capacity. FH can receive certain refunding from wireless service provider (WSP) in exchange for traffic offloading. FH employs congestion pricing policy so as to control the cell load in the femtocell. Within this framework, we design a general utility maximization problem for user association that enables macro users to associate with femtocells based on traffic status, cell load, and access price. Dual decomposition is used to obtain an approximate solution. The impact of congestion pricing on the aggregate throughput and load balancing is also analyzed. Extensive simulations show the proposed scheme achieves a remarkable throughput gain compared with that with no compensation and compensation with usage-based pricing policy. Load balancing is substantially improved as well.

New Bandwidth Sharing and Pricing Policies to Achieve a Win-Win Situation for Cloud Provider and Tenants

For predictable application performance or fairness in network sharing in clouds, many bandwidth allocation policies have been proposed. However, with these policies, tenants are not incentivized to use idle bandwidth or prevent link congestion, and may even take advantage of the policies to gain unfair bandwidth allocation. Increasing network utilization while avoiding congestion not only benefits cloud provider but also the tenants by improving application performance. In this paper, we propose a new pricing model that sets different unit prices for reserved bandwidth, the bandwidth on congested links and on uncongested links, and makes the unit price for congested links proportional to their congestion degrees. We use game theory model to analyze tenants’ behaviors in our model and the current pricing models, which shows the effectiveness of our model in providing the incentives. With the pricing model, we propose a network sharing policy to achieve both min-guarantee and proportionality, while prevent tenants from earning unfair bandwidth. We further propose methods for each virtual machine to arrange its traffic to reduce its unsatisfied demand and maximize its utility, while increase network utilization. As a result, our solution creates a win-win situation, where tenants strive to increase their benefits in bandwidth sharing, which also concurrently increases the utilities of cloud provider and other tenants. Our simulation and trace-driven experimental results show the effectiveness of our solutions in creating the win-win situation.

Broadband femtosecond parametric amplification in KTA close to mid-IR transparency cutoff

We report an increase in conversion efficiency and significant broadening of signal and idler bandwidth in the collinear KTA optical parametric amplifier operating close to mid-IR transparency cutoff (5.2 μm) for a visible and near IR pump. Using a 1.24 μm pump we have produced 2 μJ idler pulses at 3.8 μm central wavelength with a bandwidth supporting 65 fs transform limited duration. Further tuning to mid-IR up to 5 μm could be achieved with a 620 nm pump.

FSNoC: A Flit-Level Speedup Scheme for Network on-Chips Using Self-Reconfigurable Bidirectional Channels

In this paper, we explore optimizing the bandwidth utilization of the network-on-chips (NoCs). We propose a flit-level speedup scheme to improve the NoC performance using self-reconfigurable bidirectional channels. For the NoC intrarouter bandwidth, in addition to allowing flits from different packets to use the idle internal bandwidth of the crossbar, our proposed flit-level speedup scheme also allows flits within the same packet to be transmitted simultaneously. For interrouter channels, a distributed channel configuration scheme is developed to dynamically change the link directions. In this way, the effective bandwidth between two routers can change adaptively depending on the run time network traffic. We present the implementation of the proposed flit-level speedup NoC on a 2-D mesh. An input buffer architecture, which supports reading and writing two flits from the same virtual channel at the same time, is proposed. The switch allocator is also designed to support flit-level parallel arbitration. Extensive simulations on both the synthetic traffic and real applications show performance improvement in throughput and latency over the existing architectures using bidirectional channels.

Optimization of Inter-network Bandwidth Resources for Large-Scale Data Transmission

In order to solve problems such as low resources utilization of data center backbone bandwidth and expensive daily expenses caused by the tidal effect in the transition of large-scale network data, the new optimization method of bandwidth resource for bulk data transfer is proposed. This method finishes the bulk data transfer by taking full advantage of the idle channel bandwidth. Firstly, the dynamic idle network bandwidth resource was switched into the static flow network; and then the max-min fair multi-commodity flow model is built on the basis of static network; finally, the iterative technique is used to solve the programming model for getting the maximum transport flows and the corresponding transmission path of bulk data transfer. The simulation method was used to test this optimization project. The results show that the optimization method proposed by the paper can significantly improve the utilization of data center backbone bandwidth resource, and the maximum amount of data transmission and the speed of data transfer have been obviously increased

다중 직교 시퀀스를 이용한 인지 무선 시스템의 성능

Ad hoc networks can be used under difficult conditions, where it is difficult to construct infrastructures, such as shadowing areas, disaster areas, war area, and so on. In order to support to considerable and various wireless services, more spectrum resources are needed. However, efficient utilization of the frequency resource is difficult because of spectrum scarcity and the conventional frequency regulation. Ad-hoc networks employing cognitive radio(CR) system that guarantee high spectrum utilization provide effective way to increase the network capacity. However, there is a problem that all CR user do not fairly use the primary user`s idle bandwidth which has been sensed. In this paper, to solve this problem, we propose the spectrum sharing algorithm which uses the multiple orthogonal sequences based on the code division multiple access(CDMA). From the proposed algorithm, it is expected that system performance of CR based ad-hoc network is improved significantly and it can be applied to the implementation of CR based ad-hoc network system.

On the stability and optimality of universal swarms

Recent work on BitTorrent swarms has demonstrated that a bandwidth bottleneck at the seed can lead to the underutilization of the aggregate swarm capacity. Bandwidth underutilization also occurs naturally in mobile peer-to-peer swarms, as a mobile peer may not always be within the range of peers storing the content it desires. We argue in this paper that, in both cases, idle bandwidth can be exploited to allow content sharing across multiple swarms, thereby forming a universal swarm system. We propose a model for universal swarms that applies to a variety of peer-to-peer environments, both mobile and online. Through a fluid limit analysis, we demonstrate that universal swarms have significantly improved stability properties compared to individually autonomous swarms. In addition, by studying a swarm's stationary behavior, we identify content replication ratios across different swarms that minimize the average sojourn time in the system. We then propose a content exchange scheme between peers that leads to these optimal replication ratios, and study its convergence numerically.

Transient Analysis of a Tandem Communication Network with Dynamic Bandwidth Allocation having Two Stage Direct Bulk Arrivals

ABSTRACT Communication network models play a dominant role in optimal utilization of resources. The need for congestion control and to improve quality of service, it is needed to design new communication networks. With this motivation, a two node communication network with dynamic bandwidth allocation (DBA) having two stage bulk arrivals (BA) is introduced and analyzed. The statistical multiplexing of the communication network is developed by characterizing the arrival of packets with compound Poisson process and the transmission completions with Poisson processes. To avoid burstness in buffers, the dynamic bandwidth allocation is adapted utilizing the idle bandwidth in the transmitter depending on content of the buffer. The network performance is evaluated by deriving the performance measures like mean content of the buffers, mean delays in transmitters, throughput of the nodes, utilization of the nodes etc,. The transient analysis of the model reveals that the time has a significant influence on predicting the performance measures of the communication networks. The sensitivity analysis of the model provides evidence that the dynamic bandwidth allocation strategy along with bulk arrival consideration can provide the performance of the network more close to the reality and avoid burstness in buffers. This communication network is much useful for Satellite and Mobile communication, Computer communication etc. This communication network model also includes several of the earlier communication network models as particular cases for specific values of the model parameters.