Unused Bandwidth Research Articles

Revisiting Mackay Online

Revisiting Mackay Online

Throughput maximisation in cognitive radio networks with residual bandwidth

Recent progress in cognitive radio networks (CRNs) promises to meet device-to-device communication requirements for spectrum utilisation and power control to support billions of machines/devices to be connected worldwide. The architecture of the CRN must maintain a high data rate (throughput) at low power consumption, which requires both spectrum efficient and energy efficient system design. To this aim, the proposed work adopts a CRN model, which operates in an interweave mode that allows spectrum sensing followed by opportunistic secondary user (SU) data transmission over the unused bandwidth of the primary user (PU) in a non-overlapping frame structure. Closed form expressions of the optimal spectrum sensing duration, bandwidth, and power allocation of each secondary node are obtained to maximise the sum throughput of the overall CRN while maintaining the constraints of sensing reliability of PU, individual SU transmission outage probability, permissible interference, and residual bandwidth. Numerical results highlight that the proposed scheme maximises the sum network throughput by $\sim 50.54$~50.54 and $\sim 63.76\%$~63.76% over the other existing techniques.

Ant Colony Optimization Based Routing for Throughput Enhancement in Cognitive Radio Network

Cognitive Radio Networks (CRNs) is promising solution to spectrum scarcity which can enhance utilization of unused bandwidth in future networks, it indicate that CRNs are familiar of context and are capable of finding unused bandwidths of licensed user or Primary User (PU) and use them for transmission by unlicensed users or Secondary User (SU). The SU must release the bandwidth when PU has to access the same bandwidth without any delay and SU might be diverted to some other route. We propose an algorithm known as the ant colony optimization (ACO) for providing effective routing to SU, it is inspired by real ant behavior which is optimized for finding good routes through graphs where multiple route are required for packet transmission resulting in an enhanced throughput. The key objective is to provide alternative path to SU while PU acquires the previous path of SU during packet transmission in an efficient manner. Simulations results using NS 2 of AODV protocol are presented to indicate the performance of the proposed solution.

Comprehensive Polling and Scheduling Mechanism for Long Reach Gigabit Passive Optical Network

Abstract Dynamic bandwidth assignment (DBA) schemes for long reach PONs face a suffer from higher upstream channel idle time due to long round trip time (RTT). In ITU PONs, the DBA schemes; Immediate allocation with colorless grant (IACG), Efficient bandwidth utilization (EBU) and GPON redundancy eraser algorithm (GREAL) minimize idle time by sending bandwidth grants to the optical network units (ONUs) every downstream frame (DF). EBU further improves IACG by utilizing unused bandwidth (UBW) of other traffic classes. Sending the grant results every DF requires optical line terminal (OLT) to remember all previous grants sent to ONU during RTT and subtract them from the received queue reports. Since, both IACG and EBU assign the excess bandwidth equally to ONUs. Therefore, the OLT is actually not aware of the complete grant to each traffic class and thus do not subtract these completely from receiving reports. This leads to wastage of bandwidth and higher US delays due to over granting. GREAL resolves this problem by not utilizing the excess bandwidth which also leads to increased US delays. The proposed scheme in this study eliminates this shortcoming by allocating excess bandwidth to each traffic class completely at the OLT. Moreover, the UBW assignment mechanism of EBU is also improved. Simulation results show a 50–85 % reduction in delays of type-2 (T2) and type-3 (T3) traffic classes versus GREAL and IACG and up to 40 % reduction in delays for type-4 (T4) versus EBU.

Towards predictable performance via two-layer bandwidth allocation in cloud datacenter

In today’s production-grade cloud datacenters, cloud service providers do not offer any bandwidth guarantee between VMs, which results in unpredictable performance of tenants’ applications. The research community has recognized this problem; however, existing solutions to bandwidth allocation fail to take into consideration tenants’ request for bandwidth and the actual bandwidth usage of applications simultaneously, which leads to a waste of bandwidth resources or unpredictable performance. To address these issues, we present SpongeNet, a bandwidth allocation solution that consists of three components through two layers—static bandwidth guarantees at the tenant layer and a dynamic rate allocation at the application layer to realize predictable performance. The first component, named FGVC model, is a network abstraction model that provides a simple, accurate and flexible way for tenants to specify network requirements and achieve high utilization through bandwidth saving. The second component is a two-phase VM placement algorithm that provides optimal combinations of ordering policies and dispatching policies to meet multiple goals. The third component, named E–F runtime mechanism, can achieve the fairness between guaranteed and unguaranteed tenants in utilizing the unused bandwidth resources. Extensive simulations based on real application traces and 3-level tree topology show that SpongeNet enhances bandwidth saving when compared to the state-of-the-art solutions (e.g., the Oktopus system), and significantly improves the throughput rate by 18% and response time by 92%. With a small prototype implementation on a 7-server testbed, we demonstrate that SpongeNet provides fair work-conserving bandwidth guarantee among all tenants, even in extreme cases.

Price Competition in Spectrum Markets: How Accurate is the Continuous Prices Approximation?

Dynamic spectrum access technology enables two types of users to operate on a channel–primary users and secondary users, which can use the channel when it is not in use by the primaries. We consider a scenario in which multiple primaries own bandwidth in a large region which is divided into smaller locations. A primary that has unused bandwidth in a time slot would like to lease it out to secondaries in return for a fee. This results in price competition among the primaries. In prior work, this price competition has only been studied under the approximation, made for analytical tractability, that the price of each primary takes values from a continuous set. However, in practice, the set of available prices is discrete. In this paper, we investigate the fundamental question of how the behavior of the players involved in the price competition changes when this continuity assumption is removed. Our analysis reveals several important differences between the games with continuous and discrete price sets. However, we show that as the number of available prices becomes large, the strategies of the primaries under every symmetric NE converge to the unique NE strategy of the game with continuous price sets.

Development of Bi/Er co-doped optical fibers for ultra-broadband photonic applications

Targeting the huge unused bandwidth (BW) of modern telecommunication networks, Bi/Er co-doped silica optical fibers (BEDFs) have been proposed and developed for ultra-broadband, high-gain optical amplifiers covering the 1150–1700 nm wavelength range. Ultrabroadband luminescence has been demonstrated in both BEDFs and bismuth/erbium/ytterbium co-doped optical fibers (BEYDFs) fabricated with the modified chemical vapor deposition (MCVD) and in situ doping techniques. Several novel and sophisticated techniques have been developed for the fabrication and characterization of the new active fibers. For controlling the performance of the active fibers, post-treatment processes using high temperature, g-radiation, and laser light have been introduced. Although many fundamental scientific and technological issues and challenges still remain, several photonic applications, such as fiber sensing, fiber gratings, fiber amplification, fiber lasers, etc., have already been demonstrated.

Comprehensive bandwidth utilization and polling mechanism for XGPON

SummaryFor an efficient utilization of the upstream bandwidth in passive optical network, a dynamic bandwidth assignment mechanism is necessary as it helps the service providers in provisioning of bandwidth to users according to the service level agreements. The scheduling mechanism of existing schemes, immediate allocation with colorless grant and efficient bandwidth utilization (EBU), does not assign the surplus bandwidth to a specific traffic class and only divides it equally among the optical network units (ONUs). This results in overreporting of ONU bandwidth demand to the optical line terminal and causes wastage of bandwidth and increase in delays at high traffic loads. Moreover, the EBU also assigns the unused bandwidth of lightly loaded ONU queues to the overloaded queues through an Update operation. This Update operation has a flaw that it borrows the extra bandwidth to a queue in the current service interval, if the queue report is higher than its service level agreement and refunds in next service interval. This borrow‐refund operation causes reduced bandwidth allocation to the lower priority classes and increases their delay and frame loss. This study improves both these weaknesses. The simulation results show that the proposed scheme uses bandwidth efficiently and reduces mean upstream delay of type‐2 (T2) traffic class by 38% and type‐3 (T3) up to 150% compared to immediate allocation with colorless grant at a cost of up to 10% higher delay for T2. However, T4 performance improves by 400% compared to EBU with slight increase in delay for T2 traffic class. Overall, it shows a balanced performance for all the traffic classes and minimizes the bandwidth waste per cycle as well as the frame loss rate.

Combinatorial Auction-Based Two-Stage Matching Mechanism for Mobile Data Offloading

In this paper, we study the problem of mobile data offloading for a network that contains multiple mobile network operators (MNOs), multiple WiFi or femtocell access points (APs) and multiple mobile users (MUs). MNOs offload their subscribed MUs` data traffic by leasing the unused Internet connection bandwidth of third party APs. We propose a combinatorial auction-based two-stage matching mechanism comprised of MU-AP matching and AP-MNO matching. The MU-AP matching is designed to match the MUs to APs in order to maximize the total offloading data traffic and achieve better MU satisfaction. Conversely, for AP-MNO matching, MNOs compete for APs` service using the Nash bargaining solution (NBS) and the Vickrey auction theories and, in turn, APs will receive monetary compensation. We demonstrated that the proposed mechanism converges to a distributed stable matching result. Numerical results demonstrate that the proposed algorithm well capture the tradeoff among the total data traffic, social welfare and the QoS of MUs compared to other schemes. Moreover, the proposed mechanism can considerably offload the total data traffic and improve the network social welfare with less computation complexity and communication overhead.

Transparent bandwidth aggregation for residential access networks

AbstractWe propose, implement, and evaluate a bandwidth aggregation service for residential users that allows to improve the upload throughput of the asymmetric digital subscriber line connection by leveraging the unused bandwidth of neighboring users. The residential access gateway adopts the 802.11 radio interface to simultaneously serve the local home users and to share the broadband connectivity with neighboring access gateways. Differently from previous works, our aggregation scheme is transparent both for local users, who are not required to modify their applications or device drivers, and for neighboring users, who do not experience any meaningful performance degradation. To evaluate the achievable performance and tune the parameters driving the traffic balancing, we developed a fluid model that was shown experimentally to be very accurate. Our proposed scheme is amenable to efficient implementation on Linux networking stack. Indeed, we implemented it and tested in some realistic scenarios, showing an efficient exploitation of the whole available bandwidth, also for legacy cloud storage applications.

An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system

ABSTRACTChannel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space–time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space–time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.

SNR Improvement and Bandwidth Optimization Technique Using PCM-DSSS Encryption Scheme

Cryptography, the scheme of information stashing and verification, entirely deals with protocols, algorithms and strategies to ensure the precise security facility of the signal consistently by hindering unauthorized access to the confidential information. Albeit in most of the encryption schemes, certain impediments are faced by the service providers such as the expansion of required bandwidth, the fragile encryption technique, the consumption of maximum bandwidth in security purpose, less priority to improvement of SNR of the system, the complexity in decryption and so forth. This paper illustrates the SNR enhancement & bandwidth optimization technique in security purpose using PCM- DSSS sample by sample encryption scheme. For this purpose, after sampling of a signal, simple mathematical operation is performed in each sample with a time varying arbitrary weights. This arbitrary weight can be obtained from D/A conversion of pseudo noise sequence. Since the bandwidth consumption in security purpose can be minimized in this scheme, a significant portion of unused bandwidth can be used to improve the SNR of the system by reducing quantization noise of encrypted samples. By the same token, the possibility of SNR improvement is demonstrated by reckoning the quantization noise while introducing additional quantization step.

Circumventing plateaux in cellular data offloading using adaptive content reinjection

Mobile data offloading is a promising strategy to alleviate the burden on the cellular network by leveraging unused bandwidth across different wireless technologies. In this paper, we focus on hybrid offloading techniques involving both Wi-Fi and device-to-device communications. In this context, designing efficient solutions is challenging, as communication opportunities are, by nature, dependent on both individual mobility patterns and availability of the Wi-Fi infrastructure. We propose, design, and evaluate DROiD (Derivative Re-injection to Offload Data), an efficient strategy to finely control the distribution of popular content in urban scenarios. The idea is to use cellular resources as seldom as possible. To this end, DROiD injects copies using the cellular network only when needed: (i) in the beginning, when the Wi-Fi infrastructure is unable to trigger the dissemination, (ii) if the evolution of the dissemination is below some expected pace, and (iii) when the delivery delay is about to expire, in order to guarantee that all destinations receive the data. Our strategy is particularly efficient in highly dynamic scenarios, where sudden creation and dissolution of clusters of mobile nodes prevent proper content diffusion. We assess the performance of DROiD by simulating a traffic information service over two realistic large-scale vehicular datasets with several thousands of nodes. DROiD substantially outperforms other offloading strategies (opportunistic and AP-based), saving significant amount of cellular traffic even in the case of tight delivery delay constraints and energy limitations.

Enhanced Control for Adaptive Resource Reservation of Guaranteed Services in LTE Networks

Mobile innovative services are being introduced continuously to enhance people’s life through facilitating the interaction between human and the rest of the world. The world of “Internet of Things” (IoT) is expanding everyday to include more things to be connected. Considering that more and more innovative mobile services are being introduced, the long-term evolution (LTE) telecom systems/networks will be more complicated, require more resources, and demand more challenging requirements. The LTE evolved packet core (EPC) network internal design is inadequate with regard to the resources reservation techniques used to carry out the guaranteed dedicated services. In fact, EPC does not have the capabilities to utilize properly the unused bandwidth of the guaranteed bearer when the reserved bandwidth is not fully used by the mobile service, the unused guaranteed bandwidth is considered as wasted resources and consequently the whole LTE/EPC network efficiency gets affected. In this paper, we propose an adaptive technique which enhances the resource reservation for the LTE Mobile guaranteed services, our solution provides techniques to: analyze the ongoing mobile guaranteed traffic usage, provide time-series models that mathematically represent the conducted data, forecast the mobile service guaranteed resource consumption, identify the wasted/unused resources, and utilize these resources by other services. Our experiments were conducted on a dataset captured on an LTE network, the experimental results show that our approach is feasible and beneficial as it enhances the resource allocation for the LTE mobile services and increases the overall throughput of the LTE/EPC networks.

Novel adaptive virtual network embedding algorithm for Cloud’s private backbone network

In this paper, we study the adaptive virtual network embedding problem within Cloud’s backbone. The main idea is to take profit from the unused bandwidth but allocated to virtual networks. Consequently, the acceptance rate of new clients will be maximized. However, the congestion rate of virtual links must be minimized in order to maximize the satisfaction of end-users. To do so, first we formulate the problem as K-supplier optimization problem. Then, we propose a novel virtual network embedding strategy denoted by Adaptive-VNE. It is based on the approximation-algorithm for bottleneck problems and backtracking strategy. The proposal is validated by simulations and experimental testbed. The results obtained show that Adaptive-VNE outperforms the most prominent strategies and reaches a good performance.

Tracker Assisted Peer Scheduling Strategy in Multi-channel P2P VoD Streaming

Peer-to-Peer Video-on-Demand (VoD) is a capable solution which offers thousands of videos to millions of users with complete interactive watching. Most of the commercial P2P streaming deployments PPLive, PPStream, UUSee have introduced a multi-channel P2P VoD system that allows user to view more than one channel at a time. Recent research studies have proposed a cross channel resource sharing algorithms to utilize the individual peer resources effectively, including bandwidth and cache capacity by enabling crosschannel cooperation among multiple channels. However, current multiple channel P2P VoD system deliver a video at a low streaming rate due to the channel resource imbalance and channel churn. In order to improve the streaming capacity, this paper proposes different effective helpers based resource balancing scheme that actively identifies the supply-anddemand imbalance in multiple channels. Furthermore, peers in a surplus channel serve its unused bandwidth resources to peers in a deficit channel that minimizes the server bandwidth consumption. This approach proposes a tracker assisted peer scheduling policy that effectively schedules the different chunks within each video in the process of fetching and serving chunks without impairing the streaming quality. Experimental evaluation shows that the proposed tracker assisted scheduling strategy achieves high streaming capacity under reduced server workload and improves streaming quality when compared to existing algorithms.

Spectrum White Space Trade in Cognitive Radio Networks

We study price competition among primaries in a Cognitive Radio Network (CRN) with multiple primaries and secondaries located in a large region. In every slot, each primary has unused bandwidth with some probability, which may be different for different primaries. Also, there may be a random number of secondaries. A primary can lease out its unused bandwidth to a secondary in exchange for a fee. Each primary tries to attract secondaries by setting a lower price for its bandwidth than the other primaries. Radio spectrum has the distinctive feature that transmissions at neighboring locations on the same channel interfere with each other, whereas the same channel can be used at far-off locations without mutual interference. So in the above price competition scenario, each primary must jointly select a set of mutually non-interfering locations within the region (which corresponds to an independent set in the conflict graph representing the region) at which to offer bandwidth and the price at each location. In this paper, we analyze this price competition scenario as a game and seek a Nash Equilibrium (NE). For the game at a single location, we explicitly compute a NE and prove its uniqueness. Also, for the game at multiple locations, we identify a class of conflict graphs, which we refer to as mean valid graphs, such that the conflict graphs of a large number of topologies that commonly arise in practice are mean valid. We explicitly compute a NE in mean valid graphs and show that it is unique in the class of NE with symmetric independent set selection strategies of the primaries.

Bandwidth and Cache Leasing in Wireless Information Centric Networks: a Game Theoretic Study

Information-centric networking (ICN) is a novel paradigm that aims at improving the performance of today's Internet by supporting caching and multicast content delivery on every network device. The main contribution of this paper is to propose a centralized strategy to stimulate third parties to jointly lease the unused bandwidth and storage available on wireless access points (APs) in an ICN. We formulate this problem as a combinatorial reverse auction run by a content provider (CP) willing to increase the number of users reached by its service. We show that the optimal allocation with partial coverage problem is NP-hard, provide greedy heuristics that guarantee the individual rationality and truthfulness properties, and compare their performance numerically. We evaluate the benefits of our proposed mechanisms in terms of the cost savings for the CP obtained by offloading its infrastructure through the caches and the reduced computational time to execute the allocation algorithms. We compare the results obtained in this centralized setting with those that can be observed when the mobile clients autonomously choose which AP they prefer to use, among those activated by the auction mechanism. We model this second scenario as a congestion game, showing that it exhibits the desired properties (i.e., existence and uniqueness of a Nash equilibrium) and by comparing its social welfare with the centralized case.

An Adaptive DBA Scheme Using Bi-Partition Scheduling Based on Prioritized Traffics to Support Multiple Services over GPON

With the emerging broadband demand of diversified services, the gigabit-capable PON (GPON) has emerged as one of the most promising broadband access network solutions due to the increasing demand for residential bandwidth. In this paper, a novel bi-partition group based on prioritized traffics dynamic bandwidth allocation (BDBA) scheme is proposed to deliver the differentiated services over GPON. The proposed BDBA scheme divides the transmission cycle time into two groups with prioritized traffics and adjusts the bandwidth dynamically between the first group for high priorities T-CONT 1, and T-CONT 2 and the second group for low priorities T-CONT 3, and T-CONT 4. Moreover, the T-CONT 2 traffic has prediction mechanism and recycles the remaining unused bandwidth for the low priority T-CONTs. Simulation result shows that the proposed BDBA scheme can improve the system performance in terms of the throughput, blocking probability, end-to-end packet delay, jitter and fairness for 16 ONUs and 32 ONUs, and also can enhance Quality of Service (QoS) services without sacrificing the low priority traffic except before the system is half-loaded.

Design and Analytical Analysis of a Novel DBA Algorithm with Dual-Polling Tables in EPON

Ethernet passive optical network is a point-to-multipoint structure, and an effective media access protocol should be designed for collision avoidance and bandwidth allocation. Most previous researches have aimed to solve the problem using dynamic bandwidth allocation (DBA) algorithms with polling-based schemes. Unfortunately, idle channel time among the polling cycles cannot be overcome efficiently. In this paper, a dual-polling DBA (DP-DBA) algorithm which consists of an interpolling mechanism and an intrapolling mechanism is proposed. The interpolling mechanism helps eliminate the idle time problem while the intrapolling part aggregates the unused bandwidth of the light-loaded users and those due to nondefragmentation of the Ethernet frames of the general users. We also evaluate the performance of the DP-DBA algorithm by a comparison with the interleaved polling with adaptive cycle time (IPACT), the dynamic bandwidth allocation with a modified grant table generation algorithm (DBA2), the Double-Phase Polling (DPP), and the adaptive DBA algorithm with sorting report messages (Sort-DBA) schemes with simulation results. For greater realism with regard to general applications, we also simulate the asymmetric traffic loads at the optical network units (ONUs).The results show that DP-DBA outperforms the other DBA schemes under asymmetric load conditions.