Dynamic Allocation Scheme Research Articles

Dynamic Allocation Mechanism to Reduce Read Latency in Collaboration With a Device Queue in Multichannel Solid-State Devices

In this paper, we focus on read operations in flash memory, which have received less attention than write operations. To reduce read latency, we propose a read-aware dynamic allocation mechanism for multichannel solid-state devices. The proposed mechanism enables read operations to be executed immediately by reserving the resources of channels, packages, and dies dedicated to read operations. This is done in collaboration with an internal device queue, in which write operations are freely routed to their proper addresses while maintaining the merits of a dynamic allocation mechanism. Our read-aware mechanism reduces read latency by avoiding read operation conflicts when trying to access resources already occupied by preissued write operations. The experimental results show that, with our proposed mechanism, read latency decreases by up to 32.5% with an increase of write latency of up to 6.8% in real traces while providing high compatibility with existing dynamic allocation schemes.

Spectrum allocation strategy for heterogeneous wireless service based on bidding game

The spectrum scarcity crisis has resulted in a shortage of resources for many emerging wireless services, and research on dynamic spectrum management has been used to solve this problem. Game theory can allocate resources to users in an economic way through market competition. In this paper, we propose a bidding game-based spectrum allocation mechanism in cognitive radio network. In our framework, primary networks provide heterogeneous wireless service and different numbers of channels, while secondary users have diverse bandwidth demands for transmission. Considering the features of traffic and QoS demands, we design a weighted interference graph-based grouping algorithm to divide users into several groups and construct the non-interference user-set in the first step. In the second step, we propose the dynamic bidding game-based spectrum allocation strategy; we analyze both buyer’s and seller’s revenue and determine the best allocation strategy. We also prove that our mechanism can achieve balanced pricing schema in competition. Theoretical and simulation results show that our strategy provides a feasible solution to improve spectrum utilization, can maximize overall utility and guarantee users’ individual rationality.

Investor Capabilities and Dynamic Exposure to Risk

The price of sovereign bonds is currently elevated and equity valuations are far above historical averages, as unprecedented monetary expansion has caused inflation in asset prices. Long-term expected real return on a portfolio of bonds and equities is lower than in several decades, and the drawdown risk is high. This challenges the passive approach to running large long-term assets close to a rebalanced reference portfolio of bonds and equities. Changing the investment strategy to be more active in managing drawdown risk opens a Pandora’s Box of issues, some of which are addressed in this article. In particular, more active top down risk exposure decisions based on expected rewards for taking risk puts a strong demand on an investor’s capabilities. I highlight the importance of governance structure and degree of professionalism. Enhancing an investor’s capabilities to master a more dynamic allocation strategy and pursue risk factor based asset management depends partly on the ambition level of the strategy. Thus, the choice of investment strategy is endogenous to this process.

Distributed spatial modulation with dynamic frequency allocation

This paper proposes a distributed implementation of spatial modulation (SM) using cognitive radios. In distributed spatial modulation (DSM), multiple relays form a virtual antenna array and assist a source to transmit its information to a destination. The source broadcasts its signal, which is independently demodulated by all the relays. Each of the relays then divides the received data in two parts: the first part is used to decide which one of the relays will be active, and the other part decides what data it will transmit to the destination. An analytical expression for symbol error probability is derived for DSM in independent and identically distributed (i.i.d.) Rayleigh fading channels. The analytical results are later compared with Monte Carlo simulations. Further, an instantaneous symbol error rate (SER) based selection combining is proposed to incorporate the direct link between the source and destination with existing DSM. Next, DSM implementation is extended to a cognitive network scenario where the source, relays, and destination are all cognitive radios. A dynamic frequency allocation scheme is proposed to improve the performance of DSM in this scenario. The frequency allocation is modeled through a bipartite graph with end-to-end SER as a weight function. The optimal frequency allocation problem is formulated as minimum weight perfect matching problem and is solved using the Hungarian method. Finally, numerical results are provided to illustrate the efficacy of the proposed scheme.

Cost-Effective Quality Assurance in Crowd Labeling

The emergence of online paid micro-crowdsourcing platforms, such as Amazon Mechanical Turk, allows on-demand and at-scale distribution of tasks to human workers around the world. In such settings, online workers come and complete small tasks posted by employers, working for as long or as little as they wish, a process that eliminates the overhead of hiring (and dismissal). This flexibility introduces a different set of inefficiencies: verifying the quality of every submitted piece of work is an expensive operation that often requires the same level of effort as performing the task itself. A number of research challenges arise in such settings. How can we ensure that the submitted work is accurate? What allocation strategies can be employed to make the best use of the available labor force? How can we appropriately assess the performance of individual workers? In this paper, we consider labeling tasks and develop a comprehensive scheme for managing the quality of crowd labeling: First, we present several algorithms for inferring the true classes of objects and the quality of participating workers, assuming the labels are collected all at once before the inference. Next, we allow employers to adaptively decide which object to assign to the next arriving worker and propose several heuristic-based dynamic label allocation strategies to achieve the desired data quality with significantly fewer labels. Experimental results on both simulated and real data confirm the superior performance of the proposed allocation strategies over other existing policies. Finally, we introduce two novel metrics that can be used to objectively rank the performance of crowdsourced workers after fixing correctable worker errors and taking into account the costs of different classification errors. In particular, the worker value metric directly measures the monetary value contributed by each label of a worker toward meeting the quality requirements and provides a basis for the design of fair and efficient compensation schemes. The online appendix is available at https://doi.org/10.1287/isre.2016.0661 .

A Novel IEEE 802.15.4e DSME MAC for Wireless Sensor Networks.

IEEE 802.15.4e standard proposes Deterministic and Synchronous Multichannel Extension (DSME) mode for wireless sensor networks (WSNs) to support industrial, commercial and health care applications. In this paper, a new channel access scheme and beacon scheduling schemes are designed for the IEEE 802.15.4e enabled WSNs in star topology to reduce the network discovery time and energy consumption. In addition, a new dynamic guaranteed retransmission slot allocation scheme is designed for devices with the failure Guaranteed Time Slot (GTS) transmission to reduce the retransmission delay. To evaluate our schemes, analytical models are designed to analyze the performance of WSNs in terms of reliability, delay, throughput and energy consumption. Our schemes are validated with simulation and analytical results and are observed that simulation results well match with the analytical one. The evaluated results of our designed schemes can improve the reliability, throughput, delay, and energy consumptions significantly.

An efficient power saving polling scheme in the internet of energy

A global WLAN standard which utilizes country specific carrier frequencies below 1GHz has been drafted by the IEEE 802.11ah (.ah) Task Group. This draft is highly useful in rural areas due to an improved wireless propagation characteristic and a large coverage. However, the .ah draft still adopts the CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) as its media access and collision resolution protocol, which is energy-consuming and not suitable for networks where STAs (STAtions) are generally battery supplied such as meters in a SG (Smart-Grid) network, one of the typical usecases of Internet of Energy in the .ah draft. In addition, since .ah could support up to at most 6000 STAs to be scheduled within one BSS, the introduced overheads and corresponding processing delay are non-trivial and need more considerations. In this paper, a power saving scheduling scheme is proposed which could greatly reduce the introduced overhead while successfully scheduling the uplink/downlink traffics of meters in the Internet of Energy. Considering the service model and special characters of .ah networks, our model could also extend the STAs battery life with best efforts thus making our protocol specifically suitable for SG networks where battery changing for a device is usually very difficult. Further, to make our model work well, a dynamic AID allocation scheme is also presented by which the AIDs of STAs are assigned according to the average service duration thus making those scheduled STAs with similar service characteristics occupy successive AIDs. In this way, the compressed Bitmap scheme proposed in our Power Saving polling scheme for SG in the Internet of Energy (PSSG), could greatly reduce the communication overheads. Numerical results show that our scheme is better than the Power Saving Mechanism (PSM) and Power Save Multi-Poll (PSMP) protocols in terms of overheads, throughput, average awaken time and energy consumptions.

Dynamic Channel Slot Allocation Scheme and Performance Analysis of Cyclic Quorum Multichannel MAC Protocol

In high diversity node situation, multichannel MAC protocol can improve the frequency efficiency, owing to fewer collisions compared with single-channel MAC protocol. And the performance of cyclic quorum-based multichannel (CQM) MAC protocol is outstanding. Based on cyclic quorum system and channel slot allocation, it can avoid the bottleneck that others suffered from and can be easily realized with only one transceiver. To obtain the accurate performance of CQM MAC protocol, a Markov chain model, which combines the channel-hopping strategy of CQM protocol and IEEE 802.11 distributed coordination function (DCF), is proposed. The results of numerical analysis show that the optimal performance of CQM protocol can be obtained in saturation bound situation. And then we obtain the saturation bound of CQM system by bird swarm algorithm. In addition, to improve the performance of CQM protocol in unsaturation situation, a dynamic channel slot allocation of CQM (DCQM) protocol is proposed, based on wavelet neural network. Finally, the performance of CQM protocol and DCQM protocol is simulated by Qualnet platform. And the simulation results show that the analytic and simulation results match very well; the DCQM performs better in unsaturation situation.

D-ACB: Adaptive Congestion Control Algorithm for Bursty M2M Traffic in LTE Networks

When incorporating machine-to-machine (M2M) communications into the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) networks, one of the challenges is the traffic overload since many machine-type communication (MTC) devices activated in a short period of time may require access to an evolved node B (eNodeB) simultaneously. One approach to tackle this problem is by using an access class barring (ACB) mechanism with an ACB factor to defer some activated MTC devices transmitting their access requests. In this paper, we first present an analytical model to determine the expected total service time, i.e., the time used by all MTC devices to successfully access the eNodeB. In the ideal case that the eNodeB is aware of the number of backlogged MTC devices, we determine the optimal value of the ACB factor to reduce traffic overload. To better utilize the random access resources shared among human users and MTC devices in LTE networks, we propose to dynamically allocate a number of random access preambles for MTC devices. We further propose two dynamic ACB (D-ACB) algorithms for fixed and dynamic preamble allocation schemes to determine the ACB factors without a priori knowledge of the system backlog. Simulation results show that the proposed D-ACB algorithms achieve almost the same performance as the optimal performance obtained in the ideal case. The proposed D-ACB for dynamic preamble allocation algorithm can reduce both the total time to serve all MTC devices and the average number of random access opportunities required by each MTC device.

Dynamic Spectrum Allocation Scheme for Heterogeneous Network

Recently, femtocells (HeNBs) are deployed in heterogeneous network (HetNets) attributable to the addition of coverage, capacity and impeccable spectrum efficiency in private buildings/office complexes surroundings. This unplanned placement of HeNBs creates co-channel interference (CCI) in orthogonal frequency division multiple access (OFDMA). As a result service, disruption occurred at the macrocell user and femtocell user. Therefore, with always expanding interest for frequency spectrum, there is have to make available more resource allocation in order to permit more quantities of unlicensed clients to transmit their signals in the authorized groups. Cognitive-based approaches may increase the spectrum efficiency by sharing resources opportunistically from unlicensed/licensed network. However, spectrum management processes quite difficult, and a lot of chance to occur interference at the cell-edge users. Therefore, a dynamic spectrum allocation scheme is proposed for OFDMA based HetNets. The proposed scheme efficiently reduces the interferences through subchannel detection. To accomplish the CCI mitigation, the proposed scheme is functioning using the energy exposure with group creation algorithm for subchannel detection. Finally, the detected subchannel is allocated through applying power allocation algorithm. The simulation results represent that proposed scheme is able to maximize the spectrum detection and enhanced the spectral efficiency. The improved spectral efficiency recuperates the CCI situation at underlay HetNets.

A General Power Allocation Scheme to Guarantee Quality of Service in Downlink and Uplink NOMA Systems

In this paper, a novel dynamic power allocation scheme is proposed to downlink and uplink non-orthogonal multiple access (NOMA) scenarios with two users for more flexibly meeting various quality of service requirements. The exact expressions for the outage probability and the average rate achieved by the proposed scheme, as well as their high signal-to-noise ratio approximations, are established. Compared with the existing works, such as NOMA with fixed power allocation and cognitive radio inspired NOMA, the proposed scheme can: 1) strictly guarantee a performance gain over conventional orthogonal multiple access; and 2) offer more flexibility to realize different tradeoffs between the user fairness and system throughput. Monte Carlo simulation results are provided to demonstrate the accuracy of the developed analytical results and the performance gain of the proposed power allocation scheme.

System model and performance estimation of dynamic spectrum allocation strategy with multi-channel and imperfect sensing

ABSTRACTThe concept of cognitive radio networks (CRNs) is a promising candidate for enhancing the utilization of existing radio spectrum. In CRNs, secondary users (SUs) are allowed to use the spectrum unused by primary users (PUs). In order to mathematically estimate the system performance of dynamic spectrum allocation strategy with multi-channel and imperfect sensing, we propose a novel preemptive priority queueing model. We establish a discrete-time Markov chain in line with the stochastic behaviour of SU and PU packets. Then, we derive some performance measures, such as the interference rate of PU packets, the normal throughput and the average delay of SU packets. Moreover, we provide theoretical and simulation experiments to investigate the system performance. Numerical experiments show that there is a tradeoff between different performance measures when imperfect sensing is considered. Finally, we present an optimal design for setting the number of the channels in a spectrum.

GraphJet

This paper presents GraphJet, a new graph-based system for generating content recommendations at Twitter. As motivation, we trace the evolution of our formulation and approach to the graph recommendation problem, embodied in successive generations of systems. Two trends can be identified: supplementing batch with real-time processing and a broadening of the scope of recommendations from users to content. Both of these trends come together in Graph-Jet, an in-memory graph processing engine that maintains a real-time bipartite interaction graph between users and tweets. The storage engine implements a simple API, but one that is sufficiently expressive to support a range of recommendation algorithms based on random walks that we have refined over the years. Similar to Cassovary, a previous graph recommendation engine developed at Twitter, GraphJet assumes that the entire graph can be held in memory on a single server. The system organizes the interaction graph into temporally-partitioned index segments that hold adjacency lists. GraphJet is able to support rapid ingestion of edges while concurrently serving lookup queries through a combination of compact edge encoding and a dynamic memory allocation scheme that exploits power-law characteristics of the graph. Each GraphJet server ingests up to one million graph edges per second, and in steady state, computes up to 500 recommendations per second, which translates into several million edge read operations per second.

Carrier aggregation‐based dynamic spectrum access framework for LTE‐A primary operators

In this study, the authors tackle the dynamic spectrum access (DSA) problem for primary operators (POs) for long-term evolution-advanced (LTE-A) systems. They propose an auction-based DSA framework that exploits the capabilities of carrier aggregation to efficiently utilise the under-utilised spectrum which varies with time and space. Their proposed dynamic access framework defines the LTE-A resource allocation problem as a bounded knapsack auction (BKA). They solve such a BKA by converting it to a 0–1 knapsack problem that is solved using dynamic programming. Unlike prior work, they are the first to introduce an accurate model for estimating the bandwidth required to satisfy the traffic demands of an LTE-A operator’s subscribers for a projected demand model. Using extensive simulations of such a realistic network model, the results of their framework show more than 20% reduction in the required spectrum and up to 80% reduction in the average under-utilised spectrum compared with traditional static spectrum access widely adopted by spectrum regulation authorities. The reduction in the average under-utilised spectrum becomes 93.3% with 250% higher revenue compared with existing dynamic allocation strategies that are directly formulated as 0–1 knapsack auctions.

Outage Performance for Dynamic Power Allocation in Hybrid Non-Orthogonal Multiple Access Systems

In this letter, we propose a novel dynamic power allocation scheme for hybrid non-orthogonal multiple access (DH-NOMA). The exact expressions for the outage probabilities and their asymptotic approximations at high signal-to-noise ratio are derived in DH-NOMA systems. Both Monte Carlo simulations and analytical results are used to compare the proposed scheme with the existing works, such as NOMA based on fixed power allocation (F-NOMA) and cognitive radio inspired NOMA (CR-NOMA). The provided results demonstrate that the DH-NOMA scheme can always achieve better outage performance than the traditional orthogonal multiple access, and achieve a more balanced tradeoff between the two user individual rates than F-NOMA and CR-NOMA.

Timing Indicators for Structural Positions in Crude Oil Futures Contracts

This article argues that it is plausible that there are two fundamental metrics that could be useful for deciding upon crude oil futures positions: (1) whether there are ample inventories or not; and (2) whether spare capacity is at pinch-point levels or not. The article will further argue that a dynamic allocation strategy alone is not sufficient for holding the line against losses in a crude-oil-dominated strategy.

Dynamic Multi-frame Transmission Technology Using the WiMedia MAC for Multi-hop N-screen Services

N-screen is a promising technology to improve support for multimedia multicasting, content sharing, content mobility, media scalability, and seamless mobility. In this paper, the WiMedia distributed-MAC (D-MAC) protocol is adopted for development of a seamless N-screen wireless service. Furthermore, to provide a multi-hop, one source multi-use N-screen service through point to point streaming in a seamless D-MAC protocol, a dynamic multi-frame transmission technology is proposed. In this technology, a dynamic time slot allocation scheme and a multi-hop resource reservation scheme are combined. In the proposed dynamic time slot allocation scheme, two thresholds, a hard threshold and a soft threshold, are included to satisfy the power consumption and delay requirements. A multi-frame DRP reservation scheme is proposed to minimize end-to-end delay during the multi-hop transmissions between N-screen devices. The proposed dynamic multi-frame transmission scheme enhances Nscreen performance in terms of the multi-hop link establishment success rate and link establishment time compared to the conventional WiMedia D-MAC system.

Choice of Antiviral Allocation Scheme for Pandemic Influenza Depends on Strain Transmissibility, Delivery Delay and Stockpile Size.

Recently, pandemic response has involved the use of antivirals. These antivirals are often allocated to households dynamically throughout the pandemic with the aim being to retard the spread of infection. A drawback of this is that there is a delay until infection is confirmed and antivirals are delivered. Here an alternative allocation scheme is considered, where antivirals are instead preallocated to households at the start of a pandemic, thus reducing this delay. To compare these two schemes, a deterministic approximation to a novel stochastic household model is derived, which allows efficient computation of key quantities such as the expected epidemic final size, expected early growth rate, expected peak size and expected peak time of the epidemic. It is found that the theoretical best choice of allocation scheme depends on strain transmissibility, the delay in delivering antivirals under a dynamic allocation scheme and the stockpile size. A broad summary is that for realistic stockpile sizes, a dynamic allocation scheme is superior with the important exception of the epidemic final size under a severe pandemic scenario. Our results, viewed in conjunction with the practical considerations of implementing a preallocation scheme, support a focus on attempting to reduce the delay in delivering antivirals under a dynamic allocation scheme during a future pandemic.

Online Square-into-Square Packing

In 1967, Moon and Moser proved a tight bound on the critical density of squares in squares: any set of squares with a total area of at most 1/2 can be packed into a unit square, which is tight. The proof requires full knowledge of the set, as the algorithmic solution consists in sorting the objects by decreasing size, and packing them greedily into shelves. Since then, the online version of the problem has remained open; the best upper bound is still 1/2, while the currently best lower bound is 1/3, due to Han et al. (Theory Comput Syst 43(1):38---55, 2008). In this paper, we present a new lower bound of 11/32, based on a dynamic shelf allocation scheme, which may be interesting in itself. We also give results for the closely related problem in which the size of the square container is not fixed, but must be dynamically increased in order to accommodate online sequences of objects. For this variant, we establish an upper bound of 3/7 for the critical density, and a lower bound of 1/8. When aiming for accommodating an online sequence of squares, this corresponds to a $$2.82{\ldots }$$2.82ź-competitive method for minimizing the required container size, and a lower bound of $$1.33{\ldots }$$1.33ź for the achievable factor.

System level simulation platform for Cognitive LTE

The third Generation Partnership Project (3GPP) Long-Term Evolution (LTE) is becoming the first truly global wireless communication standard. LTE system is expected to have an ability to sense the wireless environment. To evaluate the performance of cognitive LTE network, the design of system level simulation platform is proposed. This platform realizes relevant spectrum sensing algorithm and dynamic spectrum allocation strategy. The architecture of this simulation platform is introduced. Based on LTE system level simulator, cognitive radio function is implemented and five modules are developed, including spectrum sensing module, spectrum allocation module, spectrum switching module, link adaptation module, link---system interface module. Class diagram of the simulation platform is also given in this paper. Simulation flow chart introduces the working mechanism in detail. Finally network performance of cognitive LTE system, including average throughput, average spectral efficiency, detection probability, false alarm probability, miss alarm probability, is evaluated using this platform.