Reallocation Approach Research Articles

A Data Envelopment Analysis Approach for Resource Allocation and Reallocation

A Data Envelopment Analysis Approach for Resource Allocation and Reallocation

Geometric-inspired graph-based Incomplete Multi-view Clustering

Multi-view clustering methods group data into different clusters by discovering the consensus in heterogeneous sources, which however becomes difficult when partial views of real-world data are missing. Consequently, reducing the impact of missing views and leveraging available views are the key concerns for the Incomplete Multi-view Clustering (IMvC) problem. In this research, we take an innovative, geometry-based perspective to investigate the IMvC problem under a commonly-used weight aggregation framework. We conduct a geometric analysis to understand how missing views shift the aggregation solution from the one achieved with full views, subsequently impacting the clustering result. Drawing from our analysis, we introduce a weight reallocation approach that minimizes the shift and approximates the full-view solution by reallocating the factual weight of each available view. Furthermore, we address the IMvC problem by using our reallocation method on a graph aggregation algorithm to obtain reliable clusters. Our extensive experiments demonstrate that our proposed approach outperforms previous IMvC methods, reporting superior results on four datasets with three metrics. Especially, on the Caltech101-7 dataset with 40 percent missing data, our method achieves an accuracy of 0.686, which significantly outperforms the results of other comparison methods that are no larger than 0.662. Further, our method can be used as a flexible plugin to improve other weight aggregation algorithms. The source code of this work is publicly available at https://github.com/bjlfzs/Geometric-Inspired-Graph-based-Incomplete-Multi-view-Clustering.

DYNAMIC MULTICAST SPECTRUM (RE) ALLOCATION USING SHARED BACKUP PATH IN ELASTIC OPTICAL NETWORKS

The routing and spectrum allocation (RSA) problem in elastic optical networks (EON) is to first find a path for a connection request and then allocate a frequency slot to it. Due to spectrum continuity and contiguity constraints, some available frequency slots cannot be allocated to connection requests. In this case, one solution is to reassign slot to some existing connections to accept new ones. However, most current reallocation schemes are proposed for unprotected connections. With the very high throughput of connections in EONs (Tb/s per link), the requirement for connection protection is becoming standard. In this paper, we examine a frequency slot reallocation approach for protected multicast connections. The proposed approach allows the reallocation of available and already used slots by temporarily using the protection resources. The experimental results show an average blocking probability of 10% lower than reallocation with hoptuning and the conventional MC-RSA algorithm.

Dynamic ID randomization for user privacy in mobile network

Mobile and telecommunication networking uses temporary and random identifiers (IDs) to protect user privacy. For greater intelligence and security o the communications between the core network and the mobile user, we design and build a dynamic randomization scheme for the temporary IDs for mobile networking, including 5G and 6G. Our work for ID randomization (ID-RZ) advances the existing state-of-the-art ID re-allocation approach in 5G in the following ways. First, ID-RZ for ID updates is based on computing, as opposed to incurring networking for the re-allocation-based updates, and is designed for lightweight and low-latency mobile systems. Second, ID-RZ changes IDs proactively (as opposed to updating based on explicit networking event triggers) and provides stronger security (by increasing the randomness and frequency of ID updates). We build on the standard cryptographic primitives for security (e.g., hash) and implement our dynamic randomization scheme in the 5G networking protocol to validate its design purposes, which include time efficiency (two to four orders of magnitude quicker than the re-allocation approach) and appropriateness for mobile applications.

PPOM: An Effective Post-Global Placement Optimization Methodology for Better Wirelength and Routability

Even though routability is of great concern to a recent global placement algorithm, there still exists a large room to improve it. To make legalization more easier and get a better placement, this article proposes an iterative approach to refine cell locations after global placement, where wirelength and routability are separately optimized in each iteration. It first moves cells to better locations to reduce wirelength. Unlike previous approaches, our approach guarantees that no wirelength will be increased so that the previous optimization result can be better maintained. Moreover, we propose a delicate procedure to move cells according to their gain values to reduce the largest wirelength. Next, the whitespace re-allocation approach is applied to redistribute whitespace over a chip to improve routability without changing relative locations of cells. To ensure that enough space will be allocated to the most routing congestion regions, we propose a sigmoid function to increase routing demands of regions according to their routing overflows and number of pins. The experimental results show that our methodology can obtain shorter wirelength and better routability in industrial designs when compared to other approach.

Optimal bandwidth allocation for web crawler systems with time constraints

Web crawler is an important tool to obtain information from the Internet in a timely manner. In a typical web crawler system with limited bandwidth, many websites are crawled with different time constraints. Existing studies regarding web crawler systems do not consider the bandwidth allocation in such a complex environment; hence, the time constraints may not be satisfied. In this study, we investigate the bandwidth allocation approaches for such a web crawler system. The approaches are designed for two scenarios, i.e., when the number of websites exceeds or does not exceed the maximum number of web crawlers that the system can execute simultaneously. For the latter situation, we propose approaches to control the bandwidth for web crawlers to minimize the maximum complete time or minimize the sum of execution times of all web crawlers, considering assumptions of both sufficient and insufficient bandwidths. For the former situation, we propose a round-based reallocation approach to schedule both the sequence and bandwidth allocation of the web crawlers. Extensive simulations are conducted to validate the proposed approaches, and the results show that our approaches satisfy the time constraints well and achieve desirable execution performances in various scenarios.

Better resource utilization: A new DEA bi-objective resource reallocation approach considering environmental efficiency improvement

This study addresses the resource reallocation problem by proposing a data envelopment analysis (DEA) bi-objective approach that considers the environmental efficiency improvement of organizations (i.e., decision making units, DMUs). First, we introduce environmental efficiency evaluation models with and without the consideration of resource reallocation. Second, we prove that all the DMUs can be environmentally efficient after resource reallocation using a common-weight evaluation mechanism and build the resource reallocation possibility set. Third, a bi-objective resource reallocation model is proposed which considers both output target realizability and the match between the new reallocated resource of a DMU and the DMU’s pre-performance and operation size. Further, a trade-off model is adopted to solve the bi-objective model to obtain the final resource reallocation result. The proposed approach guarantees that all the DMUs are environmentally efficient after resource reallocation while maintaining the non-resource inputs at their current levels. It also contributes by considering both the DMUs’ ability of achieving the output targets and each DMU’s pre-performance which is an important indicator that reflects each DMU’s ability to transform input resources into output products. Finally, the proposed approach is applied for a case study of Chinese regional land transportation systems based on data of the year 2016.

A Reallocation Approach for Software Trustworthiness Based on Trustworthy Attributes

Software trustworthiness is an important research field in software engineering. In order to appropriately evaluate it, some different measurement approaches have been proposed, which have important guiding significance for improving software trustworthiness. Recently, we have investigated attributes-based approaches. That is, how to maximize trustworthy degree of some software satisfying a given threshold by adjusting every attribute value such that the cost is minimal, i.e., the sum of all attribute values is as small as possible. The work is helpful to improve the software quality under the same cost. This paper continues this work and considers a reallocation approach to dealing with the problem that the threshold and the minimal constraints of every attribute values dynamically increase. In this process, the costs of trustworthiness improvement should be ensured to be minimal. For this purpose, we firstly define a reallocation model by mathematical programming. Then we introduce the notion of growth function. Based on this, a polynomial reallocation algorithm is designed to solve the above reallocation model. Finally, we verify our work on spacecraft softwares and the results show that this work is valid.

Towards Responsible Consolidation of Customary Lands: A Research Synthesis

The use of land consolidation on customary lands has been limited, though land fragmentation persists. Land fragmentation on customary lands has two main causes—the nature of the customary land tenure system, and the somewhat linked agricultural system. Since attempts to increase food productivity on customary lands have involved fertilisation and mechanisation on the small and scattered farmlands, these approaches have fallen short of increasing food productivity. A study to develop a responsible approach to land consolidation on customary lands using a design research approach is undertaken and reported here. Based on a comparative study, it is found that three factors inhibit the development of a responsible land consolidation approach on customary lands—the coverage of a land administration system, a land valuation approach, and a land reallocation approach the fits the customary land tenure system. To fill these gaps, firstly, this study developed the participatory land administration that brought together traditional land administration approaches with emerging bottom-up approaches, as well as technological advances that drive these approaches together with the growing societal needs. Secondly, a valuation approach was developed to enable the comparison of the farmlands in rural areas that are without land markets. Finally, a land reallocation approach was developed based on the political, economic and social, as well as technical and legal characteristics of rural customary farmlands. This study concludes that though the land consolidation strategy developed is significantly able to reduce land fragmentation, both physical and land tenure, the local customs are an obstruction to the technical processes to achieve the best form of farmland structures.

Responsible consolidation of customary lands: A framework for land reallocation

Land reallocation is an important step of land consolidation where farmland parcels are reorganised and redistributed. Most current land reallocation approaches focus on the technical aspects, at the expense of the social, cultural, economic, and political factors which are important on customary lands. This paper develops an approach for land reallocation to support responsible land consolidation on customary lands taking these factors into consideration. Using the process model approach, we identify the key characteristics of customary land tenure and the general requirements for land reallocation of these lands; from which a land re-allocation approach is developed. This is subsequently applied to a case study in Northern Ghana. The results show that even though the approach is successful to the extent that land fragmentation (physical and legal) is significantly reduced in the study area; social land mobility, land tenure and cultural practices hinder the application of the land reallocation as this would either increase legal or physical land fragmentation.

Towards Bandwidth Guaranteed Virtual Cluster Reallocation in the Cloud

Cloud data center traffic is experiencing a rapid growth as more and more data-intensive applications are required to process big data in a cloud data center. Although fat-tree networks own rich path multiplicity, and have been widely adopted as network topologies in cloud data center networks to transmit vast bisection bandwidth, they lead to bandwidth-related bottlenecks. To address this issue, in this paper, we propose a traffic-aware virtual cluster reallocation approach via biogeography-based optimization to allocate some reallocated virtual machines (VMs) as compact as possible with those VMs in the same virtual clusters. In order to validate our approach, we build a system model to perform a thorough evaluation of its performance. Experimental results show that our proposed approach outperforms six existed approaches in term of total transmission cost, total processing time, and total network resource consumption.

Near and Far Field Speech-in-Noise Intelligibility Improvements Based on a Time–Frequency Energy Reallocation Approach

An algorithm designed to enhance the intelligibility of speech signals before they are presented in noisy environments was evaluated. The processed and unprocessed speech had the same root-mean square level. Spectral energy was redistributed to increase the signal-to-noise ratio (SNR) in the mid- and high-frequency bands, while the softer segments of speech were increased in level by applying time-domain dynamic range compression. Noise level adaptation was introduced to increase the subjective quality of signals at high SNRs. Evaluations were conducted both in near field (headphones) and in far field (outdoor) conditions using listeners with normal hearing and two types of background. The results showed: (a) In the near field test, the proposed algorithm yielded significant intelligibility improvements relative to the unprocessed speech for both stationary and nonstationary backgrounds; (b) In the far field test, the proposed algorithm increased the intelligibility of unprocessed speech by a factor of seven at 200-m distance from the sound source; and (c) When the background level did not alter intelligibility, listeners preferred the quality of the speech processed by the noise-dependent version of the algorithm.

Distributed filtering algorithm based on tunable weights under untrustworthy dynamics

Aiming at effective fusion of a system state estimate of sensor network under attack in an untrustworthy environment, distributed filtering algorithm based on tunable weights is proposed. Considering node location and node influence over the network topology, a distributed filtering algorithm is developed to evaluate the certainty degree firstly. Using the weight reallocation approach, the weights of the attacked nodes are assigned to other intact nodes to update the certainty degree, and then the weight composed by the certainty degree is used to optimize the consensus protocol to update the node estimates. The proposed algorithm not only improves accuracy of the distributed filtering, but also enhances consistency of the node estimates. Simulation results demonstrate the effectiveness of the proposed algorithm.

Resilience management problem in ATM systems as a shortest path problem

As a preliminary study about the methodology for resilience management in ATM systems, this paper identifies the key aspects that should be taken into account in the formal definition of the problem. It provides an overview of the definitions and concepts related to resilience in ATM systems. Finally, the paper introduces a proposal for a definition of a resilience metric for an ATM system and formally states the resilience management problem as an optimization problem. The latter aims at finding an optimal scheduling strategy for the re-allocation of system tasks. The paper also inspects the nature of the proposed metric, highlights the constraints of the problem and makes a comparison with other approaches. A specific Case Study is discussed in detail in the paper, which allows to demonstrate the applicability of the proposed methodology. Results discussed in the paper can foster the studies on the resilience of the ATM system through a task re-allocation approach.

Multiple testing procedures for adaptive enrichment designs: combining group sequential and reallocation approaches.

Adaptive enrichment designs involve preplanned rules for modifying enrollment criteria based on accrued data in an ongoing trial. For example, enrollment of a subpopulation where there is sufficient evidence of treatment efficacy, futility, or harm could be stopped, while enrollment for the remaining subpopulations is continued. We propose a new class of multiple testing procedures tailored to adaptive enrichment designs. The procedures synthesize ideas from two general approaches. As in the modified group sequential approach, the procedures gain power by leveraging the covariance among statistics for different stages and different hypotheses. As in the alpha reallocation approach, the procedures lower rejection thresholds for the remaining null hypotheses after others have been rejected. The proposed procedures are proved to have power greater than or equal to several existing methods, and to strongly control the familywise Type I error rate when statistics are normally distributed. The methods are illustrated through simulations of a trial for a surgical intervention for stroke, involving two subpopulations.

Waste load reallocation in river–reservoir systems: simulation–optimization approach

Temporal changes in system’s topology and/or socioeconomic criteria may force the authorities to enforce waste load reallocation strategies to sustain water quality standards in a receiving body. This paper proposes a simulation–optimization model to tackle the challenging waste load reallocation in a river–reservoir system. This study links a 2-dimensional process-based water quality simulation model and a surrogate data-driven model with an efficient optimization algorithm to structure a systematic approach and methodology for reallocation of waste loads in a river–reservoir system. Long response time of the reservoir is accounted for by the continuous and long-term simulation of the system for identification of the vulnerable conditions and their consequences. The proposed methodology is particularly suitable for high-dimensional river–reservoir operation optimization with water quality–quantity objectives. To reduce the computational burden, we substitute the simulation model with a surrogate model in an online-dynamically refined routine. The optimum waste load reallocation strategies, for prior and after dam construction, are compared, and their impacts on waste allocation are discussed.

A DEA-based approach for fair reduction and reallocation of emission permits

How to allocate initial emission permits is vital for the cap-and-trade system in controlling the total emission level and improving the operation efficiency of the trade mechanism. And data envelopment analysis (DEA) has been proved to be more suitable to fairly resolve the problem as a performance-based allocation is involved here. In this paper, we present a novel DEA approach for fair reduction and reallocation of emission permits for areas under administration. The presented DEA models are based on the ideas, where, according to their eco-efficiency and current emission levels, all decision making units (DMUs) compete with each other for the least reduction amount by introducing a bargaining game, on the other hand, the central authority can improve the overall efficiency by reallocating the remaining emission permits. The approach is applied on the dataset of agricultural greenhouse gas emissions from 15 European Union members (EU15). The results of the application show that the reduction and reallocation mechanism is fair, which benefits the countries that work at the optimal scale operation while punishes those that fail to operate on the optimal scale. Furthermore, it is effective in improving the overall efficiency of the system.

Light reallocation for high contrast projection using an analog micromirror array

We demonstrate for the first time a proof of concept projector with a secondary array of individually controllable, analog micromirrors added to improve the contrast and peak brightness of conventional projectors. The micromirrors reallocate the light of the projector lamp from the dark parts towards the light parts of the image, before it reaches the primary image modulator. Each element of the analog micromirror array can be tipped/tilted to divert portions of the light from the lamp in two dimensions. By directing these mirrors on an image-dependent basis, we can increase both the peak intensity of the projected image as well as its contrast. In this paper, we describe and analyze the optical design for projectors using this light reallocation approach. We also discuss software algorithms to compute the best light reallocation pattern for a given input image, using the constraints of real hardware. We perform extensive simulations of this process to evaluate image quality and performance characteristics of this process. Finally, we present a first proof-of-concept implementation of this approach using a prototype analog micromirror device.

A load-balancing spare capacity reallocation approach in the next-generation SONET metro networks

The next-generation SONET metro network is evolving into a service-rich infrastructure. At the edge of such a network, multiservice provisioning platforms (MSPPs) provide efficient data mapping enabled by Generic Framing Procedure (GFP) and Virtual Concatenation (VC). The core of the network tends to be a meshed architecture equipped with Multi-service Switches (MSSs). In the context of these emerging technologies, we propose a load-balancing spare capacity reallocation approach to improve network utilization in the next-generation SONET metro networks. Using our approach, carriers can postpone network upgrades, resulting in increased revenue with reduced capital expenditures (CAPEX). For the first time, we consider the spare capacity reallocation problem from a capacity upgrade and network planning perspective. Our approach can operate in the context of shared-path protection (with backup multiplexing) because it reallocates spare capacity without disrupting working services. Unlike previous spare capacity reallocation approaches which aim at minimizing total spare capacity, our load-balancing approach minimizes the network load vector (NLV), which is a novel metric that reflects the network load distribution. Because NLV takes into consideration both uniform and non-uniform link capacity distribution, our approach can benefit both uniform and non-uniform networks. We develop a greedy load-balancing spare capacity reallocation (GLB-SCR) heuristic algorithm to implement this approach. Our experimental results show that GLB-SCR outperforms a previously proposed algorithm (SSR) in terms of established connection capacity and total network capacity in both uniform and non-uniform networks.

Refining fire emissions for air quality modeling with remotely sensed fire counts: A wildfire case study

This paper examines the use of Moderate Resolution Imaging Spectroradiometer (MODIS) observed active fire data (pixel counts) to refine the National Emissions Inventory (NEI) fire emission estimates for major wildfire events. This study was motivated by the extremely limited information available for many years of the United States Environmental Protection Agency (US EPA) NEI about the specific location and timing of major fire events. The MODIS fire data provide twice-daily snapshots of the locations and breadth of fires, which can be helpful for identifying major wildfires that typically persist for a minimum of several days. A major wildfire in Mallory Swamp, FL, is used here as a case study to test a reallocation approach for temporally and spatially distributing the state-level fire emissions based on the MODIS fire data. Community Multiscale Air Quality (CMAQ) model simulations using these reallocated emissions are then compared with another simulation based on the original NEI fire emissions. We compare total carbon (TC) predictions from these CMAQ simulations against observations from the Inter-agency Monitoring of Protected Visual Environments (IMPROVE) surface network. Comparisons at three IMPROVE sites demonstrate substantial improvements in the temporal variability and overall correlation for TC predictions when the MODIS fire data is used to refine the fire emission estimates. These results suggest that if limited information is available about the spatial and temporal extent of a major wildfire fire, remotely sensed fire data can be a useful surrogate for developing the fire emissions estimates for air quality modeling purposes.