Reduce Resource Usage Research Articles

Design and Thinning of Linear and Planar Antenna Arrays Using a Binary Teaching Learning Optimizer

In this paper, a binary variant of the teaching learning optimization technique is used to the design and thinning of linear and planar arrays. The purpose of the optimization task is to enhance the ratio directivity/sidelobe level which turns out to be having two conflicting parameters. The binary variant of the teaching learning optimization technique searches the way of exciting some selected elements. The array thinning problem requires some elements to be excited with the others having no current in them. This is a binary (ON-OFF) problem that requires an optimization technique that can handle the binary variables. The teaching learning optimization has been proposed initially to handle real valued variables. The results show good agreement between the desired and calculated radiation patterns with reduction in resource usage in terms of power consumption.

MDE-based Development of a Multispectral Camera for Precision Agriculture

Abstract: Precision Agriculture in conjunction with Variable Rate Technology aims at increasing productivity while reducing resource usage (water, fertilizers, pesticides and others). Within this context, the farm's management decisions include information from data collected about the crops health development, which need to be gathered in a timely basis. There are several means of obtaining information about the plants health, including manual data collection from sensors installed in the soil and/or its vicinity, mobile sensor systems, for example embedded sensors in UAVs, or aircrafts, or other vehicles, and satellite imagery, to name just a few examples. The adoption of UAVs in such applications has gaining a lot of attention in recent years due to ease of access, low cost and available flight control software. UAV systems may carry several sensors, which include RGB, infrared, multispectral and hyper-spectral cameras. These cameras are respectively more powerful, in terms of data quality, as well as more expensive. The current paper contribution include the platform model, design and characterization of a multispectral camera system made from two low cost, commercial of the shelf cameras that can be integrated in a small UAV. These aforementioned cameras are compatible with open source hardware, namely Raspberry Pi boards, that are used to collect, process and store information.

Framework of Resource Management using Server Consolidation to Minimize Live Migration and Load Balancing

Live Migration is one of the essential operations that require more attention to addressing its high variability problems with virtual machines. We review the existing techniques of resource management to find that there are less modeling to solve this problem. The present paper introduces a novel framework that mainly targets to achieve a computational effective resource management technique. The technique uses the stochastic approach in modelling to design a new traffic management scheme that considers multiple traffic possibilities over VMs along with its switching states. Supported by an analytical modelling approach, the proposed technique offers an efficient placement of virtual machine to the physical server, performs the computation of blocks, and explores reduced resource usage. The study outcome was found to possess potential reduction in live migration, more extent of VM mapping with physical servers, and increased level of capacity.

Resource optimised reconfigurable modular parallel pipelined stochastic approximation‐based self‐tuning regulator architecture with reduced latency

Present self-tuning regulator architectures based on recursive least-square estimation are computationally expensive and require large amount of resources and time in generating the first control signal due to computational bottlenecks imposed by the calculations involved in estimation stage, different stages of matrix multiplications and the number of intermediate variables at each iteration and precludes its use in applications that have fast required response times and those which run on embedded computing platforms with low-power or low-cost requirements with constraints on resource usage. A salient feature of this study is that a new modular parallel pipelined stochastic approximation-based self-tuning regulator architecture which reduces the time required to generate the first control signal, reduces resource usage and reduces the number of intermediate variables is proposed. Fast matrix multiplication, pipelining and high-speed arithmetic function implementations were used for improving the performance. Results of implementation demonstrate that the proposed architecture has an improvement in control signal generation time by 38% and reduction in resource usage by 41% in terms of multipliers and 44.4% in terms of adders compared with the best existing related work, opening up new possibilities for the application of online embedded self-tuning regulators.

HeteroVisor

This paper presents HeteroVisor, a heterogeneity-aware hypervisor, that exploits resource heterogeneity to enhance the elasticity of cloud systems. Introducing the notion of 'elasticity' (E) states, HeteroVisor permits applications to manage their changes in resource requirements as state transitions that implicitly move their execution among heterogeneous platform components. Masking the details of platform heterogeneity from virtual machines, the E-state abstraction allows applications to adapt their resource usage in a fine-grained manner via VM-specific 'elasticity drivers' encoding VM-desired policies. The approach is explored for the heterogeneous processor and memory subsystems evolving for modern server platforms, leading to mechanisms that can manage these heterogeneous resources dynamically and as required by the different VMs being run. HeteroVisor is implemented for the Xen hypervisor, with mechanisms that go beyond core scaling to also deal with memory resources, via the online detection of hot memory pages and transparent page migration. Evaluation on an emulated heterogeneous platform uses workload traces from real-world data, demonstrating the ability to provide high on-demand performance while also reducing resource usage for these workloads.

Resource-efficient workflow scheduling in clouds

Workflow applications in science and engineering have steadily increased in variety and scale. Coinciding with this increase has been the relentless effort to improve the performance of these applications through exploiting the abundance of resources in hyper-scale clouds and with little attention to resources efficiency. The inefficient use of resources when executing scientific workflows results from both the excessive amount of resources provisioned and the wastage from unused resources among task runs. In this paper, we address the problem of resource-efficient workflow scheduling. To this end, we present the Maximum Effective Reduction (MER) algorithm, a resource efficiency solution that optimizes the resource usage of a workflow schedule generated by any particular scheduling algorithm. MER trades the minimal makespan increase for the maximal resource usage reduction by consolidating tasks with the exploitation of resource inefficiency in the original workflow schedule. The main novelty of MER lies in its identification of “near-optimal” trade-off point between makespan increase and resource usage reduction. Finding such a point is of great practical importance and can lead to: (1) improvements in resource utilization, (2) reductions in resource provisioning, and (3) savings in energy consumption. Another significant contribution of this work is MER’s broad applicability. In essence, MER can be applied to any environments that deal with the execution of (scientific) workflows of many precedence-constrained tasks although MER best suits for the IaaS cloud model. Based on results obtained from our extensive simulations using scientific workflow traces, we demonstrate MER is capable of reducing the amount of actual resources used by 54% with an average makespan increase of less than 10%. The efficacy of MER is further verified by results (from a comprehensive set of experiments with varying makespan delay limits) that show the resource usage reduction, makespan increase and the trade-off between them for various workflow applications.

A Reconfigurable Hardware Architecture for Fractional Pixel Interpolation in High Efficiency Video Coding

We present a novel reconfigurable hardware architecture for interpolation filtering in high efficient video coding that adapts to run-time changes of the number of interpolation filter calls and thereby provides a high potential of energy efficiency. It employs a picture-based prediction scheme to estimate the number of interpolation filter calls at run-time by monitoring the group of pictures history based on video coding structure knowledge. Reconfigurable acceleration engines are developed that can adapt to different filter types. Dynamic composition of different instances of these engines enables different implementation versions with area versus throughput tradeoff. A run-time selection scheme determines the best implementation version for each picture based on the throughput requirements. Compared to state-of-the-art, our architecture reduces resource usage by 57% while supporting various throughputs and video resolutions.

Linking Process Quality and Resource Usage: An Empirical Analysis

Motivated by an increasing adoption of evidence‐based medical guidelines in the delivery of medical care, we examine whether increased adherence to such guidelines (typically referred to as higher process quality) is associated with reduced resource usage in the course of patient treatment. In this study, we develop a sample of US hospitals and use cardiac care as our context to empirically examine our questions. To measure a patient's resource usage, we use the total length of stay, which includes any additional inpatient stay necessitated by unplanned readmissions within thirty days after initial hospitalization. We find evidence that higher process quality, and more specifically its clinical (as opposed to its administrative) dimensions, are associated with a reduction in resource usage. Moreover, the standardization of care that is achieved via the implementation of medical guidelines, makes this effect more pronounced in less focused environments: higher process quality is more beneficial when the cardiac department's patient population is distributed across a wider range of medical conditions. We explore the implications of these findings for process‐oriented pay‐for‐performance programs, which tie the reimbursement of hospitals to their adherence to evidence‐based medical guidelines.

A hierarchical framework for large 3D mesh streaming on mobile systems

Large 3D meshes are emerging as the new media for various applications but are still hard to use in mobile applications, due to the limited resources of mobile systems. This paper introduces a large 3D mesh streaming framework which flexibly deals with the limited resources of mobile systems and also provides a user with interactive controls and random accessibilities. To reduce resource usage, our framework presents a uniform mesh partitioning algorithm, in which each partition of a large mesh has the same number of vertices. Our uniform partitioning is based on a k-d tree clustering and extended for out-of-core meshes. A median search with heaps in the main memory is designed for faster external sorting. Large 3D meshes are transformed into a set of partitioned and simplified meshes in the server. For interactive 3D browsing, on mobile devices, our framework presents a mobile 3D viewer which is hierarchically designed with intuitive interfaces. A user can experience rapid 3D searches with 3D previews of simplified meshes. Multi touch inputs can control zooming and the level of detail in meshes automatically. Double tap touches enable a user to randomly select a region of a large mesh, and a set of partitions for the selected region will be streamed and displayed on a mobile client. As a result, our framework enables a user to browse large 3D meshes on a mobile system interactively, while optimizing system resource usage and protecting the original data in the server.

A concurrently updatable index structure for predicted paths of moving objects

While location-aware services, both in professional and private context, are widely used today, not all the available knowledge is exploited. The predicted path moving objects follow when being guided e.g. by a smartphone, is not used, instead only the current position is taken into account. In this article, we describe how the exploitation of not only point but also route information can be used to offer a new value to the users as well as a reduction of resource usage. It allows having queries on the future position of moving objects, taking the probability of its estimation into account. An index structure to handle this kind of objects and queries is introduced. Different methods for updating objects are proposed, allowing for even less consumption of resources. A set of experiments shows the performance of our approach. This enables new services to be able to cope with a growing demand, both in quality and quantity, by using sophisticated algorithms and return real value to the user. Furthermore, the communication between server and client is optimized to avoid an overload of the mobile network.

On detection and tracking of variant phenomena clouds

Phenomena clouds are characterized by nondeterministic, dynamic variations of shapes, sizes, direction, and speed of motion along multiple axes. The phenomena detection and tracking should not be limited to some traditional applications such as oil spills and gas clouds but also be utilized to more accurately observe other types of phenomena such as walking motion of people. This wider range of applications requires more reliable, in-situ techniques that can accurately adapt to the dynamics of phenomena. Unfortunately, existing works which only focus on simple and well-defined shapes of phenomena are no longer sufficient. In this article, we present a new class of applications together with several distributed algorithms to detect and track phenomena clouds, regardless of their shapes and movement direction. We first propose a distributed algorithm for in-situ detection and tracking of phenomena clouds in a sensor space. We next provide a mathematical model to optimize the energy consumption, on which we further propose a localized algorithm to minimize the resource utilization. Our proposed approaches not only ensure low processing and networking overhead at the centralized query processor but also minimize the number of sensors which are actively involved in the detection and tracking processes. We validate our approach using both real-life smart home applications and simulation experiments, which confirm the effectiveness of our proposed algorithms. We also show that our algorithms result in significant reduction in resource usage and power consumption as compared to contemporary stream-based approaches.

On Resource Efficiency of Workflow Schedules

This paper presents the Maximum Effective Reduction (MER) algorithm, which optimizes the resource efficiency of a workflow schedule generated by any particular scheduling algorithm. The inefficiency in resource usage of workflow execution/schedule is not only in the number of resources used, but also the actual amount of “used” resource time, including idle time between any two task executions sourced from data dependencies. MER trades the minimal makespan increase for the maximal resource usage reduction by consolidating tasks with the exploitation of resource inefficiency in the original workflow schedule. Our evaluation using traces from four real-world scientific workflow applications shows that the rate of resource usage reduction far outweighs that of the increase in makespan, i.e., the number of resources used is halved on average while incurring an increase in makespan of less than 10%.

Two levels autonomic resource management in virtualized IaaS

Virtualized cloud infrastructures are very popular as they allow resource mutualization and therefore cost reduction. For cloud providers, minimizing the number of used resources is one of the main services that such environments must ensure. Cloud customers are also concerned with the minimization of used resources in the cloud since they want to reduce their invoice. Thus, resource management in the cloud should be considered by the cloud provider at the virtualization level and by the cloud customers at the application level. Many research works investigate resource management strategies in these two levels. Most of them study virtual machine consolidation (according to the virtualized infrastructure utilization rate) at the virtualized level and dynamic application sizing (according to its workload) at the application level. However, these strategies are studied separately. In this article, we show that virtual machine consolidation and dynamic application sizing are complementary. We show the efficiency of the combination of these two strategies, in reducing resource usage and keeping an application’s Quality of Service. Our demonstration is done by comparing the evaluation of three resource management strategies (implemented at the virtualization level only, at the application level only, or complementary at both levels) in a private cloud infrastructure, hosting typical JEE web applications (evaluated with the RUBiS benchmark).

Power Efficient Sum of Absolute Difference Algorithms for video Compression

Video Compression (VC) is one of the resource hungry key element in video communication and is commonly achieved using Motion Estimation (ME). In this paper we proposed power efficient one bit full adder and one of the simple and easy metric called Sum of Absolute Difference (SAD) for estimating the motion vectors in motion estimation. SAD is primarily used to detect motion in the video sub system. Here we proposed power efficient 4X4 and 8X8 SAD architectures. The proposed 4X4 SAD proves that 29%, 63.23% and 61.31% improvement in leakage power, dynamic power and total power respectively as compared with existing 4X4 SAD. Similarly the proposed 8X8 SAD which proves that 57%, 46.16% and 46.78% improvement in Leakage Power (LP), Dynamic Power (DP) and Total Power (TP) respectively as compared with that of existing 8X8 SAD at the gate level. The designs are implemented in ASIC methodology using cadence tools. Keywords - SAD, ME, VC, CSA, DSP, LP, DP, TP, FPGA etc. I. INTRODUCTION Many recent multimedia applications of digital video systems such as video conferencing, video-on- demand, video-phone, distance learning and digital TV, object tracking and many more have become popular products because of their convenience. Such applications require video compression with ever higher compression ratios, better visual quality and high bandwidth. The high efficiency video compression commonly uses the efficient hardware architectures. In general the development of hardware architectures are designed to form the integrated circuits which allows parallel processing of data from various sub blocks of the architectures, however hardware architectures suffers from limitations such as algorithm flexibility due to timing dependencies, which arises from the dataflow of various blocks of the architecture. Thus the development of good architecture of video codec in integrated circuits is very important. The customization of video codec is the video compression in the modern state of the art real time Digital Signal Processing (DSP) systems. Video compression is one of the techniques in video processing system to reduce resource usage. The two primary challenges addressed during video compression are:  Limited Network bandwidth.  Limited Storage capacity. Hence the two important metrics of a video encoder are low computational complexity & low power hardware implementation. Present day world, compression ratio plays the major role in the field of video processing. The motion in the video scene will reduce the efficiency of the compression ratio. Hence the motion estimation field has seen the highest research topic and interested issue in the past a few decades. In short the motion estimation means the estimation of the displacement (or velocity) of image structures from one frame to another in a time sequence of 2-D images of the video in order to achieve video compression in video coding. The efficiency of the compression ratio can be increased by exploiting the similarities between the video frames. The simple metric system is the SAD algorithm, where the absolute differences between the corresponding elements are added up. There are varieties of video coding standards in the video processing systems; the modern video coding standard is H.264/AVC. This coding standard uses the Variable Block Size Motion Estimation (VBSME), in this standard; the computation requirements are much higher than the previous coding standards such as H.263/ MPEG-IV. In H.264/AVC, each picture frame is divided into many macro blocks.

CZLoD

This article presents a psychophysical study that measures the perceptual thresholds of a new factor called Color-plus-Depth Level-of-Details (CZLoD) peculiar to polygon-based 3D tele-immersive video. The results demonstrate the existence of Just Noticeable Degradation and Just Unacceptable Degradation thresholds on the factor. In light of the results, we design and implement a real-time perception-based quality adaptor for 3D tele-immersive video. Our experimental results show that the adaptation scheme can reduce resource usage (e.g., CPU cycles) while considerably enhancing the overall perceived visual quality. Our analysis confirms the potential temporal and spatial performance benefits achievable with CZLoD adaptation.

Sustainable product development strategies: business planning and performance implications

Manufacturing firms are under many financial and competitive pressures that focus attention on the performance of their manufacturing processes. In this article the opportunities for improving the environmental impact of products within the constraints of existing manufacturing infrastructure are examined. Approaches that support sustainability in two aspects are proposed; first, the provision of products to the users in ways which extend the product life; and second, manufacturing approaches that reduce resource usage. This article outlines three different sustainable development strategies for different product types and describes the cost implications for manufacturers across the life cycle. The performance measures affected by these strategies are examined, drawing on product development case studies from a number of high technology sectors to highlight the different approaches taken. The results are intended to aid manufacturers during the earliest stages of business planning to consider alternative product development approaches that are more sustainable.

Information structure required for life-cycle monitoring of electronic products

Real time visibility of product-centric data has become increasingly important to original equipment manufacturers in order to optimise supply chain operations, increase quality, reduce resource usage and increase the retained value at the end-of-life of the product. The development of a system capable of supporting collection and visualisation of product-centric data that is used in life-cycle monitoring systems for electronic products is described in this article. The concepts behind intelligent products in the electronics manufacturing domain are discussed. In particular the research is focused on which product-related information is needed throughout the supply chain and how business processes can be optimised if this knowledge is available. A review of intelligent products is outlined and product information that is generated and travels with the product through the supply chain is described by analysis of business processes and identification of those processes, which could be made redundant if product-related data were available. A survey of manufacturing experts within this domain has been undertaken to determine what information should travel with the product, what opportunities exist for embedded information and what barriers for the implementation exist with regard to the specific constraints and needs in the electronics manufacturing domain. The results of this survey are discussed with conclusions drawn and future research derived and described.

Exploiting Isochrony in Self-Triggered Control

Event-triggered control and self-triggered control have been recently proposed as new implementation paradigms that reduce resource usage for control systems. In self-triggered control, the controller is augmented with the computation of the next time instant at which the feedback control law is to be recomputed. Since these execution instants are obtained as a function of the plant state, we effectively close the loop only when it is required to maintain the desired performance, thereby greatly reducing the resources required for control. In this paper we present a new technique for the computation of the execution instants by exploiting the concept of isochronous manifolds, also introduced in this paper. While our previous results showed how homogeneity can be used to compute the execution instants along some directions in the state space, the concept of isochrony allows us to compute the executions instants along every direction in the state space. Moreover, we also show in this paper how to homogenize smooth control systems thus making our results applicable to any smooth control system. The benefits of the proposed approach with respect to existing techniques are analyzed in two examples.

Effects of the per diem prospective payment system with DRG-like grouping system (DPC/PDPS) on resource usage and healthcare quality in Japan

ObjectivesIn 2003, Japan introduced the prospective payment system (PPS) with diagnosis-related groups (DRG) rearranged grouping system called the diagnostic procedure combination/per-diem payment system (DPC/PDPS). Even after eight years, little is known about the effects of DPC/PDPS. The purpose of this study was to examine the effects of DPC/PDPS on resource usage and healthcare quality. MethodsUsing 2001–2009 (fiscal year) administrative data of acute myocardial infarction patients, four indices, including inpatient total accumulated medical charges, length of stay (LOS), mortality rate, and readmission rate, were compared between patients reimbursed by DPC/PDPS or by fee-for-service. ResultsDPC/PDPS significantly reduced total accumulated medical charges by $1061 (95% confidence interval [CI], −2007, −116) and LOS by 2.29 days (95% CI, −3.71, −0.88) after risk adjustment. However, mortality rate (Odds ratio [OR], 0.94; 95% CI, 0.73, 1.21) was unchanged. Furthermore, DPC/PDPS increased the readmission rate (OR, 1.37; 95% CI, 1.03, 1.82). ConclusionsThis study showed that DPC/PDPS was associated with reduced resource usage, but not improved healthcare quality, as with DRG/PPSs in other countries. To achieve successful healthcare reform, further discussion on additional motives will be required.

Heuristic Burst Construction Algorithm for Improving Downlink Capacity in IEEE 802.16 OFDMA Systems

IEEE 802.16 OFDMA systems have gained much attention for their ability to support high transmission rates and broadband access services. For multiuser environments, IEEE 802.16 OFDMA systems require a resource allocation algorithm to use the limited downlink resource efficiently. The IEEE 802.16 standard defines that resource allocation should be performed with a rectangle region of slots, called a burst. However, the standard does not specify how to construct bursts. In this paper, we propose a heuristic burst construction algorithm, called HuB, to improve the downlink capacity in IEEE 802.16 OFDMA systems. To increase the downlink capacity, during burst constructions HuB reduces resource wastage by considering padded slots and unused slots and reduces resource usage by considering the power boosting possibility. For simple burst constructions, HuB makes a HuB-tree, in which a node represents an available downlink resource and edges of a node represent a burst rectangle region. Thus, making child nodes of a parent node is the same as constructing a burst in a given downlink resource. We analyzed the proposed algorithm and performed simulations to compare the performance of the proposed algorithm with existing algorithms. Our simulation study results show that HuB shows improved downlink capacity over existing algorithms.