Unmanned aerial vehicle (UAV) systems have gained widespread recognition due to their versatility and autonomy. Their deployment for disaster mitigation and management operations is seen as one of their most important...
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Unmanned aerial vehicle (UAV) systems have gained widespread recognition due to their versatility and autonomy. Their deployment for disaster mitigation and management operations is seen as one of their most important applications over the past decade. In such UAV networks, routing plays a crucial role in determining network performance parameters such as network lifetime, data transmission latency, and packet delivery ratio. This paper presents a novel routing mechanism - Multi-Objective Markov Decision Based Routing (MOBMDP) for UAV networks carrying out search-based operations. MOBMDP models routing decisions in a Markov Decision Process (MDP) framework and uses Q-learning to take decisions. It compares routing paths using three metrics, viz., Remaining Energy of the Minimum Energy Node (REMEN), Power Distance ratio (PD), and Expected Delay (ED). Amongst these metrics, PD is a novel metric proposed by this work. PD simultaneously optimizes the energy efficiency and energy distribution in the network. Further, MOBMDP uses a novel reinforcement learning inspired method to estimate transmission delay in a given path. Intensive simulation studies compare MOBMDP to four state-of-the-art routing protocols. Results show a significant improvement in network lifetime, packet delivery ratio, energy efficiency, average data transmission delay, and error in delay estimation.
The dynamic landscape of cloud computing design presents significant challenges regarding power consumption and quality of service (QoS). Virtual machine (VM) consolidation is essential for reducing power usage and en...
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The dynamic landscape of cloud computing design presents significant challenges regarding power consumption and quality of service (QoS). Virtual machine (VM) consolidation is essential for reducing power usage and enhancing QoS by relocating VMs between hosts. OpenStack Neat, a leading framework for VM consolidation, employs the Modified Best-Fit Decreasing (MBFD) VM placement technique, which faces issues related to energy consumption and QoS. To address these issues, we propose an Energy Efficient VM Consolidation (EEVMC) approach. Our method introduces a novel host selection criterion based on the incurred loss during VM placement to identify the most efficient host. For validation, we conducted simulations using real-time workload traces from Planet-Lab and Materna over ten days, leveraging the latest CloudSim toolkit to compare our approach with state-of-the-art techniques. For Planet-Lab's workload, our EEVMC approach shows a reduction in energy consumption by 80.35%, 59.76%, 21.59%, and 7.40%, and fewer system-level agreement (SLA) violations by 94.51%, 94.85%, 47.17%, and 17.78% when compared to Modified Best-Fit Decreasing (MBFD), Power-Aware Best Fit Decreasing (PABFD), Medium Fit Power Efficient Decreasing (MFPED), and Power-Efficient Best-Fit Decreasing (PEBFD), respectively. Similarly, for Materna, EEVMC achieves a reduction in energy consumption by 16.10%, 61.0%, 4.94%, and 4.82%, and fewer SLA violations by 76.99%, 88.88%, 12.50%, and 48.65% against the same benchmarks. Additionally, Loss-Aware Performance Efficient Decreasing (LAPED) significantly reduces the total number of VM migrations and SLA time per active host, indicating a substantial improvement in cloud computing efficiency.
This study developed an algorithm, TerrorClassify, which places terror organizations into hierarchical categories of casualties and consequences. A previous study proposed a method of categorizing terrorists into four...
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This study developed an algorithm, TerrorClassify, which places terror organizations into hierarchical categories of casualties and consequences. A previous study proposed a method of categorizing terrorists into four classes based on the extent of havoc caused by individual terror groups. The classes include low-casualty, medium-consequence terror groups;medium-casualty, high-consequence terror groups;high-casualty, low-consequence terror groups;and higher-casualty, low-consequence terror groups. In this research, an algorithm was designed to show the procedures to be followed in placing terror groups into the four classes using the records in the global terrorism database. The algorithm can be implemented with any programming language.
Methods that make it possible to choose optimal layout solutions for technological complexes are considered. As a result of the analysis, we have established a method for compiling layout diagrams for technological co...
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Methods that make it possible to choose optimal layout solutions for technological complexes are considered. As a result of the analysis, we have established a method for compiling layout diagrams for technological complexes of mechanical assembly production based on minimization of the total annual traffic flow. A block diagram of this department placement algorithm is given based on the chosen method. The proposed method has been implemented based on the example of choice of the optimal layout diagram of the technological complex of mechanical assembly production using the developed program.
The high density of temporary hotspots will result in a significant reduction in data rates per user. In addition, when base stations are no longer functional in the disaster area, it is necessary to develop wireless ...
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ISBN:
(纸本)9781665401203
The high density of temporary hotspots will result in a significant reduction in data rates per user. In addition, when base stations are no longer functional in the disaster area, it is necessary to develop wireless infrastructure as soon as possible. To address this situation, we focus on UAVs (Unmanned Aerial Vehicles) equipped with wireless communication infrastructure to provide services. Building a wireless network with mobility, UAVs can provide high data rates for ever-changing user distribution. In this paper, for dynamic user distributions, which have not been considered much so far, we identify issues due to differences from static user distributions and propose methods to solve them. This paper reports on the study of UAV placement method from the viewpoint of data rate and power consumption.
This paper introduces hybrid iterative algorithms that combine Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms for Field Programmable Gate Array (FPGA) placement by considering adaptive inert...
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This paper introduces hybrid iterative algorithms that combine Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms for Field Programmable Gate Array (FPGA) placement by considering adaptive inertia weight and local minima avoidance. The algorithms target to optimize the wire-length of the nets, run time and critical path delay in the placement of logic blocks. Using the adaptive inertia weight parameter and local minima avoidance, the hybrid PSO-SA algorithm is modified to Time-varying PSO-SA (TPSO-SA) and Modified PSO-SA (MPSO-SA) algorithm, respectively. These different hybrid PSO-SA algorithms are checked for efficiency by comparing with the Versatile Place and Route (VPR) algorithm of the Verilog to Routing (VTR) tool using Microelectronics Centre of North Carolina (MCNC) benchmark circuits. The hybrid PSO-SA algorithms give 537% better results for wire-length cost and 2058% reduction in runtime compared to the VPR placement algorithm on different benchmark circuits. Critical path delay is also taken into consideration.
Three-Dimensional (3D) FPGA as a promising design trend, achieves significant performance improvement over conventional 2D-based FPGA. The maturity of the uni-directional routing architecture design, which achieves 25...
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ISBN:
(纸本)9781479921980;9781479921997
Three-Dimensional (3D) FPGA as a promising design trend, achieves significant performance improvement over conventional 2D-based FPGA. The maturity of the uni-directional routing architecture design, which achieves 25% area saving in area-delay-product (ADP) over bi-directional routing architectures, has driven major vendors such as Xilinx and Altera to switch to such architecture in their 2D-based products. However, few studies were contributed to exploring performance-optimal uni-directional 3D routing architectures. In this paper, we propose and evaluate a novel uni-directional 3D routing architecture named UNI-3D. Additionally, in the EDA counterpart, we also propose an improved simulated annealing (SA)-based placement algorithm that caters the unidirectional architecture, to alleviate signal propagation imbalance in the vertical channels resulted from using conventional bi-directional based SA approach. Our simulation results show that our proposed architecture is able to achieve up to 28.44% of delay reduction and 26.21% planar channel width reduction compared with the baseline 2D uni-directional architecture. At the same time, the proposed SA algorithm is able to improve the average vertical channel width up to 16% compared to state-of-the-art works.
Hardware-accelerators in Network Function Virtualization (NFV) environments have aided telecommunications companies (telcos) to reduce their expenditures by offloading compute-intensive VNFs to hardware-accelerators. ...
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ISBN:
(纸本)9781728163000
Hardware-accelerators in Network Function Virtualization (NFV) environments have aided telecommunications companies (telcos) to reduce their expenditures by offloading compute-intensive VNFs to hardware-accelerators. To fully utilize the benefits of hardware-accelerators, VNF-chain recovery models need to be adapted. In this paper, we present an ILP model for optimizing prioritized recovery of VNF-chains in heterogeneous NFV environments following node failures. We also propose an accelerator-aware heuristic for solving prioritized VNF-chain recovery problems of large-size in a reasonable time. Evaluation results show that the performance of heuristic matches with that of ILP in regard to restoration of high and medium priority VNFchains and a small penalty occurs only for low-priority VNF-chains.
DevOps (software DEVelopment and information technology OPerationS) has established a culture and environment, in which building, testing, and releasing software happen more rapidly, frequently, and reliably through a...
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ISBN:
(纸本)9781728127057
DevOps (software DEVelopment and information technology OPerationS) has established a culture and environment, in which building, testing, and releasing software happen more rapidly, frequently, and reliably through automated pipelines. To support this high turnover application cycle, the cluster orchestration frameworks such as Kubernetes or Docker Swarm have evolved to provide high flexibility and reliability. However, while cluster orchestrators run on the cloud infrastructure, any failure incurred from the infrastructure can directly impact the nodes of a cluster, so infrastructure failures can disrupt applications running on the cluster. In this paper, we propose proactive application placement algorithms with prediction of infrastructure failures. The proposed algorithms utilize failure-risk measurements, Failure-Index, determined from turnover rate of applications and prediction of infrastructure failures. We build stochastic models for application turnover and infrastructure failure processes, and provide various types of Failure-Index. Our placement algorithms are implemented in an orchestration framework, Kubernetes, and in the simulation model. Experimental results show that our methods reduce the amount of application disruption by 20% than the state-of-the-art algorithms in Kubernetes.
Network Function Virtualization aims to migrate packet-processing tasks from special-purpose appliances to Virtual Network Functions (VNFs) running on x86 or ARM servers. However, achieving the line-rate packet-proces...
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ISBN:
(纸本)9781728145457
Network Function Virtualization aims to migrate packet-processing tasks from special-purpose appliances to Virtual Network Functions (VNFs) running on x86 or ARM servers. However, achieving the line-rate packet-processing for VNFs running on CPUs can be a challenging task. External hardware accelerators can be used to offload heavy-lifting tasks (e.g. en/decryption and hashing) from performance-critical VNFs. State-of-the-art VNF placement algorithms only consider compute resources while assigning VNFs on server nodes. We propose a placement algorithm which takes into consideration hardware accelerator resources in addition to compute resources. For evaluation, we compare the performance of our approach with the Integer Linear Program (ILP) method and also with the state-of-the-art best-fit method of VNF placement.
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