Multi-tier System Research Articles

QM-ARC: QoS-aware Multi-tier Adaptive Cache Replacement Strategy

Distributed data-centric systems, such as Named Data Networking, utilize in-network caching to reduce application latency by buffering relevant data in high-speed memory. However, the significant increase in data traffic makes expanding memory capacity prohibitively expensive. To address this challenge, integrating technologies like non-volatile memory and high-speed solid-state drives with dynamic random-access memory can form a cost-effective multi-tier cache system. Additionally, most existing caching policies focus on categorizing data based on recency and frequency, overlooking the varying Quality-of-Service (QoS) requirements of applications and customers—a concept supported by Service Level Agreements in various service delivery models, particularly in Cloud computing. One of the most prominent algorithms in caching policy literature is the Adaptive Replacement Cache (ARC), that uses recency and frequency lists but does not account for QoS. In this paper, we propose a QoS-aware Multi-tier Adaptive Replacement Cache (QM-ARC) policy. QM-ARC extends ARC by incorporating QoS-based priorities between data applications and customers using a penalty concept borrowed from service-level management practices. QM-ARC is generic, applicable to any number of cache tiers, and can accommodate various penalty functions. Furthermore, we introduce a complementary feature for QM-ARC that employs Q-learning to dynamically adjust the sizes of the two ARC lists. Our solution, evaluated using both synthetic and real-world traces, demonstrates significant improvements in QoS compared to state-of-the-art methods by better considering priority levels. Results show that QM-ARC reduces penalties by up to 45% and increases the hit rate for high priority data by up to 84%, without negatively impacting the overall hit rate, which also increases by up to 61%.

Community Detection-Empowered Self-Adaptive Network Slicing in Multi-Tier Edge-Cloud System

Community Detection-Empowered Self-Adaptive Network Slicing in Multi-Tier Edge-Cloud System

Mitigating triple-marginalization in a multi-tier product tracking system: blockchain application and real-data validation

ABSTRACT Most of product waste is due to label problems and handling errors, some retailers try to use blockchain-based system to tackle food waste. However, blockchain adoption requires the participation of all supply chain members (e.g. suppliers and logistics service providers) while their incentives remain unclear. Considering a multi-tier system comprising a supplier, a retailer and a logistic service provider, we solve a multi-stage optimisation problem when the products stored in advance are subject to shelf-life due date risk while the real-time order is subject to upstream responsive pricing threat. We evaluate the effectiveness of product tracking system based on blockchain applications. Both real-data validation and game theoretic analysis reveal the stakeholder’s participation incentive conflicts and the dark side of triple-marginalization. However, a sequential co-opetition mechanism is capable of coordinating the stakeholders’ preferences for the product tracking system. We further find that saving waste and balancing the advanced and real-time orders do not necessarily indicate improvement of environmental sustainability. We suggest that: Retailers should carefully judge the product tracking system because of the potential lose-lose situation for profitability and sustainability. But once retailers can profit from blockchain adoption, suppliers are likely to profit from joining the blockchain.

Validation of the Youth Internalizing Problem Screener in Singapore

The use of a screening tool for school-wide screening of internalizing symptoms is an important strategy for early identification and prevention of more serious and impairing emotional and behavioral health problems in adolescents. However, threshold cut-off scores determined for screening tools may not be suitable for all populations. Using a sample of 237 Singaporean secondary school students, this study validated the Youth Internalizing Problems Screener (YIPS) for local use. Results of confirmatory factor analyses supported a one-factor solution for the construct. A threshold cut-off score of 27 was found to show good classification accuracy based on receiver operating characteristics (ROC) analyses. Correlational and path analyses provided evidence of convergent and predictive validity for using YIPS to indicate at-risk status. The YIPS status was uniquely associated with girls’ sense of school well-being over and above the nature of their interpersonal relationships and their sense of inadequacy. Overall, YIPS demonstrated comparable sensitivity and specificity rates even though a different cut-off score was used for this study sample. The use of YIPS as a screening tool in a multitier system of support and directions for future development were discussed.

A systematic review of factors influencing self-governed public open spaces: insights from social-ecological system framework and collective action

PurposeDue to the influence of complex and intersecting factors, self-governed public open spaces (POSs) (managed by local communities) are subject to collective action dilemmas such as tragedy of the commons (overexploitation), free-riding, underinvestment and mismanagement. This review paper adopts a multi-dimensional and multi-tier social-ecological system (SES) framework proposed by McGinnis and Ostrom, drawing on collective action theory to explore the key institutional-social-ecological factors that impact POS self-governance.Design/methodology/approachIn this paper, Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was utilized to systematically screen and review the relevant literature for the period from 2000 to 2023 in three databases: Web of Science, Scopus and Google Scholar. A total of 57 papers were chosen for in-depth analysis.FindingsThe literature review identified and categorized several variables associated with the self-organizing system of POS; consequently, an SES-based POS management framework was developed for the first time, consisting of 114 institutional-social-ecological sub-variables from different dimensions and three levels. Compared to ecological factors, among others, governance organizations, property-rights systems, socioeconomic attributes and actors' knowledge of SES have been commonly and primarily studied.Research limitations/implicationsThere is still room for the refinement of the conceptual SES-based POS collective action framework over the time (by adding in new factors), and indefinitely empirical research validating those identified factors is also worth to be undertaken, particularly testing how SES factors and interaction variables affect the POS quality (collective action).Originality/valueThe findings of this study can provide local policy insights and POS management strategies based on the identification of specific SES factors for relevant managers. Moreover, this research makes significant theoretical contributions to the integration of the SES framework and collective action theory with POS governance studies.

Urban-Rural Health Insurance Integration and China's Rural Household Savings.

A linchpin to realizing the internal circulation (referring to the domestic cycle of production, distribution and consumption) is reducing residents' saving rate and expanding the domestic needs. However, rural residents in China demonstrate a strong propensity to save money. In light of practical characteristics of urban-rural health integration promoted in different places, the three-phase data (from 2014 to 2018) and the dual difference-in-differences model of the China Labor-force Dynamics Survey (CLDS) are used to empirically investigate the impact of urban-rural health insurance integration on rural household savings. Research reveals that urban-rural health integration can reduce the health risks and medical risks facing rural households, thus weakening the motivation of precautionary savings. The analysis of heterogeneity reveals that the integration of urban-rural health insurance significantly influences the savings rates of households headed by older individuals, particularly women, with lower levels of educational attainment. Besides, the single-tier health insurance system can have a more significant impact, whereas the multi-tier insurance system may not significantly affect the savings rate. Based on the aforesaid research conclusions, this article believes that in order to reduce the savings rate of rural households and expand consumption, the health insurance system should be further improved.

Multi-tier scheduling algorithm of dispatching systems for urban water logging

Due to global warming, considerable amounts of storm rain have occurred, causing urban water logging and flooding. The efficient scheduling of drainage systems among pumping stations is crucial to mitigating flash flooding in urban areas. This study introduces a Multi-Level Dynamic Priority and Importance Scheduling (MDPIS) algorithm as a proactive solution for addressing urban flooding through the optimization of drainage system discharge capacities. The algorithm's robustness is guaranteed through the integration of a multi-tier drainage system and dependency relationships. Additionally, the incorporation of an importance parameter is considered for facilitating the practical exploration of flooding risk evaluation. The proposed model was applied to simulate a drainage system in Haining City, and the results indicate that its accuracy, flexibility and reliability outperform that of existing algorithms such as fixed-priority scheduling. Moreover, the proposed approach enabled a considerable reduction in overflow loss and improved the efficiency of the sewage system. This method can improve the responses of cities to the rising problem of urban water logging.

Crime and Sanctions: Beyond Sanctions as a Foreign Policy Tool

AbstractTargeted sanctions, namely asset freezes and travel bans, are no longer the province of foreign policy alone. They are increasingly often used by governments in response to crime, such as corruption, human rights abuse, cybercrime, drug trafficking, and transnational organized crime writ large. Such sanctions are imposed based on permissive evidential standards, such as that of “credible evidence” or “reasonable grounds to suspect.” Their advent has added a new layer to a multi-tier system of state responses to crime. First, there is the traditional approach of criminal prosecution and conviction based on the criminal standard of proof. Second, one rung below is non-conviction based asset forfeiture, a notionally civil confiscation of supposed proceeds of crime that eschews the need for compliance with a suite of criminal trial safeguards. At the third level of this hierarchy are crime-based targeted sanctions, which vest the state with the greatest latitude in dealing with suspected criminals. Based on a wide-ranging analysis of international practice, this article contends that not only are crime-based sanctions de facto a criminal justice tool, but also that a coherent set of principles is required to determine their relationship with other responses to criminal behavior.

METAL ADDITIVE MANUFACTURING IN SPACE AND AEROSPACE EXPLORATION: CURRENT PROCESSES, MATERIAL SELECTION AND CHALLENGES

Space and aerospace exploration have the highest regulations regarding design and manufacturing processing. As a result, an immense multi-tier manufacturing system has been developed because of the tooling and machinery associated with the production of high-grade spacecraft and aircraft. Furthermore, the nature of the supply chain and hefty capital investments further complicate spacecraft and aircraft manufacturing. Metal additive manufacturing (AM) offers the best solution to produce complex parts from digital information without the need for large amounts of tooling and machinery. MAM represents a promising aspect of innovations to revolutionize the way manufacturing is designed and constructed for many applications. Moreover, various research activities are being carried out in the aerospace industry for MAM process, which produces parts that would be impossible to create using conventional manufacturing (CM) methods. MAM has gained popularity in recent years from its initial stages of development in the research phase to providing a wide range of functional applications in the aerospace industry to manufacture and repair a wide range of components used in spacecraft and aircraft. The significant growth in MAM process can be attributed to its commercial and performance advantages within the aerospace industry. In this paper, a detailed assessment of existing MEM processes is presented, emphasizing the ability to manufacture and repair metal parts for the aerospace industry, providing information about the materials currently in use, as well as identifying possible future applications and challenges. There is no doubt that the information provided in this study will support exploring MAM’s new opportunities for future needs in space and aerospace exploration.

Keel bone fractures affect laying hens' mobility, but no evidence for reciprocal effects.

Keel bone fractures (KBF) are prevalent in commercial laying hens and are considered one of the greatest welfare concerns in the egg-production industry. While clear associations exist between KBF and animal mobility, suggesting that KBF impair mobility, the effect of mobility on KBF remains unclear. We combined data from three studies that assessed keel bone fracture severity through radiographs and monitored hens' transitions between different zones of a multi-tier aviary system (the three tiers, a littered floor, and a winter garden) the week prior to radiograph. For each hen, we extracted two daily movement behaviours: the vertical distance travelled and the mean number of zones crossed within one transition; and two daily space-use behaviours: the time spent in the top tier and the unevenness of time spent across zones. We used hierarchical Bayesian continuous time dynamic modelling to estimate how a change in a behaviour predicted a later change in keel bone fracture severity, and vice versa. Increased fracture severity did not predict later changes in space-use behaviours, but it did predict changes in movement behaviours. Specifically, increased fracture severity led to decreased vertical travelled distance and a tendency to cross more zones within one transition, suggesting impaired mobility in hens with increased fracture severity. In contrast, we found no evidence that movement or space-use behaviours predict later change in fracture severity, challenging previous literature suggesting that vertical locomotion through jumping and flying may exacerbate keel bone fractures in complex three-dimensional systems due to increased risk of collisions. However, similar efforts accounting for the location of fractures on the keel could unveil the potential influence of movement and space-use behaviours in the formation and change (healing or worsening) of KBF and increase our ability to mitigate their effects.

An Investigation of Simultaneous Prompting to Teach an Addition Algorithm to Preschool Students

This manuscript reports the results of an investigation of the simultaneous prompting procedure to teach a five-step algorithm for solving three addition basic facts. Four preschool students receiving Tier 1 services in their school’s multi-tier system of supports (MTSS) framework participated. A multiple probe across participants single case design was employed, and a visual analysis of the data indicate a functional relationship between the independent and dependent variable. Three of the participants achieved the mastery criterion and maintained the targeted learning outcome for 2–6 weeks. These participants applied the five-step algorithm to three sets of novel addition facts and acquired incidental information consisting of mathematics terminology. The fourth participant voluntarily discontinued her involvement in the study but, prior to her withdrawal, her data were similar to that of the other three participants. Social validity data from the participants’ teachers confirmed their satisfaction with the study’s procedures and participants’ learning outcomes. The results extend those from related research and validate simultaneous prompting’s effectiveness in teaching mathematics to students receiving Tier 1 and Tier 3 services in an MTSS framework. Topics for future research are discussed, and include investigating the effectiveness of simultaneous prompting to teach mathematics across students receiving services through all MTSS tiers.

Spatial distribution, movement, body damage, and feather condition of laying hens in a multi-tier system

The welfare and health of laying hens in the multitier system raise concern in public. The flock distributions during feeding time at 51 and 89 wk were studied in a multitier system. Furthermore, the ultra-high frequency radio frequency identification (UHF RFID) equipment was used to identify the transition between tiers and time spent in each tier of 48 focal hens (12 hens from each tier-group of the multitier system) at 92 wk of age. The body weight, tibia size (length and width), body damage (comb and rear part), and feather condition (neck, breast, back, tail, cloaca, and wings) of focal hens from different tier-groups were further compared. The results showed that the spatial distribution in flocks changed from top to bottom with increasing age. The hens at 51 wk of age were mainly distributed in the 4th tier (19.6 ± 5.0% in 1st tier, 9.6 ± 1.1% in 2nd tier, 23.6 ± 2.9% in 3rd tier and 47.3 ± 2.6% in 4th tier), and hens at 89 wk of age were mainly distributed in the lower tiers (33.5 ± 1.5% in 1st tier, 31.9 ± 5.1% in 2nd tier, 15.7 ± 3.4% in 3rd tier and 16.6 ± 3.1% in 4th tier). The spatial distribution of hens at 89 wk of age was more even than that at 51 wk of age. At 92 wk of age, the proportion of time spent in original tier of 4 tier-groups was 91.0 ± 5.7%, 51.9 ± 5.7%, 59.0 ± 7.0% and 63.0 ± 6.7%, respectively. Focal hens preferred to stay in the original tier and spent significantly less time in other tiers (P < 0.05). There was no significant difference in body weight, body damage score, tibia width and partial feather scores (neck, breast, tail, and cloaca) of focal hens among 4 tier-groups (P > 0.05). However, focal hens from 1st tier had worse feather scores on wings and back, and shorter tibia length compared to other tiers suggesting that there were more lower ranking birds that located in lower tier to avoid competition, but had equal access to resource, which is good for their welfare and health. In summary, the overcrowding situation was improved near the end of the laying cycle in the multitier system, thereby mitigating the potential negative effects to the lower ranking hens and maintain a satisfactory level of welfare and health for laying hens near the end of the laying cycle.

MADDPG-empowered slice reconfiguration approach for 5G multi-tier system

With the advancement of fifth-generation (5G) communication technology, plenty of vertical applications have emerged. These applications usually center on highly different quality of service (QoS) requirements, posing challenges for the supporting communication network. To address these challenges, network slicing has been proposed to partition the underlying network into multiple tailored logical networks, called as network slices. Each slice corresponds to a specific application. However, fluctuations in user activities for applications may lead to workload variation across corresponding slices, which compromising the consistent QoS provisioning. In this context, slice reconfiguration becomes imperative to ensure satisfactory user experiences. In this work, we introduce the multi-agent deep reinforcement learning method to tackle the slice reconfiguration problem and propose the multi-agent deep deterministic policy gradient-empowered slice reconfiguration (MADDPG-SR) algorithm. In MADDPG-SR, each network function is abstracted as an agent that learns to optimize its own migration in the multi-layer network to minimize the preference-weighted processing resource cost while adhering QoS and resource constraints. The proposed method is compared with four other benchmarks, and the comparison results demonstrate that MADDPG-SR can significantly reduce both the preference-weighted resource cost, and the running time for acquiring slice reconfiguration decisions while ensuring the QoS performance of slices.

Pricing, replenishment and consignment strategies for a multi-tier supply system under various structures

Pricing, replenishment and consignment strategies for a multi-tier supply system under various structures

Adaptive variable neighbourhood search approach for time-dependent joint location and dispatching problem in a multi-tier ambulance system

Location-allocation of ambulances is a critical planning problem in the efficient operation of an emergency medical services system. This work considers a joint ambulance location and dispatch problem for a multi-tier ambulance system. The proposed problem addresses three key decisions: the location of ambulance stations, allocation of ambulances to these stations, and the preference order of stations for dispatching ambulances. We consider various other important factors, such as temporal variation in demand and travel time, station-specific ambulance busy probabilities and possible relocation of ambulances over the day. A mixed-integer non-linear programming model is formulated with a survival probability-based objective function to represent the problem. A queueing-based iterative approximation approach is presented to estimate the station-level dispatch probability of ambulances. We propose an adaptive variable neighbourhood search approach to solve the problem that utilises the approximation approach to obtain the objective function. A relaxed station location problem combined with a particle swarm approach for ambulance allocation is solved to obtain an initial solution. The effectiveness of the proposed approach is validated using a dataset generated based on the city of Kolkata in India.

Delayed arrival of advanced life support adversely affects the neurological outcome in a multi-tier emergency response system

AimPrehospital management of out-of-hospital cardiac arrest (OHCA) is based on basic life support, with the addition of advanced life support (ALS) if possible. This study aimed to investigate the effect of delayed arrival of ALS on neurological outcomes of patients with OHCA at hospital discharge. MethodsThis was a retrospective study of a registry of patients with OHCA. A multi-tier emergency response system was established in the study area. ALS was initiated when the second-arrival team arrived at the scene. A restricted cubic spline curve was used to investigate the relationship between the response time interval of the second-arrival team and neurological outcomes at hospital discharge. Multivariable logistic regression analysis was performed to assess the independent association between the response time interval of the second-arrival team and neurological outcomes of patients at hospital discharge. ResultsA total of 3186 adult OHCA patients who received ALS at the scene were included in the final analysis. A restricted cubic spline curve showed that a long response time interval of the second-arrival team was correlated with a high likelihood of poor neurological outcomes. Meanwhile, multivariable logistic regression analysis showed that a long response time interval of the second-arrival team was independently associated with poor neurological outcomes (odds ratio, 1.10; 95% confidence interval, 1.03–1.17). ConclusionIn a multi-tiered prehospital emergency response system, the delayed arrival of ALS was associated with poor neurological outcomes at hospital discharge.

Collaborative Orchestration of Multi-Domain Edges From a Connected, Cooperative and Automated Mobility (CCAM) Perspective

The 5G ecosystem is comprised of the cellular 5G System, as well as a managed and orchestrated infrastructure providing virtualized network and service functions. The automotive industry with its stringent requirements for connected vehicles is a promising and yet challenging consumer of such 5G ecosystem. Deployment of service instances at distributed cloud resources of cellular network infrastructure edges enables localized low-latency access to these services from moving vehicles but comes along with challenges, such as the need for fast reconfiguration of the distributed deployment according to mobility pattern and associated service and resource demand. In this paper, we investigate a solution for the collaborative orchestration of services for Connected, Cooperative and Automated Mobility (CCAM) within such 5G ecosystem. A key objective is the service continuity for a highly dynamic automotive scenario, achieved by the associated management and orchestration of these services in distributed edge clouds. The proposed solution leverages a multi-tier orchestration system as well as localized management and protocol operations for collaborative edge resources. By means of both analytical and experimental evaluations, the paper draws conclusions on the gain in accelerating orchestration decisions and enforcements, while balancing associated protocol and computational load over the highly distributed and multi-layered orchestration system.

Defining Trade Secrets in the United States: Past and Present Challenges – A Way Forward?

When approaching an analysis of a particular area of law, one must initially locate and understand the definition of its core concept. Yet in trade secret law serious obstacles impede the process. Unlike other intellectual property (IP) regimes, such as copyright and patent law, the core concepts of which are subject to unitary definitions governed by international treaties or domestic statutes, the trade secret concept has received no parallel treatment and, until recently in the United States, remained mainly defined under common law. Subtle differences in the way trade secrets were judicially conceived often generated conflicts between courts, opening the door for the application of divergent rules on similar points. This confusing background prompted the individual U.S. jurisdictions to gradually orient towards implementing statutory provisions in defining trade secrets. Despite the fact that U.S. trade secret law has since seen several statutory interventions at state and federal level, the precise meaning and definitional parameters of the concept remain elusive. This paper probes the existing trade secret definitions applicable in the U.S. via analysis of the divergent sources of law that underscored their formulation from the past until the present and identifies the challenges pertinent to their application in practice. Its aim is to analyze and compare these legal sources: first, to determine whether the current definition for the concept of a trade secret is adequate, or whether perhaps the existence of the multi-tier system impedes a party’s ability to identify trade secrets in a cross-border context; and second, to investigate whether a unanimously accepted definition under a pre-emptive statute complementary to one under an elaborated internationally binding treaty might remedy this issue.

Joint C-V2X Based Offloading and Resource Allocation in Multi-Tier Vehicular Edge Computing System

Emerging intelligent transportation services are latency-sensitive with heavy demand for computing resources, which can be supported by a multi-tier computing system composed of vehicular edge computing (VEC) servers along the roads and micro servers on vehicles. In this work, we investigate the dual Uu/PC5 interface offloading and resource allocation strategy in Cellular Vehicle-to-Everything (C-V2X) enabled multi-tier VEC system. The successful transmission probability is characterized to obtain the normalized transmission rate of PC5 interface. We aim to minimize the system latency of task processing while satisfying the resource requirements of Uu and PC5 interfaces. Due to the non-convex and variables coupling, we decompose the original problem into two subproblems, i.e., resource allocation and offloading strategy subproblems. Specifically, we derive the closed-form expressions of packet transmit frequency of PC5 interface, transmission power of Uu interface, and CPU computation frequency in the resource allocation subproblem. Moreover, for the offloading strategy subproblem, the offloading ratio matrix is obtained by proposing the PC5 interface based greedy offloading (PC5-GO) algorithm, which concludes offloading decision and ratio. Simulation results are provided that the proposed PC5-GO algorithm can significantly improve the system performance compared with other baseline schemes by 13.7% at least.

Intelligent Reflecting Surface Backscatter Enabled Multi-Tier Computing for 6G Internet of Things

This paper investigates a novel framework of intelligent reflecting surface (IRS) backscatter enabled multi-tier computing system. In such a hierarchical network, the data bits of computational task requested by each user equipment (UE) are broken up into three parts, which are respectively computed at tier-1 UEs, tier-2 access points (APs) and a tier-3 central server. Distinguished from conventional active antennas, IRS backscatter at the UEs is leveraged to offload data bits to the APs. Based on the established network framework, an optimization problem is formulated, which aims at maximizing the sum computational bits of system during the considered time block by jointly optimizing the active beamforming at the power beacon, the passive beamforming at the UEs, the active beamforming at the APs, the bandwidth and power allocation among all the UEs, as well as the time of local computing. To seek the optimal solution, the optimization problem is decomposed into two, namely the maximization of stage-1 sum computational bits and the minimization of stage-2 delay. By the objective function conversion and alternative optimization methods, the two problems are addressed. Extensive simulations are performed to confirm the feasibility of the proposed system and show the achievable performance in processing computational bits.