Resource Broker Research Articles

Different ways to broker: school social workers, resource distribution, and equity for immigrant students

ABSTRACT This study uses quantitative methods to explore the role of school social workers (SSWs) in promoting education equity for immigrant students. We focus on how SSWs act as resource brokers, connecting immigrant students to valuable resources both in schools and the wider community. Our analysis is based on data from a national survey of SSWs (N = 324). Through regression and multivariate analyses we find that a significant number of SSWs actively facilitate resource access for immigrant students. This often involves bridging the gap between teachers and immigrant parents. Notably, SSWs were more likely to engage in these brokerage activities when they recognized that the students were adversely affected by the threat of immigration enforcement. We conclude with targeted recommendations for policy and practice to better train and support SSWs as resource brokers.

An autonomous blockchain-based workflow execution broker for e-science

Scientific workflows are essential for many applications, enabling the configuration and execution of complex tasks across distributed resources. In this paper, we contribute an Ethereum blockchain-based scientific workflow execution manager, which distributes workflows to run on cluster computing providers that utilize the Slurm workload manager to execute them. We extended our blockchain-based autonomous resource broker called eBlocBroker, which is a DAO-based decentralized coordinator, by providing distributed workflow execution via blockchain. Through various tests, we demonstrate how our eBlockBroker autonomous organization, which is programmed as a smart contract, can manage scientific workflow submission, scheduling, and execution on cluster computing providers. The utilization of blockchain for distributed workflow execution is a new concept. We are motivated because our system has been developed with e-Science in mind where scientific workflows are widely utilized.

Brokers and Boundary Managers: School Expulsions amid the Non-Punitive Turn

Abstract Like many American institutions, K–12 schools are increasingly embracing a rhetoric of non-punitiveness and seeking to supply resources instead of imposing harsh punishment. Using ethnographic data from a diverse, suburban, well-resourced public high school, I explore how institutional actors manage this central role in the provision of goods and services. I find that school staff lack the capacity to successfully serve as brokers for all their constituents, forcing decisions about how to allocate their limited resources. Staff navigate these constraints by strategically managing the boundaries of the institution, redefining who gets to remain a member and who they will continue brokering for. I describe how and when these exclusions occur and show that students from less advantaged backgrounds are at higher risk of expulsion because they depend more on the school for resources than their privileged peers. Further, informal methods of exclusion become favored in this non-punitive pivot, meaning that official data likely undercount the number of students forcibly removed from their schools. As institutions take on more resource brokering amid the turn towards non-punitiveness, the decisions of boundary managers – those actors with the power to enroll and expel members – become increasingly consequential for the allocation of public resources.

TRUSTS Technology Integration Inventory: Assessing the Impact of a New Technology on Work System Resilience

We present the Transform with Resilience during Upgrades to Socio-Technical Systems (TRUSTS) Framework, which specifies sources of work system resilience. A work system is defined as elements, including technology, people, policies, protocols, and procedures, that cooperatively function to achieve shared goals. By describing sources of work system resilience, the framework can help a work system’s stakeholders preserve its resilience. This is especially important for high-consequence work systems; these are work systems involved in healthcare, military operations, and national airspace management, as examples. In these work systems, responsivity and adaptivity, i.e., resilience, are requisites to achieving missions and goals in the face of outages and other unexpected events, high demands, and nonroutine conditions. In event-driven environments, system resilience is also required to respond to routine variety produced by uncontrollable aspects of the work, such as treatment responses, weather, and adversary behaviors. The TRUSTS framework is derived from foundational literature in complex systems science and resilience engineering. We build upon prior research in resilience engineering. In that body of work, work system resilience has been defined by Erik Hollnagel and colleagues as based on four cornerstones: anticipating, monitoring, responding, and learning. Its fundamental principles have been described in David Woods’ Theory Graceful Extensibility and writings on complex systems’ adaptive capacity. These cornerstones and principles have typically been described as high-level system capabilities that are illustrated by examples. With TRUSTS, we identify detailed system characteristics and capabilities that afford those high-level cornerstones. The framework is organized into five inter-related factors (a.k.a. the “Big Five” factors) that allow a high-consequence work system and its operations to be responsive and adaptive in the face of challenges. Each of the “Big Five” consists of three to four sub-factors, and each sub-factor consists of two or more resilience requirements. The framework and our associated efforts to operationalize work system resilience are heavily informed by targeted analysis of case studies of new technologies introduced into high-consequence work operations, including healthcare work operations, and interviews with military planning and command and control experts. Currently, we are endeavoring to integrate the TRUSTS Framework into the development of new technologies for health care and other high-consequence work systems. Increasingly, technologies are designed to participate in core work system activities, such as assessment, decision making, planning, and resource brokering and allocation. In these roles, they become integral to the work of other system elements—both technological and human—and the work system as a whole; i.e., they are a part of that work system. When technologies have core roles such as these, they have greater potential to inadvertently interfere with one or more of the means used by the work system to be adaptive and resilient to changing demands and conditions. They also have greater potential to positively contribute to the work system’s resilience. Our goal is to help developers attend to the ways their new technology will impact the work system’s ability to be adaptive and resilient. We present ongoing work to integrate TRUSTS Framework resilience sources into technology development, including newly developed methods and tools that together enable a TRUSTS Resilience-Aware Development (RAD) approach to technology development. The goal of RAD is to help ensure new technologies are designed to contribute to and not unintentionally compromise work system resilience. It ensures technology development benefits both work system efficiency and resilience in the balanced way that is necessary for long-term work system and mission success. Together, the TRUSTS framework and RAD approach and tools can be used to ensure that, as our healthcare work systems become more complex and technology-driven, they maintain the ability to provide responsive patient care and safety that is adaptive to conditions.

Measuring a motivational interviewing practice orientation in criminal justice practitioners: initial validation of the response style screening questionnaire.

The use of collaborative communication techniques by criminal justice practitioners has been identified as a component of core correctional practices (CCPs). Criminal justice agencies and programs are investing in motivational interviewing (MI) training for their staff with varying intensity, follow-up coaching, and expectations for integration into practice. The present article describes the development and initial validation of the Response Style Screening Questionnaire (RSSQ), a practitioner completed tool assessing an MI-consistent practice orientation. Over three studies, we examined the factor structure, reliability, and correlations between the scale and self-reported and behavioral validity indicators. Study 1 examined the factor structure of the RSSQ with a sample of 825 criminal justice practitioners. In Study 2, data from 350 probation officers completing the RSSQ alongside measures of work-orientation and attitudes was used to conduct a confirmatory factor analysis and an initial assessment of its construct validity. In Study 3, correlations between the RSSQ and audio recorded office visits of 33 probation officers coded for MI and relationship building skills examined the scale's criterion validity. In Study 1, an exploratory factor analysis with an oblique rotation yielded 18 items on four factors. In Study 2, four and five factor models were tested, with the 4-factor model of Study 1 yielding the best fit. Two of the 4 factor-derived subscales reflect styles inconsistent with MI: (1) Confrontational style, and (2) Sustain Talk style; while the remaining two reflect styles consistent with MI: (3) Eliciting style, and (4) Change Talk style. Confrontational style scores were correlated with a work-orientation reflecting probation as a law enforcement endeavor, while Eliciting and Change Talk scores were correlated with a behavior change and resource broker work-orientations. In Study 3, Confrontational and Sustain Talk style scores were negatively correlated with a variety of MI skills and CCPs displayed on audio recordings, while Change Talk style scores were positively correlated with use of such skills. Overall, the findings suggest the RSSQ is a potentially useful new practitioner self-report tool for assessing an MI practice orientation.

A computational computing system and its implementation for resource broker in IoT

In the computing world Internet of Things or even more normally IoT is an arising idea in the specialized world. We need more solace in our life. The web has turned into a centerpiece of our life. This IoT depends on this coordinated effort of solace and the Web. open new security challenges in light of multiple factors. First and foremost, security techniques should be adjusted because proposed calculation that in view of appropriated design require extra various agents and different correspondence principles that might increment security dangers and increment security the executive’s intricacy. Besides, proposed calculation is intrinsically missing productive security highlights since it performs username/secret word-based validation in a plain text, that safeguarded by cryptographic convention SSL/TSL which is not consider as lightweight convention for assets obliged gadgets. This paper will introduce scientific categorization and acknowledgment interaction of IoT confirmation conspire. Moreover, the paper will talk about difficulties of applying validation components for IoT frameworks that in view of circulated.

Smart resource scheduling by correlating discriminative quality factors to optimise resource utilisation in IAAS of cloud networks

The significant requirement in cloud computing is detecting the deterministic model for performing resource scheduling. Resource scheduling is crucial because of the presence of several anomalies and high dimensionality values shown during resource scheduling. The number of tasks envisioned in contention at resource broker of IAAS and higher dimensionality of proposed anomalies values for quality resource aspects was out of scope concerning the existing resource scheduling techniques. Therefore, the contemporary resource scheduling techniques were not prominent for optimal resource scheduling. For optimising resource scheduling in terms of earlier mentioned properties like the maximum amount of tasks and maximum dimensionality anomalies projection, an ensemble resource scheduling technique has been derived in this article under batch scheduling classification. Further, the simulation study envisioned that the projected model of this contribution is more significant and robust for delivering optimum resource scheduling when compared to other contemporary models in terms of dimensionality and volume of anomalies.

Resource Brokering: Efforts to Assist Patients With Housing, Transportation, and Economic Needs in Primary Care Settings.

Clinicians and policy makers are exploring the role of primary care in improving patients' social conditions, yet little research examines strategies used in clinical settings to assist patients with social needs. Study used semistructured interviews with leaders and frontline staff at 29 diverse health care organizations with active programs used to address patients' social needs. Interviews focused on how organizations develop and implement case management-style programs to assist patients with social needs including staffing, assistance intensity, and use of referrals to community-based organizations (CBOs). Organizations used case management programs to assist patients with social needs through referrals to CBOs and regular follow-up with patients. About one-half incorporated care for social needs into established case management programs and the remaining described standalone programs developed specifically to address social needs independent of clinical needs. Referrals were the foundation for assistance and included preprinted resource lists, patient-tailored lists, and warm handoffs to the CBOs. While all organizations referred patients to CBOs, some also provided more intense services such as assistance completing patients' applications for services or conducting home visits. Organizations described 4 operational challenges in addressing patients' social needs: (1) effectively engaging CBOs; (2) obtaining buy-in from clinical staff; (3) considering patients' perspectives; and (4) ensuring program sustainability. As the US health care sector faces pressure to improve quality while managing costs, many health care organizations will likely develop or rely on case management approaches to address patients' social conditions. Health care organizations may require support to address the key operational challenges.Visual abstract.

BRAINS 2020 special issue: Blockchain research and applications for innovative networks and services

BRAINS 2020 special issue: Blockchain research and applications for innovative networks and services

Protected Area Rangers as Cultural Brokers? Implications for Wildlife Crime Prevention in Viet Nam

The scope, scale, and socio-environmental impacts of wildlife crime pose diverse risks to people, animals, and environments. With direct knowledge of the persistence and dynamics of wildlife crime, protected area rangers can be both an essential source of information on, and front-line authority for, preventing wildlife crime. Beyond patrol and crime scene data collected by rangers, solutions to wildlife crime could be better built off the knowledge and situational awareness of rangers, in particular rangers' relationships with local communities and their unique ability to engage them. Rangers are often embedded in the communities surrounding the conserved areas which they are charged with protecting, which presents both challenges and opportunities for their work on wildlife crime prevention. Cultural brokerage refers to the process by which intermediaries, like rangers, facilitate interactions between other relevant stakeholders that are separate yet proximate to one another, or that lack access to, or trust in, one another. Cultural brokers can function as gatekeepers, representatives, liaisons, coordinators, or iterant brokers; these forms vary by how information flows and how closely aligned the broker is to particular stakeholders. The objectives of this paper are to use the example of protected area rangers in Viet Nam to (a) characterize rangers' cultural brokerage of resources, information, and relationships and (b) discuss ranger-identified obstacles to the prevention of wildlife crime as an example of brokered knowledge. Using in-depth face-to-face interviews with rangers and other protected area staff (N = 31, 71% rangers) in Pu Mat National Park, 2018, we found that rangers regularly shift between forms of cultural brokerage. We offer a typology of the diverse forms of cultural brokerage that characterize rangers' relationships with communities and other stakeholders. We then discuss ranger-identified obstacles to wildlife protection as an example of brokered knowledge. These results have implications for designing interventions to address wildlife crime that both improve community-ranger interactions and increase the efficiency of wildlife crime prevention.

Transformative Social Innovation in Rural Areas: Insights from a Rural Development Initiative in the Portuguese Region of Baixo Alentejo

Abstract The role of social innovation initiatives in contributing to sustainable rural development has been discussed both in academia and practice. Some scholars argue that, rather than delivering solely on unmet needs and services, social innovation should have a broader transformative impact. By applying Castro-Arce and Vanclay’s analytical framework for transformative social innovation (2020), the paper seeks to analyse the experience of a rural development initiative based in Portugal. The results of this exploratory study indicate that, in triggering bottom-linked governance, the initiative has taken on the bridging roles of knowledge broker, resource broker, shared vision champion, transparency and conflict resolution agent, and network enabler. Alongside taking on these bridging roles, the initiative under study, while promoting cooperation and knowledge exchange, has encountered some challenges further discussed in the paper. Finally, the paper makes some suggestions on how the proposed framework could be enriched.

Multi-Cloud Performance and Security Driven Federated Workflow Management

Federated multi-cloud resource allocation for data-intensive application workflows is generally performed based on performance or quality of service (i.e., QSpecs) considerations. At the same time, end-to-end security requirements of these workflows across multiple domains are considered as an afterthought due to lack of standardized formalization methods. Consequently, diverse/heterogenous domain resource and security policies cause inter-conflicts between application's security and performance requirements that lead to sub-optimal resource allocations. In this paper, we present a joint performance and security-driven federated resource allocation scheme for data-intensive scientific applications. In order to aid joint resource brokering among multi-cloud domains with diverse/heterogenous security postures, we first define and characterize a data-intensive application's security specifications (i.e., SSpecs). Then we describe an alignment technique inspired by Portunes Algebra to homogenize the various domain resource policies (i.e., RSpecs) along an application's workflow lifecycle stages. Using such formalization and alignment, we propose a near optimal cost-aware joint QSpecs-SSpecs-driven, RSpecs-compliant resource allocation algorithm for multi-cloud computing resource domain/location selection as well as network path selection. We implement our security formalization, alignment, and allocation scheme as a framework, viz., “OnTimeURB” and validate it in a multi-cloud environment with exemplar data-intensive application workflows involving distributed computing and remote instrumentation use cases with different performance and security requirements.

Mobilizing Blackness: Analyzing 21st Century Black Student Collective Agency in the University

Black student activism in the 21st century has gained international notoriety with popular movements such as #StudentBlackOut, #FeesMustFall, and #ConcernedStudent1950. Between 2014-2017, Black students manipulated the momentum of a larger social movement (the Movement for Black Lives) in order to secure organizing victories for racial justice, both on and off their college campuses. This essay explores the meaning making processes of Black student activists who participated either in on campus or off campus activism between 2014-2017. Emerging themes from the interviews have demonstrated that Black student activists are both politicized and enter movement organizing because of catalytic events, and they see themselves as resource brokers who funnel university resources, labor, and energy into dispossessed communities. I argue that students use their racialized subjectivities in the neoliberal university space to leverage resources. In addition, Black students are highly aware of their positionality, and they raise critiques of their class-fluid positions as college students and the protections that student identity provides them.

Combinatorial Double Auction Based Meta-scheduler for Medical Image Analysis Application in Grid Environment

Background: Medical image analysis application has complex resource requirement. Scheduling Medical image analysis application is the complex task to the grid resources. It is necessary to develop a new model to improve the breast cancer screening process. Proposed novel Meta scheduler algorithm allocate the image analyse applications to the local schedulers and local scheduler submit the job to the grid node which analyses the medical image and generates the result sent back to Meta scheduler. Meta schedulers are distinct from the local scheduler. Meta scheduler and local scheduler have the aim at resource allocation and management. Objective: The main objective of the CDAM meta-scheduler is to maximize the number of jobs accepted. Methods: In the beginning, the user sends jobs with the deadline to the global grid resource broker. Resource providers sent information about the available resources connected in the network at a fixed interval of time to the global grid resource broker, the information such as valuation of the resource and number of an available free resource. CDAM requests the global grid resource broker for available resources details and user jobs. After receiving the information from the global grid resource broker, it matches the job with the resources. CDAM sends jobs to the local scheduler and local scheduler schedule the job to the local grid site. Local grid site executes the jobs and sends the result back to the CDAM. Success full completion of the job status and resource status are updated into the auction history database. CDAM collect the result from all local grid site and return to the grid users. Results: The CDAM was simulated using grid simulator. Number of jobs increases then the percentage of the jobs accepted also decrease due to the scarcity of resources. CDAM is providing 2% to 5% better result than Fair share Meta scheduling algorithm. CDAM algorithm bid density value is generated based on the user requirement and user history and ask value is generated from the resource details. Users who, having the most significant deadline are generated the highest bid value, grid resource which is having the fastest processor are generated lowest ask value. The highest bid is assigned to the lowest Ask it means that the user who is having the most significant deadline is assigned to the grid resource which is having the fastest processor. The deadline represents a time by which the user requires the result. The user can define the deadline by which the results are needed, and the CDAM will try to find the fastest resource available in order to meet the user-defined deadline. If the scheduler detects that the tasks cannot be completed before the deadline, then the scheduler abandons the current resource, tries to select the next fastest resource and tries until the completion of application meets the deadline. CDAM is providing 25% better result than grid way Meta scheduler this is because grid way Meta scheduler allocate jobs to the resource based on the first come first served policy. Conclusion: The proposed CDAM model was validated through simulation and was evaluated based on jobs accepted. The experimental results clearly show that the CDAM model maximizes the number of jobs accepted than conventional Meta scheduler. We conclude that a CDAM is highly effective meta-scheduler systems and can be used for an extraordinary situation where jobs have a combinatorial requirement.

Vehicular Cloud Resource Management, Issues and Challenges: A Survey

Recent advancements in the automotive industry have led to the design of smart vehicles with high capacity resources for communication, sensing, processing, and storage of data. In the near future, it is envisaged that these resources will be harnessed and utilized to provide cloud services such as storage as a service, computation as a service, and sensing as a service. This paradigm of computing termed vehicular cloud, presents a lot of opportunities for the deployment of delay-sensitive applications in vehicular environment. However, high mobility of vehicles and rapidly changing topology of vehicular networks introduce new challenges such as instability of resources which make the management of resources in vehicular cloud complicated. Therefore, vehicular cloud computing require robust and mobility-aware resource management solutions to be designed. In order to achieve this goal, researchers and engineers need to be abreast with the techniques of resource management in vehicular cloud. This article presents a detailed survey of resource management tasks in vehicular clouds. A thorough introduction to vehicular cloud is presented initially. Then we identify and examine all the resource management tasks that are carried out in vehicular cloud by classifying them into three different phases: pre-resource assignment phase, resource-assignment phase, and post resource assignment phase. Proposed solutions to resource management challenges in literature at each phase are reviewed in detail. Unlike the existing surveys on vehicular clouds, this study covers all aspects of resource management such as resource brokering, resource demand prediction, resource allocation, and resource scheduling. Following the extensive survey, we also propose frameworks for resource monitoring and resource brokering for vehicular cloud. Finally, open issues and research directions for vehicular cloud resource management are presented.

Transformative social innovation for sustainable rural development: An analytical framework to assist community-based initiatives

The interactions between bottom-up initiatives and top-down structures in the implementation of regional development policies and projects are complex in theoretical and practical terms. Using concepts such as transformative social innovation, adaptive governance, and bridging institutions, we developed an analytical framework to enhance understanding of the processes by which local top-down and bottom-up forces enhance sustainable rural development by co-developing bottom-linked governance. Bottom-linked governance is a multi-level middle ground where actors from various political levels, geographical scales and industry sectors come together to share decision-making. Social innovation has the potential to be transformative, but to do this, it has to be able to scale-up and provoke changes in the governance system. Using a rural social innovation initiative in Costa Rica, we tested our framework and considered the enabling factors of bottom-linked governance. They comprise the various bridging roles the initiative must play: network enabler; knowledge broker; resource broker; transparency and conflict resolution agent; and shared vision champion. We also considered the critical success factors of bottom-linked governance. Bottom-linked governance and social innovation together comprise how planning practice contributes to social-ecological regional development. Sharing of power and participatory decision-making facilitate more flexible, inclusive and effective planning. Our analytical framework was helpful in understanding how a social innovation initiative fostered transformation and contributed to sustainable rural development.

IRMM: An Integrated Resource Management Model for Grid Computing

Grid computing is a collection of heterogeneous systems or heterogeneous objects that are geographically distributed over a network. Resource management is a process in which various activities like allocation of resources and scheduling are performed for handling issues like load balancing, reliability, scalability, maximum, throughput, minimum expectation time and security. There are several factors that make resource management difficult as different system may have different requirements, properties, conditions and different access and cost models. Resource management in Grid is the method of identifying requirements, finding corresponding resources to the applications, allocating those matching resources, scheduling and monitoring. In Grid resource management resource broker plays the very important role. Users communicate with a resource broker to access the grid information. Resource broker discover the resource that are available and negotiates with their owners or their agents to get the reservation of resources. Number of approaches exists through which one can develop grid resource management systems. In this paper a new architectural model has been implemented for grid resource management which is based on the characteristics of both the Economical model and Hierarchical model.

Diversified Quality Aware Ensemble Resource Scheduling (DQAERS) for IAAS with Massive Load of Tasks and Resources in Cloud Computing

Identifying a deterministic approach to perform resource scheduling in cloud computing is crucial requirement, which is since, the volume of the anomalies and the high dimensionality of the values projected to these anomalies observed during resource scheduling. The volume of tasks that evinces flash-crowd state at resource broker of the IAAS, and high dimensionality of the anomalies projected for resource quality factors are out of scope in regard to contemporary resource scheduling strategies contributed in recent past. Hence’ the resource scheduling by contemporary methods in such conditions are insignificant as the resource scheduling optimality observed as probabilistic. In order to optimize the resource scheduling in the context of aforesaid properties high volume of tasks (flash-crowd state at resource broker) and high dimensional projection of anomalies, this manuscript derived an ensemble resource scheduling strategy, which fall in to the category of batch scheduling. The experimental study outlined that the proposal is most prominent and robust to deliver optimal resource scheduling in the context of anomalies of high volume and dimensionality that compared to the contemporary method.

Global Grids and Package Toolkits at 4 Grid Middleware Technologies

Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by many organizations. Grid applications often involve large amounts of data and/or computer resources that require a secure resource sharing throughout the organization. This makes grid operation and deployment a complex undertaking. Grid middleware provides users with seamless computer skills and uniform access to resources in the heterogeneous grid. A number of toolkits and systems have been developed, most of which are the result of academic research projects worldwide. This chapter focuses on four of these intermediaries: UNICORE, Globus, Legion and Grid bus. It also presents our implementation of a UNICORE resource broker because it did not support this functionality. A comparison of these systems is included based on the architecture, the implementation model and a number of other functions.

Distributed Meta-Brokering P2P Overlay for Scheduling in Cloud Federation

The interconnected cloud (Intercloud) federation is an emerging paradigm that revolutionizes the scalable service provision of geographically distributed resources. Large-scale distributed resources require well-coordinated and automated frameworks to facilitate service provision in a seamless and systematic manner. Unquestionably, standalone service providers must communicate and federate their cloud sites with other vendors to enable the infinite pooling of resources. The pooling of these resources provides uninterpretable services to increasingly growing cloud users more efficiently, and ensures an improved Service Level Agreement (SLA). However, the research of Intercloud resource management is in its infancy. Therefore, standard interfaces, protocols, and uniform architectural components need to be developed for seamless interaction among federated clouds. In this study, we propose a distributed meta-brokering-enabled scheduling framework for provision of user application services in the federated cloud environment. Modularized architecture of the proposed system with uniform configuration in participating resource sites orchestrate the critical operations of resource management effectively, and form the federation schema. Overlaid meta-brokering instances are implemented on the top of local resource brokers to keep the global functionality isolated. These instances in overlay topology communicate in a P2P manner to maintain decentralization, high scalability, and load manageability. The proposed framework has been implemented and evaluated by extending the Java-based CloudSim 3.0.3 simulation application programming interfaces (APIs). The presented results validate the proposed model and its efficiency to facilitate user application execution with the desired QoS parameters.