On the Impact of Network Evolution on NUM Resource Allocation Problems in Wireless Multihop Networks

2015 ◽  
pp. 62-75
Author(s):  
Eleni Stai ◽  
Vasileios Karyotis ◽  
Symeon Papavassiliou
Keyword(s):  
Resource Allocation ◽  
Network Evolution ◽  
Multihop Networks ◽  
Wireless Multihop Networks ◽  
Allocation Problems ◽  
The Impact

Performance analysis of resource allocation in wireless multihop networks

2006 ◽  
Vol 29 (8) ◽  
pp. 983-993
Author(s):  
Matthias Lott ◽  
Martin Weckerle ◽  
Matthias Siebert
Keyword(s):  
Resource Allocation ◽  
Performance Analysis ◽  
Multihop Networks ◽  
Wireless Multihop Networks

scholarly journals A new enhancement to avoid video distortion in wireless multihop networks

2018 ◽  
Vol 7 (2.7) ◽  
pp. 326
Author(s):  
Dr R.Bulli Babu ◽  
SK Shahid Afridi ◽  
S Satya Vasavi
Keyword(s):  
Wireless Networks ◽  
Wireless Channels ◽  
Analytical Framework ◽  
Routing Algorithms ◽  
Multihop Networks ◽  
Link Quality ◽  
Wireless Multihop Networks ◽  
Video Traffic ◽  
The Impact

The protocols of typical routing algorithms which are designed for the wireless networks long back are specifically application oriented. Taking consideration at present, with the increase in the usage of the wireless networks the problem we are facing is video traffic. The very important thing is to maintain a good quality of video. At present users are opting videos in high quality that are to be delivered smoothly into their devices. The nature of video is changed due to 1) Because of the compression distortion occurs at the source. 2) With both interference and the errors induced on wireless channels distortion occurs. Hence, in this paper we work for the reduction of the distortion that occurs in video traffic. In order to overcome this problem we opted a wireless network in which the flow of application contains video traffic. For the clients the reduction of the distortion is very difficult. We cannot minimize the video distortions by using the link quality based routing measures. To understand this we construct an analytical framework first, then on the video distortions for accessing the impact. By using an analytical framework we design a routing measure for the reduction of distortion. With our experiment results we evaluate that our protocol is best for the reduction of video distortion and also for the reduction of the experience of user de-gradations.

Computers in Medical Care: A Review

1984 ◽  
Vol 23 (02) ◽  
pp. 63-74 ◽  
Author(s):  
Hans W. Gottinger
Keyword(s):  
Resource Allocation ◽  
Medical Care ◽  
Hospital Care ◽  
The Impact

SummaryThis survey provides an overview of major developments on the impact of computers in medical and hospital care over the last 25 years. Though the review emphasizes developments in the U. S. and their multi-faceted impacts upon resource allocation and regulation, a serious attempt is made to track those impacts being universally true in multinational environments.

Change in Service Provision Networks: The Case of Animal Welfare Services

2021 ◽  
pp. 0160323X2110092
Author(s):  
Laura A. Reese ◽  
Xiaomeng Li
Keyword(s):  
Service Provision ◽  
Survey Design ◽  
Participant Observation ◽  
Local Level ◽  
Major Change ◽  
Network Evolution ◽  
Political Factors ◽  
Before And After ◽  
Organizational Ties ◽  
The Impact

This research focuses on change within informal service provision networks, specifically examining the impact that changes within a key organization can have on the larger network. Employing a before and after survey design with a treatment at the midpoint and participant observation, it asks: What is the impact of a major change within one organization on the larger external network? What is the nature of the organizational ties? and, How do political factors exogenous to the network impact the network evolution process? The findings suggest that internal change within a focal actor can have ripple effects throughout the network increasing density. Public service provision at the local level can be enhanced through an increase in partnerships between the public and nonprofit sectors. However, network evolution can be limited by the larger political environment and lack of a coordinating role on the part of local government.

scholarly journals The impact of predictability on dual-task performance and implications for resource-sharing accounts

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Laura Broeker ◽  
Harald Ewolds ◽  
Rita F. de Oliveira ◽  
Stefan Künzell ◽  
Markus Raab
Keyword(s):  
Resource Allocation ◽  
Task Performance ◽  
Dual Task ◽  
Resource Sharing ◽  
Visual Information ◽  
Allocation Policy ◽  
Capacity Sharing ◽  
Dual Task Performance ◽  
Sound Sequence ◽  
The Impact

AbstractThe aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

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