19 papers · ranked by Valyu relevance
Zhiyuan Yao, Zihan Ding, Thomas Clausen
Network load balancers are central components in data centers, that distributes workloads across multiple servers and thereby contribute to offering scalable services. However, when load balancers operate in dynamic environments with limited monitoring of application server loads, they rely on heuristic algorithms that…
Marios Avgeris, Dimitrios Spatharakis, Dimitrios Dechouniotis, Aris Leivadeas + 3 more
Mobile applications are progressively becoming more sophisticated and complex, increasing their computational requirements. Traditional offloading approaches that use exclusively the Cloud infrastructure are now deemed unsuitable due to the inherent associated delay. Edge Computing can address most of the Cloud…
Harisankar Sadasivan, Milos Maric, Eric Dawson, Vishanth Iyer + 2 more
Long read sequencing technology is becoming increasingly popular for Precision Medicine applications like variant calling from Whole Genome Sequencing (WGS) and for metagenomics applications like microbial abundance estimation. Minimap2 is the state-of-the-art aligner and mapper used by the leading long read sequencing…
Sarita Simaiya, Umesh Kumar Lilhore, Yogesh Kumar Sharma, K. B. V. Brahma Rao + 4 more
'K. B. V. Brahma Rao' 'V. V. R. Maheswara Rao' 'Anupam Baliyan' 'Anchit Bijalwan' 'Roobaea Alroobaea'] Virtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of…
Raju Singh
—Load Balancing is a critical technological advancement for scaled cloud infrastructure. It allows the systems to distribute the load to the backend servers with predefined algorithms such as round robin, weighted round-robin, least connection, weighted least connection, resource based (adaptive), weighted response…
Connor Rawls, Mohsen Amini Salehi
Load balancing is prevalent in practical application (e.g., web) deployments seen today. One such load balancer, HAProxy, remains relevant as an open-source, easy-to-use system. In the context of web systems, the load balancer tier possesses significant influence over system performance and the incurred cost, which is…
Chukwuneke Chiamaka Ijeoma, Prof. Inyiama, C. Hyacinth, Amaefule Samuel + 2 more
'Amaefule Samuel' 'Onyesolu Moses Okechukwu' 'Asogwa Doris Chinedu'] Abstract: In cloud computing environment, load balancing is a key issue which is required to distribute the dynamic workload over multiple machines to make certain that no single machine is overloaded. In recent research, many organizations lose…
Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash + 5 more
'Tiansheng Yang' 'Rajkumar Singh Rathore' 'Lu Wang' 'Sabeen Tahir' 'Sheikh Tahir Bakhsh'] In general, edge computing networks are based on a distributed computing environment and hence, present some difficulties to obtain an appropriate load balancing, especially under dynamic workload and limited resources. The…
Maia, Diogo, Correia, Filipe + 4 more
To address this gap, we analyzed existing literature and tools to identify common orchestration practices. Based on our findings, we define three key orchestration resource optimization patterns: Preemptive Scheduling, Service Balancing, and Garbage Collection. Preemptive Scheduling allows the allocation of sufficient…
Bartłomiej Przybylski, Paweł Żuk, Krzysztof Rzaḑca
—Cloud resource management is often modeled by two-dimensional bin packing with a set of items that correspond to tasks having fixed CPU and memory requirements. However, applications running in clouds are much more flexible: modern frameworks allow to (horizontally) scale a single application to dozens, even hundreds…
Yousef Sanjalawe, Salam Fraihat, Salam Al-E’mari, Mosleh Abualhaj + 3 more
'Sharif Makhadmeh' 'Emran Alzubi' 'Davide La Torre'] The increasing dependence on cloud computing as a cornerstone of modern technological infrastructures has introduced significant challenges in resource management. Traditional load-balancing techniques often prove inadequate in addressing cloud environments’ dynamic…
Somaye Imanpour, Ahmadreza Montazerolghaem, Saeed Afshari
The Internet of Multimedia Things (IoMT) represents a significant advancement in the evolution of IoT technologies, focusing on the transmission and management of multimedia streams. As the volume of data continues to surge and the number of connected devices grows exponentially, internet traffic has reached…
Varun C. M, Anto Kumar R. P, Paulraj D, Priyanka P. S + 1 more
To increase cloud computing utilization and performance, efficient load balancing and resource distribution techniques are essential. Dynamic load balancing and resource allocation in cloud systems is necessary due to a number of reasons, but this is not an easy and straightforward task. The primary goal of dynamic…
Seong-Hyun Kim, Taehong Kim, Antonio Guerrieri
KubeEdge is an open-source platform that orchestrates containerized Internet of Things (IoT) application services in IoT edge computing environments. Based on Kubernetes, it supports heterogeneous IoT device protocols on edge nodes and provides various functions necessary to build edge computing infrastructure, such as…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Juechu Dong, Xueshen Liu, Harisankar Sadasivan, Sriranjani Sitaraman + 1 more
Long-read DNA sequencing is becoming increasingly popular for genetic diagnostics. Minimap2 is the state-of-the-art long-read aligner. However, Minimap2’s chaining step is slow on the CPU and takes 40-68% of the time especially for long DNA reads. Prior works in accelerating Minimap2 either lose mapping accuracy, are…
Ayca Aygun, Thuan Nguyen, Matthias Scheutz
Robust estimation of systemic human cognitive states is critical for many applications, from simply detecting inefficiencies in human task performance to adapting the behaviors of artificial agents to improve team performance in mixed-initiative human-machine teams. Here we use comprehensive analyses of a multi-modal…
Xiaoguang Liu, Lu Shi, Cong Ye, Yangyang Li + 1 more
In the actual operation task, the workload of the oceanaut is mainly mental workload. For the oceanaut, too high or too low mental workload will significantly reduce work efficiency and even lead to major safety accidents. Classification of mental workload of the oceanaut in operational task research is one of the key…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…