2 citations · 5 across the 12 of their papers we have counts for
13 papers
Learning based Scalable Multi-Objective Scheduling of Workflows across UD-IaaS-FaaS Systems
G Vasantha Reddy, Ram Bansal, Krashna +2
Workflow scheduling in user device-centric edge-cloud computing has emerged as a challenging problem due to the need to jointly optimize execution performance, energy consumption,…
LLM-Based Multi-Agent Collaboration for Constrained Multi-Objective Container Placement
Suvarthi Sarkar, Abhishek Hazra, Akshat Mittal +1
Container placement in data centers must simultaneously minimize power consumption and maximize affinity preferences, while satisfying multi-resource capacity and anti-affinity con…
Adaptive K-PackCache: Cost-Centric Data Caching in Cloud
Suvarthi Sarkar, Aadarshraj Sah, Poddutoori Sweeya Reddy +1
Recent advances in data analytics have enabled the accurate prediction of user access patterns, giving rise to the idea of packed caching delivering multiple co accessed data items…
DSPE: Profit Maximization in Edge-Cloud Storage System using Dynamic Space Partitioning with Erasure Code
Shubhradeep Roy, Suvarthi Sarkar, Vivek Verma +1
Edge Storage Systems have emerged as a critical enabler of low latency data access in modern cloud networks by bringing storage and computation closer to end users. However, the li…
Scientific Workflow Scheduling in Cloud Considering Cold Start and Variable Pricing Model
Suvarthi Sarkar, Sparsh Mittal, Shivam Garg +1
Cloud computing has become a pivotal platform for executing scientific workflows due to its scalable and cost-effective infrastructure. Scientific Cloud Service Providers (SCSPs) a…
Cost-Effective Edge Data Distribution with End-To-End Delay Guarantees in Edge Computing
Ravi Shankar, Aryabartta Sahu
Cloud Computing is the delivery of computing resources which includes servers, storage, databases, networking, software, analytics, and intelligence over the internet to offer fast…
EDD-NSTE: Edge Data Distribution as a Network Steiner Tree Estimation in Edge Computing
Ravi Shankar, Aryabartta Sahu
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the user's geographical location to improve response times and save bandwidth.…
Efficient Scheduling of Vehicular Tasks on Edge Systems with Green Energy and Battery Storage
Suvarthi Sarkar, Abinash Kumar Ray, Aryabartta Sahu
The autonomous vehicle industry is rapidly expanding, requiring significant computational resources for tasks like perception and decision-making. Vehicular edge computing has emer…
Power Aware Container Placement in Cloud Computing with Affinity and Cubic Power Model
Suvarthi Sarkar, Nandini Sharma, Akshat Mittal +1
Modern data centres are increasingly adopting containers to enhance power and performance efficiency. These data centres consist of multiple heterogeneous machines, each equipped w…
QoS Aware Mixed-Criticality Task Scheduling in Vehicular Edge Cloud System
Suvarthi Sarkar, Aditya Trivedi, Ritish Bansal +1
Modern-day cars are equipped with numerous cameras and sensors, typically integrated with advanced decision-control systems that enable the vehicle to perceive its surroundings and…
Efficient Profit Maximization in Reliability Concerned Static Vehicular Cloud System
Suvarthi Sarkar, Akshat Arun, Harshit Surekha +1
Modern electric VUs are equipped with a variety of increasingly potent computing, communication, and storage resources, and with this tremendous computation power in their arsenal…
Scheduling Chained Multiprocessor Tasks onto Large Multiprocessor System
T. K. Agrawal, R. Sharma, M. Ghose +1
In this paper, we proposed an effective approach for scheduling of multiprocessor unit time tasks with chain precedence on to large multiprocessor system. The proposed longest chai…
Bufferless NOC Simulation of Large Multicore System on GPU Hardware
Navin Kumar, Aryabartta Sahu
Last level cache management and core interconnection network play important roles in performance and power consumption in multicore system. Large scale chip multicore uses mesh int…