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Recently, coding has been a useful technique to mitigate the effect of stragglers in distributed computing. However, coding in this context has been mainly explored under the assumption of homogeneous workers, although the real-world…
The state-of-art of the technology focuses on data processing to deal with massive amount of data. Cloud computing is an emerging technology, which enables one to accomplish the aforementioned objective, leading towards improved business…
Modern GPU-based high-performance computing clusters offer unprecedented communication bandwidth through heterogeneous intra-node interconnects and inter-node networks. However, despite this high aggregate bandwidth, many real-world…
Cloud computing is a technological advancement in the arena of computing and has taken the utility vision of computing a step further by providing computing resources such as network, storage, compute capacity and servers, as a service via…
Unbalanced power, due to high penetration of single-phase PV rooftops into a four-wire multi-grounded LV distribution system, can result in significant rise in the neutral current and neutral voltage. This preprint proposes a distributed…
Blockchain technology, while revolutionary in enabling decentralized transactions, faces scalability challenges as the ledger must be replicated across all nodes of the chain, limiting throughput and efficiency. Sharding, which divides the…
The problem of finding clusters in complex networks has been extensively studied by mathematicians, computer scientists and, more recently, by physicists. Many of the existing algorithms partition a network into clear clusters, without…
A novel and intuitive nearest neighbours based clustering algorithm is introduced, in which a cluster is defined in terms of an equilibrium condition which balances its size and cohesiveness. The formulation of the equilibrium condition…
Distributed databases often suffer unequal distribution of data among storage nodes, which is known as `data skew'. Data skew arises from a number of causes such as removal of existing storage nodes and addition of new empty nodes to the…
This paper presents a distributed resource selection mechanism for diverse cloud-edge environments, enabling dynamic and context-aware allocation of resources to meet the demands of complex distributed applications. By distributing the…
In this paper we formulate the fixed budget resource allocation game to understand the performance of a distributed market-based resource allocation system. Multiple users decide how to distribute their budget (bids) among multiple machines…
Worldwide, storage demands and costs are increasing. As a consequence of fault tolerance, storage device heterogenity, and data center specific constraints, optimal storage capacity utilization cannot be achieved with the integrated…
As cloud computing services rapidly expand their customer base, it has become important to share cloud resources, so as to provide them economically. In cloud computing services, multiple types of resources, such as processing ability,…
This paper proposes a novel approach to address the challenges of deploying complex robotic software in large-scale systems, i.e., Centralized Nonlinear Model Predictive Controllers (CNMPCs) for multi-agent systems. The proposed approach is…
We consider robust resource allocation of services in Clouds. More specifically, we consider the case of a large public or private Cloud platform that runs a relatively small set of large and independent services. These services are…
Analyzing large datasets with distributed dataflow systems requires the use of clusters. Public cloud providers offer a large variety and quantity of resources that can be used for such clusters. However, picking the appropriate resources…
The Cloud Computing paradigm consists in providing customers with virtual services of the quality which meets customers' requirements. A cloud service operator is interested in using his infrastructure in the most efficient way while…
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…
An efficient MCMC algorithm is presented to cluster the nodes of a network such that nodes with similar role in the network are clustered together. This is known as block-modelling or block-clustering. The model is the stochastic blockmodel…
In this paper, a supervised clustering based-heuristic is proposed for the real-time implementation of approximate solutions to stochastic nonlinear model predictive control frameworks. The key idea is to update on-line a low cardinality…