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Hyper-converged cloud refers to an architecture that an operator runs compute and storage services on the same set of physical servers. Although the hyper-converged design comes with a number of benefits, it makes crucial operational tasks,…
Although the computing power of mobile devices is increasing, machine learning models are also growing in size. This trend creates problems for mobile devices due to limitations like their memory capacity and battery life. While many…
Scheduling is essentially a decision-making process that enables resource sharing among a number of activities by determining their execution order on the set of available resources. The emergence of distributed systems brought new…
The microservice architectural style has gained much attention from both academia and industry recently as a novel way to design, develop, and deploy cloud-native applications. This concept encourages the decomposition of a monolith into…
After the advent of the Internet of Things and 5G networks, edge computing became the center of attraction. The tasks demanding high computation are generally offloaded to the cloud since the edge is resource-limited. The Edge Cloud is a…
Efficient and fair allocation of multiple types of resources is a crucial objective in a cloud/distributed computing cluster. Users may have diverse resource needs. Furthermore, diversity in server properties/ capabilities may mean that…
Serverless computing has emerged as an attractive deployment option for cloud applications in recent times. The unique features of this computing model include, rapid auto-scaling, strong isolation, fine-grained billing options and access…
In this research we use a decentralized computing approach to allocate and schedule tasks on a massively distributed grid. Using emergent properties of multi-agent systems, the algorithm dynamically creates and dissociates clusters to serve…
With more applications moving to the cloud, cloud providers need to diagnose performance problems in a timely manner. Offline processing of logs is slow and inefficient, and instrumenting the end-host network stack would violate the…
Modern applications can generate a large amount of data from different sources with high velocity, a combination that is difficult to store and process via traditional tools. Hadoop is one framework that is used for the parallel processing…
Converged computing brings together the best of both worlds for high performance computing (HPC) and cloud-native communities. In fact, the economic impact of cloud-computing, and need for portability, flexibility, and manageability make it…
Efficiently exploiting servers in data centers requires performance analysis methods that account not only for the stochastic nature of demand but also for server heterogeneity. Although several recent works proved optimality results for…
Designing fast and scalable algorithm for mining frequent itemsets is always being a most eminent and promising problem of data mining. Apriori is one of the most broadly used and popular algorithm of frequent itemset mining. Designing…
Emerging information-centric networking architectures seek to optimally utilize both bandwidth and storage for efficient content distribution. This highlights the need for joint design of traffic engineering and caching strategies, in order…
The beginning of the 21st century has seen many projects on distributed hash tables, both research and commercial. One of their aims has been to replace the first generation of file sharing software with scalable peer-to-peer architectures.…
Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed…
The Internet of things (IoT) generates a plethora of data nowadays, and cloud computing has been introduced as an efficient solution to IoT data management. A cloud resource administrator usually adopts the replication strategy to guarantee…
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…
Cloud computing has attracted both end-users and Cloud Service Providers (CSPs) in recent years. Improving resource utilization rate (RUtR), such as CPU and memory usages on servers, while maintaining Quality-of-Service (QoS) is one key…
Today's datacenters face important challenges for providing low-latency high-quality interactive services to meet user's expectation. For improving the application throughput, recent research works have embedded application deadline…