Related papers: Efficient Large-Scale Multiple Migration Planning …
In this paper, we study and present a management and orchestration framework for vehicular communications, which enables service continuity for the vehicle via an optimized application-context relocation approach. To optimize the transfer…
Data center networks leverage multiple parallel paths connecting end host pairs to offer high bisection bandwidth for cluster computing applications. However, state of the art distributed multi-pathing protocols such as Equal Cost Multipath…
Lightweight containers provide an efficient approach for deploying computation-intensive applications in network edge. The layered storage structure of container images can further reduce the deployment cost and container startup time.…
Contemporary Distributed Computing Systems (DCS) such as Cloud Data Centres are large scale, complex, heterogeneous, and distributed across multiple networks and geographical boundaries. On the other hand, the Internet of Things…
Bulk transfers from one to multiple datacenters can have many different completion time objectives ranging from quickly replicating some $k$ copies to minimizing the time by which the last destination receives a full replica. We design an…
As novel applications spring up in future network scenarios, the requirements on network service capabilities for differentiated services or burst services are diverse. Aiming at the research of collaborative computing and resource…
Containers are standalone, self-contained units that package software and its dependencies together. They offer lightweight performance isolation, fast and flexible deployment, and fine-grained resource sharing. They have gained popularity…
We study an edge demand response problem where, based on historical edge workload demands, an edge provider needs to dispatch moving computing units, e.g. truck-carried modular data centers, in response to emerging hotspots within service…
We propose throughput and cost optimal job scheduling algorithms in cloud computing platforms offering Infrastructure as a Service. We first consider online migration and propose job scheduling algorithms to minimize job migration and…
As the demand of real time computing increases day by day, there is a major paradigm shift in processing platform of real time system from single core to multi-core platform which provides advantages like higher throughput, linear power…
Edge computing operates between the cloud and end users and strives to provide low-latency computing services for simultaneous users. Redundant use of multiple edge nodes can reduce latency, as edge systems often operate in uncertain…
Stateful migration has emerged as the dominant technology to support microservice mobility at the network edge while ensuring a satisfying experience to mobile end users. This work addresses two pivotal challenges, namely, the…
Emerging paradigms of big data and Software-Defined Networking (SDN) in cloud data centers have gained significant attention from industry and academia. The integration and coordination of big data and SDN are required to improve the…
Large Language Models (LLMs), as the foundational architecture for next-generation interactive AI applications, not only power intelligent dialogue systems but also drive the evolution of embodied intelligence on edge devices, including…
To meet the timing requirements of interactive applications, the no-frills congestion-agnostic transport protocols like UDP are increasingly deployed side-by-side in the same network with congestion-responsive TCP. In cloud platforms, even…
The recent advance of edge computing technology enables significant sensing performance improvement of Internet of Things (IoT) networks. In particular, an edge server (ES) is responsible for gathering sensing data from distributed sensing…
In an edge-cloud multi-tier network, datacenters provide services to mobile users, with each service having specific latency constraints and computational requirements. Deploying such a variety of services while matching their requirements…
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…
To effectively process high volume of data across a fleet of dynamic and distributed vehicles, it is crucial to implement resource provisioning techniques that can provide reliable, cost-effective, and timely computing services. This…
Deploying multiple controllers in the control panel of software-defined networks increases scalability, availability, and performance, but it also brings challenges, such as controller overload. To address this, load-balancing techniques…