Related papers: Automation of application-level caching in a seaml…
Placing applications in mobile edge computing servers presents a complex challenge involving many servers, users, and their requests. Existing algorithms take a long time to solve high-dimensional problems with significant uncertainty…
Pushing popular content to cheap "helper" nodes (e.g., small cells) during off-peak hours has recently been proposed to cope with the increase in mobile data traffic. User requests can be served locally from these helper nodes, if the…
In this paper we study online caching problems where predictions of future requests, e.g., provided by a machine learning model, are available. Typical online optimistic policies are based on the Follow-The-Regularized-Leader algorithm and…
Large language models (LLMs) have excelled in various applications, yet serving them at scale is challenging due to their substantial resource demands and high latency. Our real-world studies reveal that over 70% of user requests to LLMs…
In-network caching is likely to become an integral part of various networked systems (e.g., 5G networks, LPWAN and IoT systems) in the near future. In this paper, we compare and contrast model-based and machine learning approaches for…
Application Programming Interfaces (APIs), which encapsulate the implementation of specific functions as interfaces, greatly improve the efficiency of modern software development. As numbers of APIs spring up nowadays, developers can hardly…
Although every individual invented storage technology made a big step towards perfection, none of them is spotless. Different data store essentials such as performance, availability, and recovery requirements have not met together in a…
Coded caching is a technique that leverages locally cached contents at the end users to reduce the network's peak-time communication load. Coded caching has been shown to achieve significant performance gains compared to uncoded schemes and…
Emerging heterogeneous wireless architectures consist of a dense deployment of local-coverage wireless access points (APs) with high data rates, along with sparsely-distributed, large-coverage macro-cell base stations (BS). We design a…
We consider models of content delivery networks in which the servers are constrained by two main resources: memory and bandwidth. In such systems, the throughput crucially depends on how contents are replicated across servers and how the…
In wireless caching networks, a user generally has a concrete purpose of consuming contents in a certain preferred category, and requests multiple contents in sequence. While most existing research on wireless caching and delivery has…
The rapid growth of data volume and the accompanying congestion problems over the wireless networks have been critical issues to content providers. A novel technique, termed as coded cache, is proposed to relieve the burden. Through…
This paper addresses a fundamental limitation for the adoption of caching for wireless access networks due to small population sizes. This shortcoming is due to two main challenges: (i) making timely estimates of varying content popularity…
There are around a hundred installed apps on an average smartphone. The high number of apps and the limited number of app icons that can be displayed on the device's screen requires a new paradigm to address their visibility to the user. In…
The problem of content delivery in caching networks is investigated for scenarios where multiple users request identical files. Redundant user demands are likely when the file popularity distribution is highly non-uniform or the user…
Software development needs continuous quality control for a timely detection and removal of quality problems. This includes frequent quality assessments, which need to be automated as far as possible to be feasible. One way of automation in…
Web application providers have been migrating their applications to cloud data centers, attracted by the emerging cloud computing paradigm. One of the appealing features of the cloud is elasticity. It allows cloud users to acquire or…
While Deep Learning (DL) technologies are a promising tool to solve networking problems that map to classification tasks, their computational complexity is still too high with respect to real-time traffic measurements requirements. To…
Autoscaling is a hallmark of cloud computing as it allows flexible just-in-time allocation and release of computational resources in response to dynamic and often unpredictable workloads. This is especially important for web applications…
Cache-aided coded multicast leverages side information at wireless edge caches to efficiently serve multiple unicast demands via common multicast transmissions, leading to load reductions that are proportional to the aggregate cache size.…