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Modern data analytic and machine learning jobs find in the cloud a natural deployment platform to satisfy their notoriously large resource requirements. Yet, to achieve cost efficiency, it is crucial to identify a deployment configuration…
Optimizing resource allocation for analytical workloads is vital for reducing costs of cloud-data services. At the same time, it is incredibly hard for users to allocate resources per query in serverless processing systems, and they…
We introduce a stochastic version of the cutting-plane method for a large class of data-driven Mixed-Integer Nonlinear Optimization (MINLO) problems. We show that under very weak assumptions the stochastic algorithm is able to converge to…
We study a fundamental online scheduling problem where jobs with processing times, weights, and deadlines arrive online over time at their release dates. The task is to preemptively schedule these jobs on a single or multiple (possibly…
The notion of age of information (AoI) has become an important performance metric in network and control systems. Information freshness, represented by AoI, naturally arises in the context of caching. We address optimal scheduling of cache…
Content Delivery Network (CDN) has been emerged as a compelling technology to provide efficient and scalable web services even under high client request. However, this leads to a dilemma between minimum deployment cost and robust service…
Serverless computing promises convenient abstractions for developing and deploying functions that execute in response to events. In such Function-as-a-Service (FaaS) platforms, scheduling is an integral task, but current scheduling…
Cache plays an important role to maintain high and stable performance (i.e. high throughput, low tail latency and throughput jitter) in storage systems. Existing rule-based cache management methods, coupled with engineers' manual…
Non-independent and identically distributed (Non-IID) data across edge clients have long posed significant challenges to federated learning (FL) training in edge computing environments. Prior works have proposed various methods to mitigate…
The demand for real-time cloud applications has seen an unprecedented growth over the past decade. These applications require rapidly data transfer and fast computations. This paper considers a scenario where multiple IoT devices update…
Mobile browser is known to be slow because of the bottleneck in resource loading. Client-only solutions to improve resource loading are attractive because they are immediately deployable, scalable, and secure. We present the first publicly…
In the last decades, the computational power of GPUs has grown exponentially, allowing current deep learning (DL) applications to handle increasingly large amounts of data at a progressively higher throughput. However, network and storage…
Data analytics in the cloud has become an integral part of enterprise businesses. Big data analytics systems, however, still lack the ability to take user performance goals and budgetary constraints for a task, collectively referred to as…
Multi-agent applications utilize the advanced capabilities of large language models (LLMs) for intricate task completion through agent collaboration in a workflow. Under this situation, requests from different agents usually access the same…
This paper optimizes the configuration of large-scale data centers toward cost-effective, reliable and sustainable cloud supply chains. The problem involves placing incoming racks of servers within a data center to maximize demand coverage…
Using artificial intelligence to manage IT operations, also known as AIOps, is a trend that has attracted a lot of interest and anticipation in recent years. The challenge in IT operations is to run steady-state operations without…
E-commerce Web-servers often face overload conditions during which revenue-generating requests may be dropped or abandoned due to an increase in the browsing requests. In this paper we present a simple, yet effective, mechanism for overload…
Function-as-a-Service (FaaS) has recently emerged to reduce the deployment cost of running cloud applications compared to Infrastructure-as-a-Service (IaaS). FaaS follows a serverless 'pay-as-you-go' computing model; it comes at a higher…
Unexpected loads in Cloud data centers may trigger overloaded situation and performance degradation. To guarantee system performance, cloud computing environment is required to have the ability to handle overloads. The existing approaches,…
In large-scale distributed file systems, efficient meta- data operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the…