Allocation and Admission Policies for Service Streams

简单与最优动态服务器分配策略性能差距量化

Quantifying the Performance Gap for Simple Versus Optimal Dynamic Server Allocation Policies

本文研究动态服务器分配策略的性能差异，提出简单策略模型和分析方法，并通过半马尔可夫决策模型量化最优策略与简单策略的性能差距，探讨多站点系统中状态依赖路由的潜在性能优势。

Resource Allocation in One-dimensional Distributed Service Networks with Applications

We consider assignment policies that allocate resources to users, where both resources and users are located on a one-dimensional line. First, we consider unidirectional assignment policies that allocate resources only to users located to their left. We propose the Move to Right (MTR) policy, which scans from left to right assigning nearest rightmost available resource to a user, and contrast it to the Unidirectional Gale-Shapley (UGS) matching policy. While both policies among all unidirectional policies, minimize the expected distance traveled by a request (request distance), MTR is fairer. …

On the tradeoff of average delay, average service cost, and average utility for single server queues with monotone policies

In this thesis, we study the optimal tradeoff of average delay, average service cost, and average utility for single server queueing models, with and without admission control. The continuous time and discrete time queueing models that we consider are motivated by cross-layer models for noisy point-to-point links, with random packet arrivals. We study the above tradeoff problem for a class of admissible policies, which are monotone and stationary and obtain an asymptotic characterization of the minimum average delay as a function of the average service cost and average utility constraints.

Resource Allocation in One-dimensional Distributed Service Networks

We consider assignment policies that allocate resources to users, where both resources and users are located on a one-dimensional line. First, we consider unidirectional assignment policies that allocate resources only to users located to their left. We propose the Move to Right (MTR) policy, which scans from left to right assigning nearest rightmost available resource to a user, and contrast it to the Unidirectional Gale-Shapley (UGS) matching policy. While both these policies are optimal among all unidirectional policies, we show that they are equivalent with respect to the expected distance…

优先考虑延迟与利润：一种基于DRL的5G网络切片准入控制

Prioritizing Latency with Profit: A DRL-Based Admission Control for 5G Network Slices

针对现有DRL框架忽略服务延迟导致QoS违规的问题，提出延迟与利润感知的准入控制方案DePSAC，通过延迟感知奖励函数和Boltzmann探索优化5G网络切片的QoS与利润权衡。

PSACCF: Prioritized Online Slice Admission Control Considering Fairness in 5G/B5G Networks

5G/B5G is envisioned to support various services with the assistance of network slices, each slice instance asks for adequate resources to provide the pre-negotiated service quality to its subscribers. Slice Admission Control (SAC) algorithm is a necessity for Slice Providers (SPs) to guarantee the QoS and QoE of each admitted request with limited resources. In that circumstance, the priority concern of services and the fairness of resource allocation arise as meaningful topics for researchers. The former originates from the innate characteristics of various services supported by 5G networks, …

Optimal control policies for resource allocation in the Cloud: comparison between Markov decision process and heuristic approaches

We consider an auto-scaling technique in a cloud system where virtual machines hosted on a physical node are turned on and off depending on the queue's occupation (or thresholds), in order to minimise a global cost integrating both energy consumption and performance. We propose several efficient optimisation methods to find threshold values minimising this global cost: local search heuristics coupled with aggregation of Markov chain and with queues approximation techniques to reduce the execution time and improve the accuracy. The second approach tackles the problem with a Markov Decision Proc…

Towards Cost-Optimal Policies for DAGs to Utilize IaaS Clouds with Online Learning

Premier cloud service providers (CSPs) offer two types of purchase options, namely on-demand and spot instances, with time-varying features in availability and price. Users like startups have to operate on a limited budget and similarly others hope to reduce their costs. While interacting with a CSP, central to their concerns is the process of cost-effectively utilizing different purchase options possibly in addition to self-owned instances. A job in data-intensive applications is typically represented by a directed acyclic graph which can further be transformed into a chain of tasks. The key …