Application of Control Theory to a Commercial Mobile Service Support System

The Mobile Service Support system (MSS), which Ericsson AB develops, handles the setup of new subscribers and services into a mobile network. Experience from deployed systems show that traffic monitoring and control of the system will be crucial for handling overload situations that may occur at sudden traffic surges. In this paper we identify and explore some important control challenges for this type of systems. Further, we present analysis and experiments showing some advantages of proposed solutions. First, we develop a load-dependent server model for the system, which is validated in testbed experiments. Further, we propose a control design based on the model, and a method for estimation of response times and arrival rates. The main contribution of this paper is that we show how control theory methods and analysis can be used for commercial telecom systems. Parts of our results have been implemented in commercial products, validating the strength of our work

Resource Management in Computing Systems

Resource management is an essential building block of any modern computer and communication network. In this thesis, the results of our research in the following two tracks are summarized in four papers. The first track includes three papers and covers modeling, prediction and control for multi-tier computing systems. In the first paper, a NARX-based multi-step-ahead response time predictor for single server queuing systems is presented which can be applied to CPU-constrained computing systems. The second paper introduces a NARX-based multi-step-ahead query response time predictor for database servers. Both mentioned predictors can predict the dynamics of response times in the whole operation range particularly in high load scenarios without changes having to be applied to the current protocols and operating systems. In the third paper, queuing theory is used to model the dynamics of a database server. Several heuristics are presented to tune the parameters of the proposed model to the measured data from the database. Furthermore, an admission controller is presented, and its parameters are tuned to control the response time of queries which are sent to the database to stay below a predefined reference value.The second track includes one paper, covering a problem formulation and optimal solution for a content replication problem in Telecom operator's content delivery networks (Telco-CDNs). The problem is formulated in the form of an integer programming problem trying to minimize the communication delay and cost according to several constraints such as limited content replication budget, limited storage size and limited downlink bandwidth of each regional content server. The solution of this problem is a performance bound for any distributed content replication algorithm which addresses the same problem

Modeling and Control of Server-based Systems

When deploying networked computing-based applications, proper resource management of the server-side resources is essential for maintaining quality of service and cost efficiency. The work presented in this thesis is based on six papers, all investigating problems that relate to resource management of server-based systems. Using a queueing system approach we model the performance of a database system being subjected to write-heavy traffic. We then evaluate the model using simulations and validate that it accurately mimics the behavior of a real test bed. In collaboration with Ericsson we model and design a per-request admission control scheme for a Mobile Service Support System (MSS). The model is then validated and the control scheme is evaluated in a test bed. Also, we investigate the feasibility to estimate the state of a server in an MSS using an event-based Extended Kalman Filter. In the brownout paradigm of server resource management, the amount of work required to serve a client is adjusted to compensate for temporary resource shortages. In this thesis we investigate how to perform load balancing over self-adaptive server instances. The load balancing schemes are evaluated in both simulations and test bed experiments. Further, we investigate how to employ delay-compensated feedback control to automatically adjust the amount of resources to deploy to a cloud application in the presence of a large, stochastic delay. The delay-compensated control scheme is evaluated in simulations and the conclusion is that it can be made fast and responsive compared to an industry-standard solution