Degree

Doctor of Philosophy (PhD)

Department

School of Electrical Engineering and Computer Science

Document Type

Dissertation

Abstract

Massively multiplayer online games (MMOGs) have been very popular over the past decade. The infrastructure necessary to support a large number of players simultaneously playing these games raises interesting problems to solve. Since the computations involved in solving those problems need to be done while the game is being played, they should not be so expensive that they cause any noticeable slowdown, as this would lead to a poor player perception of the game. Many of the problems in MMOGs are NP-Hard or NP-Complete, therefore we must develop heuristics for those problems without negatively affecting the player experience as a result of excessive computation. In this dissertation, we focus on a few of the problems encountered in MMOGs – the Client Assignment Problem (CAP) and both centralized and distributed load balancing – and develop heuristics for each. For the CAP we investigate how best to assign players to servers while meeting several conditions for satisfactory play, while in load balancing we investigate how best to distribute load among game servers subject to several criteria. In particular, we develop three heuristics - a heuristic for a variant of the CAP called Offline CAP-Z, a heuristic for centralized load balancing called BreakpointLB, and a heuristic for distributed load balancing called PLGR. We develop a simulator to simulate the operations of an MMOG and implement our heuristics to measure performance against adapted heuristics from the literature. We find that in many cases we are able to produce better results than those adapted heuristics, showing promise for implementation into production environments. Further, we believe that these ideas could also be easily adapted to the numerous other problems to solve in MMOGs, and they merit further consideration and augmentation for future research.

Date

6-28-2018

Committee Chair

Trahan, Jerry

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