Resource allocation in a client/server hybrid network for virtual world environments

Abstract

The creation of a virtual world environment (VWE) has significant costs, such as maintenance of server rooms, server administration, and customer service. The initial development cost is not the only factor that needs to be considered; factors such as the popularity of a VWE and unexpected technical problems during and after the launch can affect the final cost and success of a VWE. The capacity of servers in a client/server VWE is hard to scale and cannot adjust quickly to peaks in demand while maintaining the required response time. To handle these peaks in demand, we propose to employ users' computers as secondary servers. The introduction of users' computers as secondary servers allows the performance of the VWE to support an increase in users. In this study, we develop and implement five static heuristics to implement a secondary server scheme that reduces the time taken to compute the state of the VWE. The number of heterogeneous secondary servers, conversion of a player to a secondary server, and assignment of players to secondary servers are determined by the heuristics implemented in this study. A lower bound of the performance is derived to evaluate the results of the heuristics.

Robust resource allocation in a massive multiplayer online gaming environment

“…load computation the RTmax of the system was decreased by an order of magnitude. This study is different from the research in [9] because this study evaluates the performance of the heuristics based on a robustness metric. Both this study and [9] use a very similar system model.…”

“…This study is different from the research in [9] because this study evaluates the performance of the heuristics based on a robustness metric. Both this study and [9] use a very similar system model. In [9], the optimization criteria was to minimize RTmax.…”

“…The goal of this research is to maximize the number of users allowed to be added during a game session while maintaining fairness. Subsequent to our work in [9], a related concept was presented in [18]. This work presented a hybrid server similar to the one we considered.…”

“…In [9], it was shown that by employing users' computers to off-(1) Create the tabu list of size size tabu .…”

“…Both this study and [9] use a very similar system model. In [9], the optimization criteria was to minimize RTmax. The goal of this research is to maximize the number of users allowed to be added during a game session while maintaining fairness.…”