In this paper, we study the server provisioning problem for continuous Distributed Interactive Applications (DIAs) whose application states not only change because of the operations performed by participants, but also evolve along with the passing of time. We focus on finding the locations of servers for hosting continuous DIAs, with the goals of optimizing the interactivity performance while fulfilling the consistency and fairness requirements. We show that the server provisioning problem is challenging by presenting its NP-hardness and non-approximability results under several conditions. We propose two efficient server placement algorithms and analyze their approximation ratios. The approximation ratio of the proposed M-BETTER algorithm is quite close to a lower bound for any polynomial-time algorithm. We also conduct experimental evaluations to compare the proposed algorithms with several baseline server placements.

Increasing geographical spreads of modern distributed interactive applications (DIAs) make distributed server deployment vital for combating network latency and improving the interactivity among participants. In this paper, we investigate the server provisioning problem that concerns where to place servers for DIAs. We formulate the server provisioning problem with an objective of reducing the network latency involved in the interaction between participants. We prove that the problem is NP-hard under several scenarios. We analyze the performance of the classical k-median server placement for DIAs and propose a new greedy server provisioning heuristic for DIAs. Theoretical analysis shows that the approximation ratio of the proposed greedy algorithm is much lower than that of the k-median placement. Experiments using real Internet latency data also show that our proposed algorithm significantly outperforms the k-median and other baseline server placements.

Increasing geographical spreads of modern distributed interactive applications (DIAs) make distributed server deployment vital for combating network latency and improving the interactivity among participants. In this paper, we investigate the server provisioning problem that concerns where to place servers in DIAs. We formulate the server provisioning problem with an objective of reducing the network latency involved in the interaction between participants. We prove that the problem is NP-hard under any one of the following three scenarios that may be common in practice: (a) the network latency does not satisfy the triangle inequality; or (b) the choices of server locations in the network are restricted; or (c) the number of server locations to select is limited. Then, we propose an efficient greedy server provisioning heuristic, analyze its approximation ratio and give a tight example. Experiments using real Internet latency data show that our proposed algorithm significantly outperforms traditional k-median and k-center server placements.

An Interest Management (IM) mechanism eliminates irrelevant status updates transmitted in Distributed Virtual Environments (DVE). This paper proposes a new hierarchical IM mechanism for DVEs. The hierarchical mechanism divides the virtual world into multiple levels of cells and keeps the relationship between an entity and an Area-Of-Interest (AOI) at a particular cell level according to their relative position. As their relative position changes, the relationship level is updated accordingly. Compared with the traditional area-based and cell-based mechanisms, the proposed hierarchical mechanism significantly reduces the communication bandwidth consumption of IM and thus considerably improves the scalability of DVEs. In addition, the proposed mechanism also has much lower computation cost than the traditional mechanisms and very acceptable storage requirement for its data structures.

Recent years have witnessed the enormous popularity of distributed interactive applications (DIAs), which allow participants that are distributed in the network to interact with each other concurrently. The rapid growth of DIAs has raised stringent requirements on providing realistic sense of interaction between participants, whose quality is heavily influenced by network latencies. Although network latencies cannot be eliminated due to geographical spreads of participants, it is possible to reduce them by a smart selection of the locations where the servers of the DIAs are placed. The locations of servers affect not only the inter-server latencies but also the latencies from participants to servers, both of which are involved in the interactions among participants. Thus, the placement of servers is an important factor to the interactivity performance of DIAs. We formulate the server placement problem, and propose to solve it by an enhanced genetic algorithm, whose genetic operators are specially designed based on the nature of the problem. Experimental results using various datasets show that our algorithm leads to appreciable improvement of the interaction quality in DIAs.