Abstract — As the technology available on cars is increasing, a wide range of applications, from safety to entertainment, are becoming factually accessible to passengers. Many of these applications involves a one-to-many transmission model where a single car broadcasts a message that has to be forwarded, even with multiple hops, in a very short time to all the other cars located within a range of few kilometers from the source. Since the high mobility and density of a car network scenario, specific solutions need to be devised to choreograph a fast-delivery multihop broadcast. To this aim, we developed a practical and efficient technique that allows cars to estimate their communication range with the help of a very limited message exchange and exploit this information to reduce the number of transmissions, as well as the hops to be traversed, and hence the time, required by a broadcasted message to reach all the cars following the sender within a certain distance.

Massively Multiplayer Online Games (MMOGs) are no longer a chimera. Day after day, new exemplars of this application are released, available for free on the Web or on sale. Yet, high lags frequently affect MMOGs annoying customers. This frustrating phenomenon is mainly due to the best-effort service provided by the Internet that is often responsible for congestion and loss of responsiveness. To address this challenging issue, we consider a mirrored game server architecture and present a mechanism aimed at accelerating the delivery of game events generated during game sessions. Our approach rests upon the use of an optimistic synchronization mechanism that exploits the semantics of the game to diminish the delivery time of game events, whilst maintaining the full consistency of the game state. Experimental results are reported confirming the adequacy of our approach.

Multiplayer online games have now become popular with millions across the globe, capturing the attention of both researchers and practitioners. Unfortunately, online games still have to deal with the limitations imposed by some unresolved issues. Interactivity, consistency, fairness, and scalability are the major requirements that need to be addressed efficiently in order to provide an appealing product to a huge number of potential customers worldwide. To answer this demand, we describe a holistic approach that can exploit the semantics of the game to satisfy the aforementioned requirements. We provide extensive and comparative results that demonstrate how our scheme copes efficiently with an elevated level of game traffic.

Abstract — Ensuring fairness among players engaged in online games is a challenging task. Yet, it is a fundamental requirement that can make the difference between having customers that persist or desist in using this kind of application. Answering to this demand, we present here an event delivery mechanism among mirrored game servers able to effectively uplift the fairness degree during game sessions through the heterogenesis of ends in targeting interactivity. We also provide extensive results that sustain our claim.

In this paper we discuss the viability of deploying Multiplayer Online Games (MOGs) over scale-free networks. We employ a general peer-to-peer overlay network; nodes have a number of neighbors which follows a power law distribution, pk ∼ k −α, the usual degree distribution that characterizes scale-free nets. Game events generated by nodes during the game evolution are disseminated through the network, based on some (push) gossip protocols run over the created overlay. We experiment with different gossip protocols. Results demonstrate that the employed gossip protocol may greatly influence the ability of disseminating the game data through the scale-free network. In particular, when gossip is performed using a small dissemination probability, a nonnegligible percentage of the network is not able to receive the message. This implies that not all players might be able to perceive the game event. Hence, parameters of gossip protocols must be properly tuned to guarantee a full network coverage. Concurrently, it is shown that, due to their low diameter, the use of scale-free networks allows to disseminate game events in very few steps. This could ensure a high level of responsiveness on the dissemination of game events, which is the main objective to pursue when dealing with MOGs.

Typical cheating avoidance solutions are able to prevent cheats, often at the cost of loosing interactivity in highly distributed games. With the need for responsiveness in view, we claim that (instead of preventing the cheat) cheating detection schemes could represent profitable solutions, which enable the identification of cheaters without impeding a realtime evolution of the game. Based on a general framework able to fairly model game time advancements which was recently proposed [4], we provide evidence of its effectiveness on a specific case of time cheat termed fast rate cheat. According to this malicious scheme, players alter the event generation rate of game events. We show that detection of fast rate cheat can be easily accomplished based on the proposed framework.

Online games represent one of the most important revenue sources for entertainment based companies and a challenging field in multimedia application research. With vehicular networks poised to become the new wireless frontier of the Internet, car passengers embody the next consumers that will be targeted by online game providers. Yet, the high mobility and heterogeneity of vehicular networks pose serious challenges to the deployment of efficient online game services such as, for instance, continuous variations in the number and type of flows served by access points along the road. To this aim, we discuss a solution based on the deployment of smart access points along the road and demonstrate how this solution is able to smoothen network traffic conditions, ensuring coexistence among heterogeneous types of flow even in presence of frequent network traffic variations.

Modern Massively Multiplayer Online Games (MMOGs) allow hundreds of thousands of players to interact with a large, dynamic virtual world. Implementing a scalable MMOG service is challenging because the system is subject to high workload variability, and nevertheless must always operate under very strict Quality of Service (QoS) requirements. Traditionally, MMOG services are implemented as large dedicated IT infrastructures with aggressive over-provisioning of resources in order to cope with the worst-case workload scenario. In this paper we address the problem of building a large-scale, multi-tier MMOG service using resources provided by a Cloud computing infrastructure. The Cloud paradigm allows customers to request as many resources as they need using a pay as you go model. We harness this paradigm by proposing a dynamic provisioning algorithm which can resize the resource pool of a MMOG service to adapt to workload variability and maintain a response time below a given threshold. We use a Queueing Network performance model to quickly estimate the system response time for different configurations. The performance model is used within a greedy algorithm to compute the minimum number of servers to be allocated on each tier in order to satisfy the system response time constraint. Numerical experiments are used to validate the effectiveness of the proposed approach.

Modern Massively Multiplayer Online Games (MMOGs) allow hundreds of thousands of players to interact with a large, dynamic virtual world. Implementing a scalable MMOG service is challenging because the system is subject to high variabilities in the workload, and nevertheless must always operate under very strict QoS requirements. Traditionally, MMOG services are implemented as large dedicated IT infrastructures with aggressive over-provisioning of resources in order to cope with the worst-case workload scenario. In this paper we address the problem of building a large-scale, multi-tier MMOG service using resources provided by a Cloud computing infrastructure. The Cloud paradigm allows the service providers to allocate as many resources as they need using a pay as you go model. We harness this paradigm by describing a dynamic provisioning algorithm which can resize the resource pool to adapt to workload variabilities, still maintaining a response time below a user-defined threshold. Our algorithm uses a Queueing Network performance model to quickly evaluate different configurations. Numerical experiments are used to validate the effectiveness of the proposed approach.