Biblio

Predicting the success of a mobile game is a prime issue in game industry. Thousands of games are being released each day. However, a few of them succeed while the majority fail. Towards the goal of investigating the potential correlation between the success of a mobile game and its specific attributes, this work was conducted. More than 17 thousands games were considered for that reason. We show that specific game attributes, such as number of IAPs (In-App Purchases), belonging to the puzzle genre, supporting different languages and being produced by a mature developer highly and positively affect the success of the game in the future. Moreover, we show that releasing the game in July and not including any IAPs seems to be highly associated with the game’s failure. Our second main contribution, is the proposal of a novel success score metric that reflects multiple objectives, in contrast to evaluating only revenue, average rating or rating count. We also employ different machine learning models, namely, SVM (Support Vector Machine), RF (Random Forest) and Deep Learning (DL) to predict this success score metric of a mobile game given its attributes. The trained models were able to predict this score, as well as the rating average and rating count of a mobile game with more than 70% accuracy. This prediction can help developers before releasing their game to the market to avoid any potential disappointments.

This paper proposes a new cross-layer based packet scheduling scheme for multimedia traffic in satellite Long Term Evolution (LTE) network which adopts MIMO technology. The Satellite LTE air interface will provide global coverage and hence complement its terrestrial counterpart in the provision of mobile services (especially multimedia services) to users across the globe. A dynamic packet scheduling scheme is very important towards actualizing an effective utilization of the limited available resources in satellite LTE networks without compromise to the Quality of Service (QoS) demands of multimedia traffic. Hence, the need for an effective packet scheduling algorithm cannot be overemphasized. The aim of this paper is to propose a new scheduling algorithm tagged Cross-layer Based Queue-Aware (CBQA) Scheduler that will provide a good trade-off among QoS, fairness and throughput. The newly proposed scheduler is compared to existing ones through simulations and various performance indices have been used. A land mobile dual-polarized GEO satellite system has been considered for this work.