领域：学术论文 · 应用学科

Abstract
The landscape of mobile gaming has evolved significantly over the years, with profound changes in network reliability and traffic patterns. In the early 2010s, mobile games faced challenges due to unreliable networks and primarily featured asynchronous gameplay. However, in the current era, modern mobile games benefit from robust network connectivity, mirroring PC gaming experiences by relying on persistent connections to game servers. This shift prompted us to conduct an in-depth traffic analysis of two mobile games that represent opposite ends of the genre spectrum: a massively multiplayer game resembling PC MMORPGs with tightly synchronized gameplay, and a single-player puzzle game that incorporates asynchronous social interactions. Surprisingly, both games exhibited remarkably similar traffic footprints; small packets with short inter-packet arrival times, indicating their high expectations for network reliability. This suggests that game developers now prioritize network quality similarly to their PC gaming counterparts. Additionally, our analysis of packet lengths unveiled that recent mobile games predominantly employ short packets dominated by a few key packet types closely tied to player actions, which conforms to observations from PC online games. However, the self-similarity in traffic patterns, a notable feature in PC online games, only partially explains the traffic in mobile games, varying across genres. These findings shed light on the evolving traffic patterns in mobile games and emphasize the need for further research in this dynamic domain.
Keywords: mobile games; traffic analysis; Internet measurement
1. Introduction
Network traffic analysis reports have illustrated that gaming is one of the most popular Internet applications, accounting for an estimated 8–10% of total Internet traffic and ranking as the third biggest traffic source after video streaming and web applications, including social media [1,2,3]. Another report highlights that 92.3% of Internet users access the Internet using mobile phones, with gaming being the most common use for these devices [4]. Given that game servers are typically hosted in cloud data centers and that game service providers incur significant costs for network traffic, understanding mobile game traffic patterns is crucial, not only from an engineering viewpoint but also from a business perspective.
As mobile devices, including smartphones and tablets, have become the prevailing service environment for the gaming industry, game genres that run on mobile devices have also become diverse and complicated. In the early era of networked mobile gaming in the 2010s, most mobile games were asynchronous due to the poor robustness and high cost of mobile networks. In these games, players could interact with other players, such as family members and friends, but they generally played independently rather than tightly together.
On the other hand, today’s mobile network technology, especially in metropolitan areas, has significantly improved in connection stability. A recent survey showed that from October 2022 through March 2023, 5G and 4G networks in the UK exhibited 98.4% and 97.8% connection success rates on average, respectively, when a mobile device becomes active [5]. This suggests that mobile games enjoy much more robust network connectivity, even in the mobile network, and thus such games now rely more on a persistent network connection to the game server. This phenomenal change suggests that the current underlying network traffic patterns might differ from those of the 2010s and from those in the PC gaming environment.
This paper illustrates traffic analysis from two mobile games with global service. The analyzed games represent opposite extremes in terms of their genre. One is strongly synchronized and a massive multiplayer game similar to that of a PC environment, but with an “auto-hunt” feature to allow gameplay without human engagement. The other is less synchronized and primarily played by a single player, although it also features social interactions among players.
The primary contribution of our work is demonstrating that recent mobile games exhibit traffic patterns akin to those in PC games, particularly regarding packet length and inter-packet arrival times, but have differences regarding traffic self-similarity. Our analysis of the games’ traffic traces reveals that current mobile games typically feature notably short inter-packet arrival times, similar to traditional multiplayer games in the PC environment, accompanied by a long-tail distribution due to the intermittent sleep and resume nature of mobile applications. Concerning packet lengths, recent mobile games predominantly use shorter packets, favoring them over aggregated larger packets to conserve network bandwidth. These patterns, observed consistently across different game genres, suggest that modern mobile games are developed with expectations of reliable network connectivity, a notable shift from earlier in the 2010s. This consistency in traffic characteristics, irrespective of game genre, underscores a fundamental similarity in network usage between contemporary mobile and PC gaming platforms. Our analysis, however, discovered that the presence of self-similarity in traffic patterns, identified by previous research on PC online games’ traffic patterns, varies across game genres. This finding encourages further research to model mobile game traffic.
This paper is organized as follows: Section 2 reviews research related to the mobile gaming industry. Section 3 briefly introduces the mobile games analyzed and explains the methods for collecting and anonymizing traffic data. In Section 4, we describe our analysis methodology and present key findings. Finally, Section 5 summarizes these findings and proposes directions for future research.
2. Related Work
Reports have shown that gaming is the most popular activity among mobile device users. Furthermore, gaming activities, which include those on PCs, mobile devices, and consoles, collectively constitute the third largest source of total Internet traffic [1,2,3,4]. Despite its significance in the context of today’s Internet traffic, there is a notable dearth of comprehensive research on mobile game traffic. In contrast, considerable research efforts have been directed towards analyzing PC online game traces, modeling traffic patterns, and optimizing traffic [6,7,8,9,10,11,12,13]. Previous research agrees that PC online games generate highly periodic bursty short packets. In particular, Chen et al. discovered traffic exhibits pronounced periodicity and temporal locality in inter-packet arrival times, attributable to player action patterns by a comprehensive traffic analysis using substantial packet traces from a PC MMORPG game [11]. Feng et al. also observed that the distribution of game session time in PC games is not heavy-tailed, a characteristic stemming from the synchronized nature of gameplay [12]. Henderson et al. explored the network quality of service (QoS) tolerance of game players [14]. Apart from previous research mainly focusing on PC online games, our work fills the gap for mobile games. We confirmed that mobile games share similarities with PC online games regarding traffic patterns while having unique differences at the same time. Chen et al. conducted a preliminary traffic analysis using Pokémon Go, which is a mobile AR game [15], but their preliminary results did not uncover relationships with PC online games.
There is considerable research measuring the real-life performance of various mobile network technologies (i.e., the 3G, 4G, and 5G) [5,16,17,18,19,20,21,22,23]. Based on these research findings, mobile application developers can reasonably assume that even 4G LTE, currently the most prevalent mobile network worldwide, can provide an average round-trip time (RTT) of about 50 ms between a carrier network and a player’s device in metro areas. In particular, Ref. [22] reports that a study conducted in London showed a 5-millisecond latency could be achieved with 99.999% reliability over a 5G network. This research indicates that applications, including games, running on mobile networks can reliably expect lower latency as mobile infrastructure evolves. The finding in mobile network robustness is the main motivation for our research on mobile game traffic patterns.
Kämäräinen et al. investigated factors contributing to end-to-end latency in cloud gaming, where game scenes are rendered at cloud servers. Their research highlights emerging technologies that could enhance gaming experiences demanding high network bandwidth and strict latency constraints [24]. Similarly, Braud et al. conducted research on mobile AR applications, which require computational offloading to cloud servers and are, therefore, also subject to network bandwidth and latency limitations [25]. Despite the disruptive approach of cloud gaming, it was not widely deployed in the mobile gaming industry because of high costs and the limited robustness of mobile networks. This approach is, however, being revitalized by the rapid emergence of virtual reality technologies and technological improvements in mobile networks. Therefore, understanding mobile traffic characteristics through our research can also contribute to cloud gaming.
3. Materials and Methods
Due to the exclusivity or closed nature of the gaming industry, game traffic traces are not readily accessible, even in anonymized form. Game companies hesitate to release traffic traces not only because of concerns over players’ privacy information but also due to fears that the data might be used to compromise the security of their services. This partially explains why there has been limited research conducted on the network traffic characteristics of online/mobile games, despite their significance in terms of traffic usage.
For this limitation, we selected two representative game genres at opposite ends of the spectrum and collected network traffic traces from a mobile game for each genre. The games are globally serviced and independently developed and operated by different game companies. Therefore, the games do not share any specific development methodology or assumptions about underlying network behavior.
 

翻译考点：
考点 1：“traffic patterns” 应译为 “流量模式 / 流量特征”
考点 2：“asynchronous gameplay” 应译为 ”异步游戏玩法”
考点 3：“persistent connections” 应译为 “持久连接”
考点 4：“asynchronous social interactions 应译为 “异步社交互动”
考点 6：“traffic footprints” 应译为 “ 流量足迹”
考点 7：“inter-packet arrival times” 应译为 “分组间到达时间“
考点 8：“packet lengths” 应译为 ”数据包长度“
考点 9：“mobile devices” 应译为 “移动设备”
考点 10：“persistent network connection” 应译为 “持续网络连接“
考点 11：”traffic traces“ 应译为 ”流量轨迹 / 流量跟踪数据“
考点 12：“long-tail distribution” 应译为 “长尾分布”
考点 13：“game session time“ 应译为 “游戏会话时长“
考点 14：”Quality of Service (QoS)“ 应译为 ”服务质量“
考点 15：“packet traces” 应译为 “数据包跟踪数据”
考点 16：“Pokémon Go“ 应译为 “精灵宝可梦 Go“
考点 17：”round-trip time (RTT)“ 应译为 ”往返时延“
考点 18："latency" 应译为 “时延 / 延迟”
考点 19："cloud gaming" 应译为 “云游戏“
考点 20："end-to-end latency" 应译为 "端到端时延"
考点 21："computational offloading" 应译为 "计算卸载"
考点 22："network traffic characteristics" 应译为 "网络流量特征"