## 1 Introduction  
The rapid technology developments of wireless communications and micro electro mechanical systems (MEMSs) have made _mobile ad hoc networks (MANETs)_ possible. MANETs are infrastructure-less networks with mobile nodes, such as mobile devices, sensors, or vehicles. A MANET consisting of sensors forms a _mobile sensor network (MSN)_ while one consisting of vehicles forms a _vehicular ad hoc network (VANET)_. A major challenge of MANETs is that no centralized coordination can be adopted. Mobile nodes in MANETs have to be self-organizing, and data collection and distribution among them have to be decentralized. In addition, with a single, shared communication channel, the well-known hidden and exposed terminal problems may raise in MANETs. Several data collection and distribution mechanisms have been proposed for MANETs, which can be classified as _tree-based_, _mesh-based_, or _backbone-based_ solutions. Tree-based solutions [1; 2; 3; 4] use a tree to connect all multicast group members. However, links closer to the root suffer from heavier loads and failure of intermediate nodes is a serious issue. Mesh-based solutions [5; 6; 7] are more resilient to link failure, but the maintenance cost incurred is higher. Backbone-based solutions [8; 9; 10; 11] use a backbone to avoid flooding the network when a new member joins a multicast group. On the other hand, cycling has gained popularity in recent years due to concerns such as the environment and health [12]. Existing works include the bike-based mobile sensing system [13], sensor-based cyclist group tracking system [14], smartphone-based public bicycle sharing system [15], and networked bicycle platoon cooperation system [16]. In addition, multi-criteria urban bicycle routing [17] and cyclist crossing behavior model [18] are proposed for improving cycling experiences. A MANET with fleet cyclists using smartphones forms a two-tier _mobile long-thin network (MLTN)_ along a common cycling route, where the high-tier network consists of 3G/LTE interfaces and the low-tier network consists of IEEE 802.11 interfaces. In a fleet, individual sensing information (e.g., current position and activity, air quality, road vibration, etc.) and global status information (e.g., common messages, member locations, points of interests, social interactions, etc.) are frequently uploaded and downloaded by individual cyclists, respectively [19]. Although the energy-consuming problem using GPS for the up-to-date positions of cyclists is alleviated by cooperative energy-efficient localization [20], there are potential bandwidth and latency issues [21] that need to be addressed by optimizing sensing data collection and distribution among fleet cyclists. However, existing solutions for MANETs do not meet the requirements for a cycling fleet due to the following reasons: (1) The MANET topology is quite different from a cycling fleet. (2) The mobility patterns of a cycling fleet is not random; they follow a common cycling route. (3) The goal is to build a two-tier network while minimizing the high-tier cost. Several clustering mechanisms [22; 23; 24; 25; 26; 27; 28] for sensing data collection and distribution have been proposed in vehicular ad hoc networks (VANETs). Clustering in VANETs is a process of grouping nearby vehicles within the communication range into a cluster according to various rules, such as the current speed, moving direction, final destination, etc. Clusters are virtual groups formed by a clustering mechanism. Each group has one or more group headers that are selected or elected by other group vehicles. Additional roles of vehicles, such as group relays, may be defined in some clustering mechanisms. Group size is different from one group to another, which depends on the communication ranges of onboard units used by vehicles. The vehicles in a one-hop group can communicate with each other via the group header or directly while those in a multi-hop group can transmit messages to all members through additional group relays.