Settling for less

Abstract

In recent years smartphones have become increasingly popular. In April 2011, Google claimed that around 350000 Android smartphones are being activated daily. A smartphone is a device equipped with a range of sensors, a gigahertzrange CPU, and high bandwidth wireless networking capabilities. The power and increasing prevalence of smartphones in combination with current research on opportunistic mobile networking have (1) increased the range of applications that could be supported on an opportunistic mobile network and (2) given birth to new fields of research such as mobile crowd computing [5] that are geared towards largescale distributed computations. An opportunistic network is created between mobile phones using local peer-to-peer connections. The nodes in such a network are mobile phones carried by human users on the move, and a link between two phones represent the fact that the corresponding phone users are within each other’s wireless communication range. Opportunistic networks are usually intermittently connected and are characterized by social-based mobility and heterogeneous contact rate. Their basic principle of operation is based on the store-and-forward strategy [2]. Keeping in mind the fact that opportunistic networks in the near future will primarily comprise of smartphones as nodes, and would be geared towards servicing numerous applications of varied QoS demands, the opportunistic network research community today still face three basic hurdles to achieving good performance on most applications. User mobility is one such hurdle. In a relatively sparse network, user mobility might lead to network disconnectivity at times, which in turn increases response time of a user application. The second hurdle is the uncertainty in the quality of the wireless transmission channel. Effects like fading, shadowing, and interference might result in data packets being lost during transmission or being transmitted at a low speeds. Finally, individual user selfishness is a psychological hurdle which users in an opportunistic network face. A mobile user would be unwilling to forward packets for someone it does not know due to (1) individual security concerns and (2) it unnecessarily expending battery power and computation resources for an application it has no relation with. Under the above mentioned hurdles, it is not guaranteed that user QoS demands could be satisfied to a certain degree at all times let alone guaranteeing complete user satisfac-