1 Introduction
2 Related work
3 System model and problem formulation
3.1 System model
3.2 Problem formulation
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The “ ε−N a s h” condition, i.e., for any 0≤ε≤1, no task can decrease the load by more than factor of (1−ε).
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The algorithm should converge fast enough, since the mobile crowdsourcing network only provides intermittent connections.
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First, we suppose mobile users have sufficient time and bandwidth, for sharing the task load information among all neighbor nodes. As depicted in Fig. 2 a, users could use WiFi connections and have relatively long contact window to share data, such working scenario is typical for crowdsourcing network [1].×
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Second, we consider the weak connection case, where the contact window is short or the transmission bandwidth is limited. For mobile crowdsourcing network, this concern is very necessary as such weak communication opportunities are very common. Although the data sharing is not sufficient, contacting with small number of users could be allowed, which is illustrated in Fig. 2 b.