Problem statement: Mobile Workforces (MW) unlike computational resources of an automated system are active but not passive entities. Therefore, an automated resource allocation system that deals with MWs should assign tasks to them fairly and in a comparatively equal manner. An unfair task allocation in a group will cause dissatisfaction, which in turn demotivates MWs who are supposed to work a...

In recent years, more and more attention has been paid to task allocation both in research [17, 21] and applications [4, 18]. Generally speaking, task allocations are carried out mainly in two circumstances: (i) agents are cooperative, and (ii) agents are noncooperative (also known as market-based), and this paper addresses the task allocation in noncooperative grid environment. In a cooperativ...

Dynamic coordination for task allocation in disaster environments under spatial and communicational constraints is a challenging issue in both research and applications. To this end, this paper presents a coordinated task allocation approach for disaster environments by considering spatial and communicational constraints, dynamic features of environments as well as heterogenous capabilities of ...

The coordination of dynamic task allocation based on available resources is very challenging in disaster domains under time, space and communication constraints. In addition, it is also very hard or even impossible to achieve tasks allocation by using a centralised manner with the global knowledge of the working environment. This paper presents a novel decentralised coordination approach for dy...

In mobile crowdsourcing, organizers usually need participants’ precise locations for optimal task allocation, e.g., minimizing selected workers’ travel distance to locations. However, the exposure of users’ raises privacy concerns. this paper, we propose a location privacy-preserving allocation framework with geo-obfuscation protect during assignments. More specifically, make participants obfus...

Mobile crowd sensing (MCS) is a popular paradigm that leverages the power of massive mobile workers to perform various location-based tasks. To assign with suitable tasks, recent research works investigated mobility prediction methods based on probabilistic and statistical models estimate worker’s moving behavior, which allocation algorithm designed match tasks such do not need deviate from the...