Equilibrium is priceless: selfish task allocation for mobile crowdsourcing network

Abstract

Recent years have witnessed major innovations in mobile crowdsourcing networks. For selfish participants, conventional methods resort to incentive mechanism design for resource utilization, which might overlook the inherent equilibrium property among mobile users. In contrast to these proposals, we investigate the problem that whether or not the selfish users could be enabled to endorse stable task sharing with balanced allocations without incentive mechanism designs. Before making a positive answer to this problem, we need to address the following challenge, i.e., users have to make their balancing decisions with only very limited and dynamic local load information, which could possibly incur longer convergence time and imbalanced task allocations. In tackling this difficulty, we propose two distributed selfish load balancing schemes, the max-weight best response policy for strong information scenario, where load information could be sufficiently collected; and the proportional allocation policy for weak information scenario. We make experimental studies to validate proposed schemes. In our simulation study with real trace data, the proposed schemes converge fast in many typical settings with fairly good balancing performance. As for data traces from RollerNet (Tournoux et al., The accordion phenomenon 2009), the performance of load balancing and convergence property are further validated.

FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks

“…Meanwhile, mobile user's task arriving rate at cloudlet i is sampled from the Normal distribution N (4, 2) > 0. We adopt three baseline methods for comparison, including random task offloading, proportional task offloading [26] and greedy task offloading [24]. We run the simulation codes on a Dell laptop with Intel Core i5 CPU, 8GB RAM.…”

“…Second, by leveraging the '2-choice' paradigm for selecting the target for computation offloading, FairEdge only probes load information from two contactable neighboring cloudlets for comparison. According to [26] and [24], such a process would significantly reduce the complexity overhead to O(1) compared with greedy offloading's O(n) complexity.…”

A Crowdsensing-Based Real-Time System for Finger Interactions in Intelligent Transport System

“…Crowdsensing is one kind of fusing [4]. Crowdsensing, as a special form of crowdsourcing [5,6], leverages human intelligence/experience from the general public and social interactions to create participatory sensor networks to solve specific problems collaboratively [7].…”