A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era <s> V. DISCUSSION, CHALLENGES AND OPEN RESEARCH ISSUES <s> Recently, content-based publish/subscribe (pub/sub) services have become a significant research field in opportunistic mobile networks (OppNets). Pub/sub is an asynchronous messaging paradigm, in which content transmissions are guided by the interest. Since selfish behavior is common in reality, nodes often behave selfishly with an aim to maximize their own utilities without considering performance of other nodes. Therefore, how to encourage nodes to collect, store and share network content efficiently is one of the key challenges under this paradigm. In this paper, we propose an incentive-based pub/sub scheme, called ConSub, for OppNets. In ConSub, Tit-For-Tat (TFT) mechanism is employed to deal with selfish behavior. ConSub also implements a content exchange protocol between two interacting node, thus encouraging them to play as businessmen and carry contents to satisfy each other's interest. Specifically, the exchange order is determined by the content utility, which is calculated by contact probability and cooperation level between the current node and its neighbors subscribing to the interest. Extensive realistic trace-driven simulation results show that ConSub is superior to existing schemes in terms of delivered packets and transmission hops with reasonable transmission cost. <s> BIB001 </s> A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era <s> V. DISCUSSION, CHALLENGES AND OPEN RESEARCH ISSUES <s> Mobile crowdsensing is becoming a vital technique for environment monitoring, infrastructure management, and social computing. However, deploying mobile crowdsensing applications in large-scale environments is not a trivial task. It creates a tremendous burden on application developers as well as mobile users. In this paper we try to reveal the barriers hampering the scale-up of mobile crowdsensing applications, and to offer our initial thoughts on the potential solutions to lowering the barriers. <s> BIB002
Mobile crowd-sensing plays a key role in future smart cities. Two fundamental areas that have a significant impact are energy conservation and security. The main challenges in MCS are hardware cost, system architecture, wireless connectivity, programmability, and security. The current hardware cost of smartphones capable of tracking human mobility and location is moderately high. Their system architecture is capable supporting several applications on top of it. However, most of the applications and research examples are vertically integrated to maximize performance. Although MCS has great potential and offers many opportunities as mentioned above, it also has several challenges. The main challenges and open research issues facing MCS are the following: A. USERS PARTICIPATION Mobile crowd-sensing research has many challenges that need to be considered before deploying such systems on a large scale. One of these research challenges is finding an appropriate incentive mechanism that encourage users to participate in such system. One of the main challenges facing MCS is the availability of an adequate number of participants for the required application. The requirement can be also expressed in terms of participant geographical distribution. Therefore, incentive strategies, such as monetary or credit rewards, can be employed to increase the users' participation in MCS BIB001 . Minimizing the effect of running these applications on the performance of the smartphones (Minimizing the energy consumption, processing needs and network requirements) is also important to maintain the users' interest in the participation in MCS. The user participation becomes even more challenging in active participation since it requires more user's involvement. The research work in BIB002 discusses the barriers and shows that people are most likely to help when a minimum effort is required at no additional cost.